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Data Structures

284,375

4.6

Neil Rhodes

University of California San Diego

['Priority Queue', 'Binary Search Tree', 'Hash Table', 'List', 'Stack (Abstract Data Type)']

A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this online course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it. You will also learn typical use cases for these data structures. A few examples of questions that we are going to cover in this class are the following: 1. What is a good strategy of resizing a dynamic array? 2. How priority queues are implemented in C++, Java, and Python? 3. How to implement a hash table so that the amortized running time of all operations is O(1) on average? 4. What are good strategies to keep a binary tree balanced? You will also learn how services like Dropbox manage to upload some large files instantly and to save a lot of storage space! In this module, you will learn about the basic data structures used throughout the rest of this course. We start this module by looking in detail at the fundamental building blocks: arrays and linked lists. From there, we build up two important data structures: stacks and queues. Next, we look at trees: examples of how they’re used in Computer Science, how they’re implemented, and the various ways they can be traversed. Once you’ve completed this module, you will be able to implement any of these data structures, as well as have a solid understanding of the costs of the operations, as well as the tradeoffs involved in using each data structure. 7 videos7 readings1 assignment1 programming assignment In this module, we discuss Dynamic Arrays: a way of using arrays when it is unknown ahead-of-time how many elements will be needed. Here, we also discuss amortized analysis: a method of determining the amortized cost of an operation over a sequence of operations. Amortized analysis is very often used to analyse performance of algorithms when the straightforward analysis produces unsatisfactory results, but amortized analysis helps to show that the algorithm is actually efficient. It is used both for Dynamic Arrays analysis and will also be used in the end of this course to analyze Splay trees. 5 videos1 reading1 assignment We start this module by considering priority queues which are used to efficiently schedule jobs, either in the context of a computer operating system or in real life, to sort huge files, which is the most important building block for any Big Data processing algorithm, and to efficiently compute shortest paths in graphs, which is a topic we will cover in our next course. For this reason, priority queues have built-in implementations in many programming languages, including C++, Java, and Python. We will see that these implementations are based on a beautiful idea of storing a complete binary tree in an array that allows to implement all priority queue methods in just few lines of code. We will then switch to disjoint sets data structure that is used, for example, in dynamic graph connectivity and image processing. We will see again how simple and natural ideas lead to an implementation that is both easy to code and very efficient. By completing this module, you will be able to implement both these data structures efficiently from scratch. 15 videos6 readings3 assignments1 programming assignment1 plugin In this module you will learn about very powerful and widely used technique called hashing. Its applications include implementation of programming languages, file systems, pattern search, distributed key-value storage and many more. You will learn how to implement data structures to store and modify sets of objects and mappings from one type of objects to another one. You will see that naive implementations either consume huge amount of memory or are slow, and then you will learn to implement hash tables that use linear memory and work in O(1) on average! In the end, you will learn how hash functions are used in modern disrtibuted systems and how they are used to optimize storage of services like Dropbox, Google Drive and Yandex Disk! 20 videos4 readings2 assignments1 programming assignment In this module we study binary search trees, which are a data structure for doing searches on dynamically changing ordered sets. You will learn about many of the difficulties in accomplishing this task and the ways in which we can overcome them. In order to do this you will need to learn the basic structure of binary search trees, how to insert and delete without destroying this structure, and how to ensure that the tree remains balanced. 7 videos2 readings1 assignment In this module we continue studying binary search trees. We study a few non-trivial applications. We then study the new kind of balanced search trees - Splay Trees. They adapt to the queries dynamically and are optimal in many ways. 4 videos2 readings1 assignment1 programming assignment

6 modules

Intermediate level

https://www.coursera.org/learn/data-structures

93%

AI Ethics, Responsible Use, and Creativity

Enrollment number not found

Rating not found

Garrett Schumann

University of Michigan

['Leadership', 'Analysis', 'AI Ethics']

“AI Ethics, Responsible Use, & Creativity” explores ethics and responsible use of generative AI tools for creative work. After completing this course, you will learn how to engage with generative AI tools with an eye toward intentionality, sustainability, and responsibility. You will learn the SIFT (Specify, Identify, Focus, Trust) process for evaluating AI tools. This compact method helps learners employ AI successfully and sustainably by realistically approaching the technology and prioritizing intentional decision-making for individuals and enterprises. You will learn the practical application of the SIFT framework by using it to evaluate tools and creative work developed in the first course. You will also learn about the reputational and legal risks of using AI in creative fields. You will explore issues of environmental cost, cultural bias, and data risks of contemporary GenAI tools through readings and a guest lecture by expert Justin Joque. This is the second course in “AI for Creative Work,” a series exploring how artificial intelligence can enhance the work of creatives. 1 video2 readings1 discussion prompt 3 videos1 reading3 app items1 plugin 5 videos1 app item 1 video4 readings1 app item 2 videos2 readings1 assignment 5 videos1 reading

6 modules

Beginner level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/ai-ethics-responsible-use-and-creativity

English Intermediate B1.2

15,472

4.7

Ruth Kerr

Università di Napoli Federico II

['English Language', 'Business English', 'Written English']

Welcome to the second and final course in our B1 program! English is the most important international language for the workplace and for study, and this second course will help you improve your language skills even further to reach the convincing intermediate level you need to work, study or travel abroad. The varied learning activities will enable you to communicate on a variety of more complex topics like the digital university, the climate and the environment, and looking after your health. This module teaches you how to talk about domestic animals, how to look after an animal successfully and give relevant advice about which pet to choose. 3 videos3 readings8 assignments1 discussion prompt The language content this week prepares you to ask and answer questions about your learning experience, especially about language learning. By the end of the week you should be able to carry out tasks related to distance learning, everyday life at university and Erasmus projects. 4 videos4 readings9 assignments1 discussion prompt This week focuses on the world of work, and you will look at the lexis to describe jobs and professions, key elements of job descriptions, as well as personal skills and competencies required for specific jobs. There will also be an opportunity to study the sections and components of a CV and how best to prepare an effective CV in English. 3 videos6 readings10 assignments1 discussion prompt In this module you will have the opportunity to learn the language you need to describe an illness or injury, how to ask for help and how to recount what happened. 3 videos4 readings9 assignments2 discussion prompts By the end of this module, you should be able to describe and talk about the weather in different contexts and seasons. You should also be able to understand basic information about climate change and explain what you do to protect the planet. 3 videos10 readings7 assignments2 discussion prompts In this last week of the course you will learn the lexis and phrases to describe the common causes and symptoms of stress. You will also explore, evaluate and apply different ways of dealing with mental health issues like stress. The grammar focus is on reported, or indirect, speech. 1 video8 readings7 assignments2 discussion prompts

6 modules

Intermediate level

https://www.coursera.org/learn/english-intermediate-b1-2

94%

Cyber Security – Technology and Governance Specialization

1,931

4.8

Guido Schmitz

University of London

['Computer Security Incident Management', 'Cybersecurity', 'Cyberattacks', 'Information Security (INFOSEC)']

This specialisation covers topics ranging from the security of computer system and networks, to the key role of human aspects in cybercrime. You will learn fundamental concepts related to computer system core components and how computers work, then extend this to consider a variety of topics from hardware to applications. Aspects of cybercriminal activity are explained in topics such as social engineering, arguably the most important attack vector in cybercrime, and the range of actors related to cybercrime: the criminals, the victims, and law enforcement. Finally, you will be presented with some of the key components of practical cyber security management and its governance. This includes what happens when things go wrong, understanding how organisations can respond to incidents, through to the essential role of people in achieving better cyber security outcomes. The purpose of this short four-week course is to introduce the topic of computer system security. We initially look at a short basic introduction to computer system core components and functions and then extend this to consider a variety of topics from hardware to applications. Throughout we provide pointers to openly available materials for background and further reading to explore the topics. We refer to the Cyber Security Body of Knowledge (CyBOK) as a reference for cyber security knowledge, alongside other sources that are widely available. In total, we have four weeks that cover this introduction to computer systems and security. No prior programming nor advanced mathematical knowledge Is required. There are a few examples of pseudocode and some basic computer logic (AND, OR, XOR, etc.) in our Week 1 Introduction to computer systems, but these are not essential to completing the course. In other lessons, we introduce basic concepts and provide pointers to online resources. The course includes active learning through four lab sessions. The first lab introduces the Linux operating system in general by exploring the Linux desktop and applications provided in the Coursera lab environment hosted in the AWS cloud. The second lab looks at the Linux command line and explores some of the file system and gathers system information, for example to explore processes. The third lab explores the network information, the system connectivity, and uses some Python scripts and Wireshark to examine the TCP and UDP transport protocols and the web/HTTP application protocol. Lastly we explore more about the network services using the Nmap tool to explore the network services in the system. The course is designed to provide a wide introduction to computer security, by outlining computer systems, including the operating system, programs, data and networking. We discuss some of the issues in computer security and introduce some of the vulnerabilities and threats as we progress through the four weeks. We include some optional readings and videos from a number of sources, including professional resources and vendor materials for additional study. The security of computer networks is a key element in cyber security. Computer networking provides the foundational connectivity services that are used for the world wide web, distributed computer applications and services, operations and manufacturing, and national infrastructure. This course provides understanding of key technologies used in computer networks and infrastructure. This includes protocols, computer networks, data centres, operational technologies that form key infrastructure critical to the success of organisations and services from a local to an international scale. The course discusses vulnerabilities and the exploits that target computer networks, systems, and the Internet infrastructure. By the end of this course learners will be able to: 1. Show a systematic understanding of digital networks and their operation, including the OSI 7 layer architecture and the TCP/IP protocol stack. 2. Discuss key security threats and risks faced in computer networks. 3. Demonstrate a critical understanding of network security architecture and design rationale of selected protocols, security technologies and how they are used in practice. 4. Identify attack models and analyse vulnerabilities in protocols, network systems, and applications. 5. Demonstrate how these vulnerabilities may be exploited in practice to penetrate a system. In this course you will look at some of the key components of practical cyber security management and its governance. This includes what happens when things go wrong, understanding how organisations can respond to incidents, through to the essential role of people in achieving better cyber security outcomes. Together, you will examine how incident management, cyber resilience, and developing an effective appreciation of people, not simply as users but as active participants, can enable better cyber security outcomes. The topics covered include: • Identifying what an incident is • Incident preparation, planning, and response • Cyber resilience • The role of people in security management • The building of trust and developing positive cyber security cultures By completing this course, you will learn how to integrate incident management and a rich knowledge of people into a real-world Information Security Management System for an organisation. This course introduces fundamental notions of cybercrime. Namely, what cybercrime is, the main questions surrounding cybercrime, how cybercrime can be defined, and how it can be studied. You will learn about the difficulties in measuring the occurrence, the frequency and the impact of cybercrime, and build a scepticism on the reliability and the interpretation of cybercrime reports. You will be introduced to discussion about human aspects of cybercrime, in particular, the actors related to cybercrime, that is, the criminals, the victims, and law enforcement. You will also learn about aspects such as personality, national and organisational culture, security culture, training, and other components which affect cybercriminal activity. Finally, you will dive into what is arguably the most important attack vector in cybercrime, that is, social engineering. You will gain an understanding of how it occurs, which techniques social engineers utilise, and which are the underlying psychological principles which make all of us – as humans – susceptible to social engineering attacks. By the end of the course you should be able to: • Reflect on the main questions related to cybercrime. • Explain the meaning, definitions, importance, and impact of cybercrime. • Assess the reliability and the interpretation of reports and surveys related to cybercrime. • Identify the various classifications of cybercrime, the related threats, and threat actors. • Explain the key role of human aspects in cybercrime. • Differentiate between the various actors involved in cybercrime and their associated perspectives. • Evaluate the underlying psychological principles which make social engineering the most successful attack vector in cybercrime. • Describe how deception and social engineering manifest and how they can be defended against.

4 course series

Beginner level

4 months (at 5 hours a week)

https://www.coursera.org/specializations/cyber-security-technology-governance

Exam Prep AI-102: Microsoft Azure AI Engineer Associate

3,735

3.5

Whizlabs Instructor

Whizlabs

['NLP Solutions', 'Python Programming', 'Conversational AI Solutions', 'Azure Cognitive Services', 'Azure AI solutions: Planning and Management']

The AI-102: Designing and Implementing a Microsoft Azure AI Solution certification exam tests the candidate’s experience and knowledge of the AI solutions that make the most of Azure Cognitive Services and Azure services. In addition, the exam also tests the candidate's ability to implement this knowledge by participating in all phases of AI solutions development—from defining requirements, and design to development, deployment, integration, maintenance, performance tuning, and monitoring. Take this Designing and Implementing a Microsoft Azure AI Solution: AI-102 exam and become a part of the futuristic world of Artificial Intelligence and grow your career by attaining Azure AI-102 certification. Azure AI engineers have experience developing solutions that use languages such as Python or C# and should be able to use REST-based APIs and software development kits (SDKs) to build secure image processing, video processing, natural language processing (NLP), knowledge mining, and conversational AI solutions on Azure. They should be familiar with all methods of implementing AI solutions. Plus, they understand the components that make up the Azure AI portfolio and the available data storage options. Azure AI engineers also need to understand and be able to apply responsible AI principles. This course contains 5+ hours of training videos. Learners could find a total of 90+ lectures in the training course with comprehensive coverage of all topics regarding the exam AI-102: Designing and Implementing a Microsoft Azure AI Solution. These lectures are divided into 5 Modules and each module is further split into lessons. The entire course includes Assessments to validate knowledge checks of learners. Also, a set of Graded Questions is available at the end of every module. Module 1: Azure AI Solutions: Planning and Management Module 2: Image & Video Processing Solutions Module 3: Natural Language Processing (NLP) Solutions Module 4: Knowledge Mining Solutions Module 5: Conversational AI Solutions Enroll in Exam Prep AI-102: Microsoft Azure AI Engineer Associate Course and advance your Azure AI Solution Workload skills with Microsoft Azure. This training course helps you develop your skills and knowledge in AI-102. You can start with fundamental certifications such as the AI-900 exam. Once you gain command over all phases of AI solutions development, you are ready to start preparing for the AI-102 exam. This AI-102 course is mainly for those who need opportunities in various job roles such as Cloud Developers, Cloud Engineers, Solutions Architects, and Cloud Architects. By the end of this course, you will be able to pass the AI-102 exam on the first attempt and master Designing and Implementing a Microsoft Azure AI Solution. Welcome to Week 1 of the Course. This week, we’ll explore the Concepts of Course Overview, Prerequisites, and Azure AI Solutions Introduction. We will also explore the concepts of Azure AI services with security-based selection. By the end of the course, we'll learn how to configure and manage the logging and cost of Azure AI Services and explore the concepts of Monitoring Azure AI Services. 27 videos3 readings4 assignments1 discussion prompt Welcome to Week 2 of the Course. This week, we’ll explore the concepts of Image processing requirements, responses, and features. We learn the concepts of extracting text with Computer Vision Models. By the end of this course, we will be able to configure Image classification and object detection and concepts of Azure AI Vision with OCR and AI. 21 videos1 reading3 assignments Welcome to Week 3 of the Course. This week, we’ll explore the concepts of Analyzing text using Azure AI Language and configuring the Process speech using Azure AI Speech. We will learn the concepts of the Translate language with Translator Services. By the end of this course, we will be able to Explore how to Implement and manage a language understanding model by using Azure AI Language and Analyze the concepts of question answering solutions by using Azure AI Language. 37 videos1 reading4 assignments Welcome to Week 4 of the Course. This week, we’ll explore the concepts of Implementing Azure AI Search Solutions. Then we learn how to Explore the concepts of Document Intelligence. By the end of this course, we will learn to demonstrate the concepts of Azure AI Document Intelligence with pre-built Models and Explore the concepts of how to implement Build an Azure AI Document Intelligence custom skill for Azure AI Search. 7 videos1 reading2 assignments Welcome to the Week 5 (Final Week) of the Course. This week, we’ll explore the concepts of Generative AI, Azure Open AI, and Content Safety Services. Then we will learn how to analyze the concepts of Azure OpenAI Service to generate content. By the end of this course, we will be able to learn how to Analyze the concepts of how to Implement and Optimize Generative AI, and how to create and implement solutions for content delivery. 15 videos2 readings4 assignments

5 modules

Intermediate level

17 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/ai-102-microsoft-azure-ai-engineer-associate-course

Engineering Practices for Building Quality Software

37,235

4.5

Kevin Wendt

University of Minnesota

['Software Testing', 'Software Architecture', 'Application Security', 'Software Design', 'Software Quality']

Agile embraces change which means that team should be able to effectively make changes to the system as team learns about users and market. To be good at effectively making changes to the system, teams need to have engineering rigor and excellence else embracing change becomes very painful and expensive. In this course, you will learn about engineering practices and processes that agile and traditional teams use to make sure the team is prepared for change. In additional, you will also learn about practices, techniques and processes that can help team build high quality software. You will also learn how to calculate a variety of quantitative metrics related to software quality. This is an intermediate course, intended for learners with a background in software development. To succeed in the course, you should have experience developing in modern programming languages (e.g., Java, C#, Python, JavaScript), an understanding of software development lifecycle models, familiarity with UML diagrams (class and sequence diagrams), and a desire to better understand quality aspects of software development beyond program correctness. At the end of this course, you will be able to comfortably and effectively participate in various techniques and processes for building secure and high quality software. In this module, you will be introduced to the concept of quality as it relates to software. 1 video1 reading In this module, you will learn about a variety of quality metrics including how to calculate them. A discussion of design patterns follows, allowing you to gain a deeper understanding of the quality they provide and exposure to several important patterns. 7 videos11 readings1 assignment2 discussion prompts In this module, you will create Scenarios in order to document and verify quality attributes relevant to software architecture, including usability, performance, and more. Then, you will examine one specific quality attribute and its implications: security. 7 videos1 reading1 peer review In this module, you will explore a variety of quality aspects of the implementation stage of the lifecycle. You will also evaluate coding style guides and static analysis tools. Finally, you will analyze self-documentation in open-source code and identify the capabilities of version control and automated build tools. 7 videos8 readings1 assignment3 peer reviews2 discussion prompts In this module, learners will discover quality in the final lifecycle stages: testing and deployment. Learners will first be instructed on the importance of test planning, understand what it means to evaluate tests and identify the benefits of test-first process. Then, a variety of resources will give learners understanding into continuous pipeline tools, allowing the learner to evaluate their potential benefits (and drawbacks) for their own projects. 5 videos15 readings1 assignment

5 modules

Intermediate level

https://www.coursera.org/learn/engineering-practices-secure-software-quality

90%

Governmental Accounting and Reporting I

Enrollment number not found

Rating not found

Jenny Ulla

University of Illinois Urbana-Champaign

['Accounting', 'Governmental Accounting', 'Financial Statement', 'nonprofit accounting']

This course includes -8 graded quizzes, required for completion, and -86 optional practice quizzes for you to check your understanding of key concepts. Building on the fundamentals, these modules dive into specific aspects of governmental and nonprofit accounting. You'll learn about constructing the required financial statements, including the statements for the government-wide as well as fund financial statements. You’ll also learn in great detail the difference between the three categories of funds: Governmental Funds, Proprietary Funds, and Fiduciary Funds. These modules provide in-depth knowledge of accounting practices and financial reporting for government and nonprofit entities. Government and nonprofit accounting involve specialized reporting practices driven by their unique characteristics and intended purposes. Reporting standards set by authoritative bodies like GASB and FASB ensure transparency and accountability to meet the needs of diverse stakeholders, while fund accounting helps entities manage resources effectively and report financial information accurately. 13 videos6 readings10 quizzes1 discussion prompt1 plugin Accurate and transparent financial reporting is the aim of governmental reporting. It ensures that financial information is presented in a way that meets the needs of various stakeholders while adhering to specific accounting standards and principles. In this module, we will begin to look at the foundational construction of government financial statements. 10 videos2 readings9 quizzes In governmental accounting, the Statement of Net Position within Government-Wide Financial Statements serves as a critical snapshot of a government entity's financial health, categorized into Net Investment in Capital Assets, Restricted, and Unrestricted. Operating Revenues and Expenses in Government-Wide Statements of Activities delineate the revenues and expenses associated with core governmental activities, distinguishing between program and general revenue sources. Governmental Fund Financial Statements follow modified accrual accounting, comprising essential funds and featuring financial statements like the Balance Sheet, Statement of Revenues, Expenditures, and Changes in Fund Balances, and the Statement of Cash Flows. Transfers and Internal Balances facilitate resource allocation among funds, while Fund Balance classifies resources as Nonspendable, Restricted, Committed, Assigned, or Unassigned. Additionally, Revenues and Other Financing Sources, Expenditures, and Other Financing Uses clarify financial inflows and outflows in governmental funds, contributing to transparent financial management within government entities. 13 videos2 readings13 quizzes1 assignment In this module, we will get an overview of what the General Fund is and how to account for transactions under the General Fund. We will examine and analyze the General Fund's operating budget and transactions, preparing and analyzing journal entries for budgetary reporting and preparing fund-level journal entries. We will also account for transactions under the modified accrual basis of accounting for state and local governments, handling encumbrances within and from prior fiscal years and analyzing and recording operating transactions for governmental activities at both government-wide and fund levels. 11 videos2 readings11 quizzes We will prepare required General Fund financial statements. They include the preparation of year-end General Fund financial statements, budget creation, and calculating ending fund balances. We will also learn how to account for property taxes under modified accrual basis. We will also learn about the key characteristics for the special revenue and permanent funds, with a focus on accurately accounting for their transactions and journal entries. Additionally, we will differentiate how to handle three grant types: purpose-restricted, time-restricted, and eligibility-restricted. Lastly, we’ll discuss how to account for transactions that take place internally versus externally and transactions that are reciprocal or nonreciprocal. 15 videos2 readings15 quizzes In this module we will learn about our next two governmental funds: capital projects fund and the debt service fund. We will focus on how governmental entities account for General Capital Assets and General Long-Term Liabilities on the fund-level and the government-wide level. Additionally, we will prepare financial statements for the capital projects fund and the debt service fund. We will get into detail about characteristics of a serial and term bond. Additionally, we will explore new disclosures in the financial statements and define new terms such as debt margin and debt limit. 13 videos2 readings12 quizzes1 assignment We will introduce proprietary funds and their key characteristics. We will learn about how these two funds are reported on both the fund level and the Government-wide level. In this section, we will also cover the three net position classification and get practice on categorizing transactions into these three classifications of net position. Lastly, we will account for transactions for both proprietary funds and create financial statements. 13 videos2 readings11 quizzes3 assignments In this module, we will focus on the Statement of Cash Flow for proprietary funds. We will first differentiate between FASB and GASB Statement of Cash Flow requirements. Next, in order to understand how governmental entities account for cash flow transactions, we will classify what activities and transactions are inflows and outflows on the Statement of Cash Flow and we will prepare a Statement of Cash Flow. In addition to this, we will create a required piece of GASB’s Statement of Cash Flow, which is the Reconciliation of Operating Income to Net Cash Provided by Operating Activities for a Statement of Cash Flow. 8 videos4 readings7 quizzes1 assignment1 plugin

8 modules

Intermediate level

28 hours to complete (3 weeks at 9 hours a week)

https://www.coursera.org/learn/governmental-accounting-and-reporting-1

Microsoft Front-End Developer Professional Certificate

Enrollment number not found

Rating not found

Microsoft

Microsoft

['Web Application Security', 'HTML', 'Front-End Development', 'JavaScript', 'C# Fundamentals', 'Blazor', 'CSS', 'Web Application Security', 'HTML', 'Front-End Development', 'JavaScript', 'C# Fundamentals', 'Blazor', 'CSS']

Are you ready to start a rewarding career in front-end development? This Professional Certificate Program, brought to you by Microsoft, is designed to give you the skills and tools to succeed in web development. Whether you're just starting out or looking to expand your knowledge, this program will guide you through essential front-end concepts and practices. You'll learn core web technologies like HTML, CSS, and JavaScript, along with advanced topics such as responsive design, web accessibility, and version control using Git and GitHub. Gain hands-on experience with industry-standard tools like Visual Studio Code and Microsoft Copilot, leveraging AI to streamline your coding, debugging, and project management tasks. Generative AI helps you write cleaner code, automatically generates suggestions, and even debugs your applications in real time. You'll also explore C# programming, a versatile language for building dynamic applications. This will enable you to integrate front-end skills with server-side development, opening up opportunities to create more complex, scalable systems. Beyond coding, the program emphasizes UI/UX design, Blazor for interactive web applications, and key security practices to protect against vulnerabilities. By the end, you’ll confidently build responsive, secure web applications with AI-driven tools. Enroll today and lead the next wave of front-end development! Applied Learning Project Throughout the program, you’ll get to practice your new front-end development skills through hands-on projects, including: Develop a code project with key components, including if/else statements, loops, conditionals, functions, and variables. Write, debug, and improve code using Microsoft Copilot. Apply Microsoft Copilot to develop a small web project using HTML, CSS, and JavaScript. Complete a comprehensive Blazor project utilizing Microsoft Copilot for writing, debugging, and optimizing code. Use Microsoft Copilot to write and enhance CSS, generate responsive design suggestions, and improve UI/UX design in practical workflows. Use Microsoft Copilot to manage and optimize a complex database system. By the end, you’ll have a professional portfolio that you can show to prospective employers. This course focuses on the fundamental concepts of front-end development. You'll learn to solve problems, design algorithms, and write efficient, modular code using industry-standard practices. By the end of this course, you will be able to… Summarize the foundational principles and practices of front-end development. Plan front-end projects using industry-standard tools and methodologies. Apply logical thinking and problem-solving techniques in programming. Design algorithms and flowcharts to represent logical steps in programming. Implement control structures and loops for repetitive tasks. Develop modular code using functions and methods. This course introduces the fundamentals of programming in C# within the .NET framework. You'll gain hands-on experience setting up projects, mastering core programming concepts, and using object-oriented principles to create scalable applications while utilizing Microsoft Copilot to enhance code quality and productivity. By the end of the course, you will be able to… Describe the setup, structure, and configuration of .NET projects in a Visual Studio Code environment by the end of the course. Implement fundamental programming concepts in C#, including variables, control structures, loops, and methods, to solve basic problems and create simple applications within a .NET environment. Apply object-oriented programming principles, such as classes, inheritance, and polymorphism, to design and implement modular and scalable C# applications. Develop asynchronous programs using C# and apply debugging techniques to ensure performance and responsiveness in modern applications. Leverage Microsoft Copilot to write, debug, and optimize C# code, improving code quality and efficiency throughout the course. This course covers the essential building blocks of web development, including HTML, CSS, and JavaScript. You'll learn responsive design, web accessibility, and how to use Git and Microsoft Copilot to collaborate and build small web projects efficiently. By the end of this program, you will be able to… Define the basic structure and elements of HTML, syntax of CSS and JavaScript, and concepts of version control. Explain the principles of responsive design, web accessibility, DOM manipulation, asynchronous JavaScript, and integration of Git with development tools. Describe advanced CSS techniques, functions, and scope in JavaScript, collaborative development with GitHub, and the features of Microsoft Copilot. Apply HTML, CSS, and JavaScript skills with Microsoft Copilot for a small web project. This course focuses on UI/UX design principles and their application in Blazor Pages. You'll learn to create responsive, user-centered designs, leveraging Microsoft Copilot to enhance CSS, generate design suggestions, and improve workflows. By the end of this program, you will be able to… Define the basic concepts and features of Blazor, Blazor components, data binding, and rendering models. Describe the steps to create and configure Blazor projects, parent-child component communication, routing and navigation techniques, and advanced component techniques. Explain how to run and debug Blazor applications, lifecycle methods, event handling, state management, and hybrid rendering approaches. Develop a Blazor project with Microsoft Copilot, including writing, debugging, and optimizing Blazor code. This course introduces key UI/UX design concepts and tools. You'll learn to create user-centered, responsive designs, using wireframing, prototyping, and Microsoft Copilot to enhance CSS and improve workflows. By the end of this program, you will be able to… Define the basic concepts of UI/UX design, design tools, and responsive design. Explain fundamental design principles, wireframing, prototyping, and responsive design testing techniques. Describe user-centered design, accessibility considerations, high-fidelity mockups, and mobile-first design principles. Use Microsoft Copilot to write and enhance CSS, generate responsive design suggestions, and improve UI/UX design in practical workflows. This course covers essential web security concepts and secure coding practices. You’ll learn to identify common vulnerabilities, implement protection techniques, and leverage Microsoft Copilot to detect and fix security issues in web applications. By the end of this program, you will be able to… Define common web application vulnerabilities and principles of secure coding. Explain the concepts and impacts of SQL injection, XSS, CSRF, input validation techniques, and best practices for authentication and authorization. Describe the importance of output encoding, sanitization, secure data storage, and transmission. Enhance the security of web applications with Microsoft Copilot to detect vulnerabilities, fix issues, and implement secure coding practices.

6 course series

Beginner level

4 months (at 10 hours a week)

https://www.coursera.org/professional-certificates/microsoft-front-end-developer

Data Visualization and Dashboards with Excel and Cognos

157,095

4.7

Sandip Saha Joy

IBM

['Data Analysis', 'Microsoft Excel', 'IBM Cognos Analytics', 'Dashboard', 'Data Visualization']

Learn how to create data visualizations and dashboards using spreadsheets and analytics tools. This course covers some of the first steps for telling a compelling story with your data using various types of charts and graphs. You'll learn the basics of visualizing data with Excel and IBM Cognos Analytics without having to write any code. You'll start by creating simple charts in Excel such as line, pie and bar charts. You will then create more advanced visualizations with Treemaps, Scatter Charts, Histograms, Filled Map Charts, and Sparklines. Next you’ll also work with the Excel PivotChart feature as well as assemble several visualizations in an Excel dashboard. This course also teaches you how to use business intelligence (BI) tools like Cognos Analytics to create interactive dashboards. By the end of the course you will have an appreciation for the key role that data visualizations play in communicating your data analysis findings, and the ability to effectively create them. Throughout this course there will be numerous hands-on labs to help you develop practical experience for working with Excel and Cognos. There is also a final project in which you’ll create a set of data visualizations and an interactive dashboard to add to your portfolio, which you can share with peers, professional communities or prospective employers. In this module, you will be introduced to the basics of charts and the Excel functions that are used to create basic charts and pivot chart visualizations. By learning how to manipulate these features and creating visualizations, you will begin to understand the important role charts play in telling a data-driven story. 6 videos4 readings1 quiz1 assignment2 plugins In this module, you will learn about creating advanced charts and visualizations and learn about the basics of dashboarding and how to create a simple dashboard using a spreadsheet. 5 videos2 readings1 quiz3 assignments2 plugins In this module, you will be introduced to another dashboarding solution called Cognos Analytics. After registering with Cognos Analytics, you will then explore the platform capabilities by creating visualizations, building a simple dashboard, and discovering its advanced features. Optionally, you can explore Google Looker Studio to create visualizations and build dashboards. 4 videos6 readings4 assignments6 plugins Congratulations! You have now completed the modules for this course. In this module, you will complete the final assignment that will be graded by your peers. In the first part of the final assignment, you will use provided sample data to create some visualizations using Excel for the web. In the second part of the final assignment, you will create some visualizations and add them to a dashboard using Cognos Analytics or Google Looker Studio. 2 readings1 peer review4 plugins

4 modules

Beginner level

https://www.coursera.org/learn/data-visualization-dashboards-excel-cognos

94%

ML Algorithms

Enrollment number not found

Rating not found

Whizlabs Instructor

Whizlabs

['Data Model', 'Machine Learning (ML) Algorithms', 'Machine Learning', 'Amazon Web Services (Amazon AWS)']

ML Algorithms is the fourth Course in the AWS Certified Machine Learning Specialty specialization. This Course enables learners to deep dive Machine Learning Algorithms. This course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:00-2:30 Hours Video lectures that provide both Theory and Hands -On knowledge. Also, Graded and Ungraded Quiz are provided with every module in order to test the ability of learners. Module 1: ML Algorithms- Part 1 Module 2: ML Algorithms- Part 2 Minimum two year of hands-on experience in architecting, building or running ML/deep learning workloads on the AWS Cloud. By the end of this course, learners will be able to : - Determine algorithm concepts in ML - Design Regression algorithms and Classification based algorithms - Examine Reinforcement learning algorithms and Forecasting algorithms Welcome to week 1 ofML Algorithms Course. This week, we'll describe algorithm concepts in Machine Learning. We'll demonstrate working of Regression algorithms ad Clustering algorithms. Additonally, we'll also demonstrate working of Classification based algorithms 12 videos3 readings2 assignments1 discussion prompt Welcome to Week 2 of ML Algorithm course. This week, we'll describe Image analysis algirithms with demonstration on Text analysis algorithms. By the end of this week, we'll be able to describe Reinforcement learning algorithms and Forecasting algorithms. 7 videos3 readings3 assignments

2 modules

Beginner level

4 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/ml-algorithms

Alteryx Advanced

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['Alteryx', 'Alteryx Certification', 'Intelligence Suite', 'Regular Expression (REGEX)', 'Machine Learning', 'RegEx']

Dive into advanced data analytics with our Alteryx course: - Begin by mastering data cleansing, handling multiple files, sampling, and regex for parsing XML. - Enhance your skills with in-database processing, blending, and selecting data efficiently. - Advance to app and macro customization, creating batch macros, and handling errors with conditional logic. - Learn Alteryx's machine learning capabilities, from building models to deploying them for fraud detection and customer segmentation. Designed for data professionals with basic Alteryx knowledge, the course offers hands-on exercises and real-world examples. The end goal is to transform complex data challenges into actionable insights, enabling you to drive informed business decisions. In this module, we will explore the foundational skills necessary for effective data cleansing and manipulation in Alteryx. You'll start with an introduction to the course and Alteryx's features, move through handling multiple files and sampling techniques, and learn advanced grouping, cleaning, and parsing methods. This section sets the stage for building robust data workflows. 8 videos1 reading1 assignment In this module, we will delve into the power of in-database processing with Alteryx. You'll learn to perform complex data operations directly within your database environment, enhancing efficiency and scalability. Topics include in-database blending and using select and summarize tools to streamline your data workflows. 3 videos1 assignment In this module, we will elevate your skills in creating and optimizing apps and macros within Alteryx. You'll gain insights into advanced techniques, batch processing, error handling, and customization. By the end, you'll be able to design sophisticated, efficient workflows and share them with others. 5 videos1 assignment In this module, we will journey through the comprehensive landscape of machine learning using Alteryx's Intelligence Suite. From foundational concepts to advanced techniques, you'll learn to build, train, deploy, and operationalize machine learning models, tackling real-world business problems with cutting-edge analytics. 5 videos1 assignment In this module, we will put your knowledge to the test with hands-on exercises designed to consolidate your learning. You'll tackle real-world datasets, apply advanced Alteryx tools, and solve complex data problems. The course concludes with a final thank-you note and a recap of your journey through advanced data analytics with Alteryx. 6 videos1 assignment

5 modules

Intermediate level

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/packt-alteryx-advanced-8ynsl

Introduction to Socially Engaged Design

Enrollment number not found

Rating not found

Shanna Daly

University of Michigan

['Equity Analysis', 'Human-Centered Design', 'Product Design', 'Design Model Comprehension', 'Ideation']

Engineering courses often focus on technical skills and processes, leaving students with few examples of how to apply these skills in the real world. With "Introduction to Socially Engaged Design," you'll learn about this essential engineering and design framework, strengthening the connection between your work and its impact on individuals, societies, and the environment. Developed by expert faculty at the University of Michigan, the Socially Engaged Design model shows engineers and designers to explore the broader societal implications, outcomes, and potential unintended consequences early in the product design process. You'll learn to explore, develop, and iterate on your solutions to make equitable, evidence-based decisions. You will better understand how your experiences shape your work and explore how power, privilege, identities, and cultural contexts can shape your approach and impact. The course draws heavily on real-world examples of product design solutions that enhanced and deterred the progress of individuals and communities. In addition to these concepts, you'll learn how to effectively work with stakeholders to bring a design solution to life. By understanding design solutions' economic, social, and environmental impacts, you can develop better product and engineering design solutions for current and future generations. In this module you will explore the intersection of technical design, engineering, and social factors, focusing on equity and societal needs. You will examine the Socially Engaged Design (SED) Process to navigate complex engineering challenges, learn its structure, and apply the SED principles through case studies showcasing the societal impact of engineering. 6 videos7 readings3 assignments5 discussion prompts In this module you will understand how to employ stakeholder maps to identify project influences and discover the impact of power dynamics and personal bias on stakeholder interactions. 6 videos12 readings6 assignments4 discussion prompts In this module you will learn the process of identifying and defining engineering needs and design opportunities, and understand how to distinguish between and gather stakeholder requirements and engineering specifications. In addition you will examine how personal biases can affect problem framing. 6 videos9 readings5 assignments4 discussion prompts In this module you will understand the role of tools and strategies in ideation to create innovative design solutions. You'll survey best practices in generating and selecting ideas, while examining how identity and power dynamics influence the ideation process. 5 videos6 readings2 assignments4 discussion prompts In this final module you will dig into the Develop and Realize stages as critical analysis processes for validating and verifying design concepts. This module defines prototyping as an iterative tool, focuses on stakeholder engagement in development, discusses varied validation strategies, and addresses the influence of personal and societal factors on idea evolution. 7 videos10 readings5 assignments2 discussion prompts

5 modules

Beginner level

29 hours to complete (3 weeks at 9 hours a week)

https://www.coursera.org/learn/socially-engaged-design

Predictive Modeling and Machine Learning with MATLAB

15,721

4.8

Michael Reardon

MathWorks

['Machine Learning', 'Matlab', 'Predictive Modelling']

In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation) and have completed courses 1 through 2 of this specialization. By the end of this course, you will use MATLAB to identify the best machine learning model for obtaining answers from your data. You will prepare your data, train a predictive model, evaluate and improve your model, and understand how to get the most out of your models. In this module you'll apply the skills gained from the first two courses in the specialization on a new dataset. You'll be introduced to the Supervised Machine Learning Workflow and learn key terms. You'll end the module by creating and evaluating regression machine learning models. 11 videos8 readings3 assignments4 app items1 discussion prompt In this module you'll learn the basics of classification models. You'll train several types of classification models and evaluation the results. 6 videos7 readings2 assignments1 discussion prompt In this module you'll apply the complete supervised machine learning workflow. You'll use validation data inform model creation. You'll apply different feature selection techniques to reduce model complexity. You'll create ensemble models and optimize hyperparameters. At the end of the module, you'll apply these concepts to a final project. 10 videos5 readings4 assignments1 discussion prompt 5 videos7 readings2 assignments1 discussion prompt

4 modules

Beginner level

18 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/predictive-modeling-machine-learning

Blockchain Revolution Specialization

39,137

4.7

Don Tapscott

INSEAD

[]

Blockchain is poised to transform every industry and managerial function—redefining the ways we transact online, share ideas, and manage workflows. It’s a new technology that every business professional needs to understand. This four-course Specialization introduces you to the world of blockchain technology—explaining what blockchain is, how it works, and why it’s revolutionary. You will learn about various categories of cryptoassets, and the ways they can be transacted on a blockchain. You will learn how blockchain is disrupting business models and financial services, offering organizations new choices in how they create and manage value. The Specialization is taught by Don Tapscott and Alex Tapscott, globally-recognized authorities on innovation and technology and authors of the best-selling book Blockchain Revolution. It also includes various industry experts and developers from the Ethereum Foundation, Grid Singularity, Keyless Technologies, and ResonanceX who will share their experiences within the blockchain ecosystem. Additionally, you will gain access to ground-breaking research from theBlockchain Research InstituteOpens in a new tabas well as theBlockchain Case Commons—a crowdsourced collection of blockchain applications and use-cases spanning multiple industries. Upon completion of this Specialization, you will produce a Blockchain Opportunity Analysis, in which you identify and evaluate a promising application of blockchain technology in your own industry. Applied Learning Project Upon completion of this Specialization, learners will produce aBlockchain Opportunity Analysis, in which you identify and evaluate a promising application of blockchain technology within your chosen industry. The goals of this project are twofold: One, it’s for you to identify a specific need or problem within an industry that can potentially be solved using blockchain technology. Two, it’s for you to investigate possible solutions to this problem, including how these solutions might be executed. You will accomplish different project milestones each week, and will be introduced to several tools to organize your findings. As an outcome of this project, you’ll walk away with a consolidated, peer-reviewedBlockchain Opportunity Analysis, which you can use to pitch your idea to your organization or even to potential investors. The limitations of the Internet for business and economic activity, and how trust is established in a pre- and post-blockchain world Terms such as miner, hash, nonce, proof-of-work, and public key cryptography, as well as the steps of a blockchain transaction Seven design principles for blockchain technology Ten challenges associated with implementing blockchain technology Describe seven types of cryptoassets, and explain what it means to “tokenize” an asset Explain what a smart contract is, as well as various applications of smart contracts Explore the features of a distributed, self-sovereign identity system Describe eight core functions of the financial services industry and explain how blockchain will disrupt each of these functions Explain how blockchain technology will transform business structures, roles, and functions Describe seven new blockchain business models Identify some strategic approaches to managing intellectual property with blockchain technologies Identify the layers comprising the blockchain technology stack, and describe how each of these affects the governance of a blockchain ecosystem Identify new ideas or opportunities for blockchain within your chosen industry Explain how you will position your idea, including how your idea will create new value for your customers Identify the business model decisions that would need to be made in order to assess the feasibility of your idea Describe what would need to change in your organization's current way of operating in order to bring your idea to fruition

4 course series

Beginner level

2 months (at 10 hours a week)

https://www.coursera.org/specializations/blockchain-revolution-enterprise

Global Diplomacy: the United Nations in the World

87,358

4.7

Dr Dan Plesch, SOAS University of London

University of London

[]

The course offers a well-researched and broad-ranging primer to the United Nations system. Consisting of an introduction to the complex UN family and its history, and a series of ‘snapshots’ of key UN functions, which are used to explore important UN themes and help learners develop important analysis, communication, and policy-based skills. The course is aimed broadly at people interested in learning more about the United Nations system, assuming a level of interest but no necessary previous knowledge, whilst also offering offering sufficient up to date research and new critical perspectives that it will also be of interest to people with more expertise or academic familiarity with the topic as well. The main aim of the course is to provide this wide-ranging introduction in a self-contained, but in-depth form, alongside the important practical skills necessary to understand and discuss UN affairs, and potentially lay the groundwork for greater engagement in future – either in civil society or in further study. An overview of the MOOC 1 video3 readings This week will introduce the idea of the United Nations as a system of more-or-less connected agencies that exist to address a wide range of world problems, and provide an overview of how different parts fit together to constitute the modern United Nations system. 2 videos1 reading1 peer review This week will provide an overview of the historical circumstances of the beginning of the UN – what early UN agencies were, what were the influential powers and groups at the early negotiations, and what values the UN was founded on, with comparisons to modern-day approaches. 2 videos1 reading1 peer review This week will use the UN Security Council as a primer to the issue of relative power in international institutions. After examining the structure and operations of the Council, it will encourage students to examine the fundamental issues that determine its existence, including the status of the five permanent members, its ability to carry out its function, and the prospects for reform. 2 videos1 reading1 peer review This week will address the question of human rights at the UN, introducing the basic documents and declarations that underpin much UN activity. It will introduce the wide range of UN declarations on this topic, how they came about, and then examine potential criticisms of modern UN conceptions of human rights- highlighting revolutionary work on the origins and practice of human rights from our research groups. The non-Western origins of sex equality in the UN Charter and the Universal Declaration of HR changed the understanding of women’s rights to one where they are created by women from the South. In parallel, the war crimes narrative focused on the Nazi leadership is transformed by understanding that there was a UN body including China and India that resulted in convictions of thousands of Nazis and Japanese war criminals. This work features in an HBO Documentary, a Ted Talk on the UN women issue and Netflix and Amazon/Ch4 documentaries featuring the war crimes research. 2 videos1 reading1 peer review This week will introduce the family of UN agencies involved in humanitarian work, and begin to unpack their relationships with each other and role in responding to conflict. 2 videos1 reading1 peer review In this week, students will have a chance to review and draw together what they have learned over the previous weeks, and develop analysis skills when assessing how different priorities. This exercise will also introduce the issue of practicality and organisational politics to it, giving students an opportunity to consider how the issues they have examined might be affected by the process of implementation. 2 videos1 reading1 peer review

7 modules

Beginner level

https://www.coursera.org/learn/global-diplomacy-un

98%

Game Design and Development 1: 2D Shooter

34,277

4.7

Brian Winn

Michigan State University

['Game Making', 'Unity', 'Video Game Development', 'technology', 'Game Design']

If you love games and want to learn how to make them, then this course will start you down that path. Making games is a creative and technical art form. In this course you will familiarize yourself with the tools and practices of game development and well as the process. You will get started developing video games using industry standard game development tools, including the Unity 2020 game engine. At the end of the course you will have completed two hands-on projects, including an Intro to Unity project and a 2D Shooter game, and will be able to leverage an array of game development techniques to create your own basic games. The only thing more fun than playing games is making them. You can make games. All it takes is some time, a willingness to learn and a passion to create. You don't need to be a "coder" to make games. Part of the beauty of games is that they take a variety of skills to make. Art, creativity, and systems thinking are just as important as code. Join us in this journey into game making! This first module will provide you with an overview of this course and the entire specialization. The module will also introduce you to the game design and development process and get you up and running with Unity, the game engine we will use across this course. 13 videos6 readings3 assignments One of the reasons we use Unity is its visual editor which makes creating interactive games accessible to both creative and technical individuals. In this module, you will continue working on the Solar System project and from start to finish. Using a variety of graphical and audio assets and a library of scripts, you will create a simple model of our solar system. By the end of the module, you should have a good understanding of the Unity editor, the core concepts of building projects in Unity, and the workflow for creating games. 10 videos4 readings3 assignments1 peer review Unity is a powerful tool for creating games. In this module, you will create your first actual game from start to finish in the form of a 2D Shooter game. This is your right of passage into game development! In the first part of the assignment, follow along with the tutorial videos in this module. In the second part of the project, you will modify the game to make it your own. 18 videos2 readings Now, don't get scared, but games need code. Code is the canvas upon which game systems are painted. However, that doesn't mean you need to be a C# ninja. In this module, you will start to learn the ins-and-outs of programming C# in Unity. In this module, you will also finish up the 2D Shooter project, submit it for peer review, and peer review your fellow learners games. Finish the course strong! 9 videos2 readings1 assignment1 peer review

4 modules

Beginner level

https://www.coursera.org/learn/game-design-and-development-1

95%

Blockchain Basics

253,185

4.6

Bina Ramamurthy

University at Buffalo

['Ethereum', 'Cryptography', 'Blockchains', 'Bitcoin']

This first course of the Blockchain specialization provides a broad overview of the essential concepts of blockchain technology – by initially exploring the Bitcoin protocol followed by the Ethereum protocol – to lay the foundation necessary for developing applications and programming. You will be equipped with the knowledge needed to create nodes on your personal Ethereum blockchain, create accounts, unlock accounts, mine, transact, transfer Ethers, and check balances. You will learn about the decentralized peer-to-peer network, an immutable distributed ledger and the trust model that defines a blockchain. This course enables you to explain basic components of a blockchain (transaction, block, block header, and the chain) its operations (verification, validation, and consensus model) underlying algorithms, and essentials of trust (hard fork and soft fork). Content includes the hashing and cryptography foundations indispensable to blockchain programming, which is the focus of two subsequent specialization courses, Smart Contracts and Decentralized Applications (Dapps). You will work on a virtual machine image, specifically created for this course, to build an Ethereum test chain and operate on the chain. This hands-on activity will help you understand the workings of a blockchain, its transactions, blocks and mining. Main concepts are delivered through videos, demos and hands-on exercises. We will introduce and define blockchain, explain the structure and operational aspects of Bitcoin blockchain, and compare different types of blockchains. 5 videos6 readings5 assignments We will discuss the innovation of the Ethereum blockchain, review its protocol, and explore the payment model for code execution. 5 videos5 readings5 assignments We will discuss the concept of asymmetric key encryption, define the concept of hashing, and explain techniques that use algorithms to manage the integrity of transactions and blocks in blockchain. 4 videos5 readings5 assignments We will define elements of trust in blockchain and discuss the Consensus protocol. 5 videos5 readings5 assignments1 programming assignment

4 modules

Beginner level

https://www.coursera.org/learn/blockchain-basics

95%

Excel Basics for Data Analysis

380,104

4.8

Sandip Saha Joy

IBM

['Data Science', 'Spreadsheet', 'Data Analysis', 'Microsoft Excel', 'Pivot Table']

Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data. This course is suitable for those who are interested in pursuing a career in data analysis or data science, as well as anyone looking to use Excel for data analysis in their own domain. No prior experience with spreadsheets or coding is required - all you need is a device with a modern web browser and the ability to create a Microsoft account to access Excel online at no cost. If you have a desktop version of Excel, you can also easily follow along with the course. Throughout this course, you'll gain valuable experience working with data sets and spreadsheets. We'll start by introducing you to spreadsheets like Microsoft Excel and Google Sheets, and show you how to load data from multiple formats. From there, you'll learn how to perform basic data wrangling and cleansing tasks using functions, and expand your knowledge of data analysis through the use of filtering, sorting, and pivot tables. There is a strong focus on practice and applied learning in this course. With each lab, you'll have the opportunity to manipulate data and gain hands-on experience using Excel. You'll learn how to clean and format your data efficiently, and convert it into a pivot table to make it more organized and readable. The final project will allow you to showcase your newly acquired data analysis skills by working with real data sets and spreadsheets. By the end of this course, you'll have a solid foundation in using Excel for data analysis. You'll have worked with multiple data sets and spreadsheets, and will have the skills and knowledge needed to effectively clean and analyze data without having to learn any code. So let's get started! In this module, you will learn about the fundamentals of spreadsheet applications, and you will be introduced to the Excel interface and learn how to navigate your way around a worksheet and workbook. 5 videos1 reading2 assignments3 plugins In this module you will learn how to perform basic spreadsheet tasks, such as viewing, entering and editing data, and moving, copying and filling data. In addition, you will learn about the fundamentals of formulas, and learn about the most common functions used by a data analyst. Finally, you will learn how to reference data in formulas. 5 videos1 reading2 assignments2 plugins In this module, you will learn about the importance of data quality, and you will learn how to import file data in to Excel. You will also learn about the fundamentals of data privacy. In addition, you will learn how to remove duplicate and inaccurate data, and how to remove empty rows in your data. Finally, you will learn how to deal with inconsistencies in your data and how to use the Flash Fill and Text to Columns features to help you manipulate and standardize your data. 8 videos3 readings4 assignments1 plugin In this module, you will learn about the fundamentals of analyzing data using a spreadsheet, and learn how to filter and sort data. You will also learn how to use some of the most useful functions for a data analyst, and how to use the VLOOKUP and HLOOKUP reference functions. In addition, you will learn how to create pivot tables in Excel, and use several pivot table features. 8 videos2 readings4 assignments3 plugins Great! You have now completed all four modules of this course. In this final module, you will be introduced to a hands-on lab where you will complete a graded assignment for cleaning and preparing data, and then analyzing data using an Excel spreadsheet. This final assignment will be graded by your peers. 2 readings1 peer review2 plugins

5 modules

Beginner level

https://www.coursera.org/learn/excel-basics-data-analysis-ibm

96%

Communicating with the Public

Enrollment number not found

Rating not found

Marcy McGinnis

University of California San Diego

['Communication', 'Writing', 'Interviewee Skills', 'Public Speaking']

Rooted in theater, journalism and humanities practices, this course presents tools and techniques that help you improve your public-facing communication skills, particularly when describing your work to a lay audience. Whether it’s a 30-second elevator pitch or speaking to a large organization, “Communicating with the Public” will boost your confidence in any speech-communication scenario. 1 reading 1 video1 reading 1 video 1 video 1 video 1 video 1 video 1 video 1 video2 readings 1 video 1 video 1 video 1 video1 reading 1 video1 reading1 assignment

14 modules

Beginner level

1 hour to complete

https://www.coursera.org/learn/communicating-with-the-public

Malware Analysis and Introduction to Assembly Language

7,993

4.5

IBM Skills Network Team

IBM

[]

Malicious software, or malware, is typically delivered over a network and is designed to cause disruption to a computer, client, server, or network. Disruptions can include leaked private information, unauthorized access to information or systems, blocked user access, interference with security and privacy, or numerous other variations of attacking systems. Malware analysis dissects malware to gather information about the malware functionality, how the system was compromised so that you can defend against future attacks. Assembly is a low-level language that is used to communicate with the machine. Assembly programming is writing human-readable machine codes or machine instructions that are directly read by the computer. All high-level languages compiled programs like C or C++ can be broken down, analyzed, and understood using Assembly language with the help of a debugger. This process is known as reverse engineering. Understanding what an executable program does is easy if you have direct access to the source code. But if not, such as the case with malware, learning Assembly can be helpful. In this course, through video demonstrations, hands-on reverse engineering, and capture-the-flag type activities, you will be introduced to the processes and methods for conducting malware analysis of different file types. You will analyze native executable files, and analyze popular files like PowerShell, JavaScripts, and Microsoft Office documents. Then you will learn the fundamentals of Assembly language, basic Win32 Assembly programming concepts, and how Reverse Engineers use Assembly to analyze malware. In this module, you will learn about malware analysis and the process. 2 videos1 reading2 assignments In this module, you will be given guidance on how to create a testing VM in your own environment, which will provide a safe self-contained system in which to analyze sample files. 4 videos10 readings1 assignment In this module, you will learn about and set up static and dynamic analysis 5 videos5 readings7 assignments In this module, you will learn about and perform manual code reversing. 4 videos3 readings4 assignments In this module, you will analyze several common sample types. 4 videos7 readings7 assignments ELF is the default executable file format on Linux systems. In this module, you will learn how to set up REMnux and analyze an ELF file. 3 videos3 readings4 assignments In this module, you will learn how to analyze webshells and JAR files. 3 videos5 readings5 assignments 6 videos1 reading4 assignments 1 reading

9 modules

Beginner level

21 hours to complete (3 weeks at 7 hours a week)

https://www.coursera.org/learn/malware-analysis-and-assembly

What is Compliance?

37,059

4.8

Andrew Kandel

University of Pennsylvania

['Risk Management', 'Compliance', 'Brand Management', 'Strategic Planning']

Compliance isn’t only about preventing problems and ensuring that everyone is abiding by laws, rules, and regulations. It’s also about the positive impact a robust and ethical compliance program can have on a business or organization. In this course we will discuss why compliance is important – from the needs facing businesses in highly regulated industries to avoiding fines and penalties to preventing reputational and economic nightmares. We’ll examine real-world examples of compliance and governance failures and their impact, and consider strategies for avoiding similar situations in our own organizations. You’ll be able to think about risk management in new ways and apply strategies to manage it. What is compliance and why is it important? In this module, we answer those questions while also looking at some recent high-profile cases of non-compliance in the business world. 8 videos3 readings2 assignments2 discussion prompts Non-compliance can have massive real-world implications for the general public, not just individuals directly related to a non-compliant company. In this module, we examine laws that specifically create compliance obligations, as well as the potential costs of non-compliance. 6 videos1 reading4 assignments1 discussion prompt Every company and organization must deal with risk, and compliance is ultimately a vehicle to mitigate risk. This module explores the close relationship between compliance and risk management. We will analyze the ways in which compliance programs manage risk, as well as alternative forms of risk management. 5 videos2 readings2 assignments1 discussion prompt This module highlights developments in the ever-evolving world of compliance, with special emphasis on recent trends in regulatory focus. 3 videos3 readings1 assignment1 peer review1 discussion prompt

4 modules

10 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/what-is-compliance

96%

Digital Manufacturing & Design Technology Specialization

45,329

4.6

Ken English

The State University of New York

['Artificial Intelligence (AI)', 'Digital Design', 'Manufacturing Engineer', 'Industry 4.0', 'Artificial Intelligence (AI)', 'Digital Design', 'Manufacturing Engineer', 'Industry 4.0']

Whether you’re a high school graduate exploring manufacturing careers, or an operations manager hungry for an understanding of the newest manufacturing technologies, this specialization will provide a foundation in how digital advances are changing the landscape and capabilities of factories. Nine courses – developed with input from the manufacturing industry – touch on Industry 4.0 and its components, including digital manufacturing and design practices, the concept of the digital thread, the Internet of Things and Big Data. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser:https://youtu.be/wETK1O9c-CAOpens in a new tab Applied Learning Project Learners will create a roadmap to achieve their own personal goals related to the digital manufacturing and design (DM&D) profession, which will help them leverage relevant opportunities. The culminating project provides a tangible element to include in their professional portfolios that showcases their knowledge of Industry 4.0. This course will expose you to the transformation taking place, throughout the world, in the way that products are being designed and manufactured. The transformation is happening through digital manufacturing and design (DM&D) – a shift from paper-based processes to digital processes in the manufacturing industry. By the end of this course, you’ll understand what DMD is and how it is impacting careers, practices and processes in companies both large and small. You will gain an understanding of and appreciation for the role that technology is playing in this transition. The technology we use every day – whether it is communicating with friends and family, purchasing products or streaming entertainment – can benefit design and manufacturing, making companies and workers more competitive, agile and productive. Discover how this new approach to making products makes companies more responsive, and employees more involved and engaged, as new career paths in advanced manufacturing evolve. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the first course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA This course will help you recognize how the "digital thread" is the backbone of the digital manufacturing and design (DM&D) transformation, turning manufacturing processes from paper-based to digital-based. You will have a working understanding of the digital thread – the stream that starts at product concept and continues to accumulate information and data throughout the product’s life cycle – and identify opportunities to leverage it. Gain an understanding of how "the right information, in the right place, at the right time" should flow. This is one of the keys to unlocking the potential of a digital design process. Acknowledging this will enable you to be more involved in a product’s development cycle, and to help a company become more flexible. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the second course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA There are opportunities throughout the design process of any product to make significant changes, and ultimately impact the future of manufacturing, by embracing the digital thread. In this course, you will dig into the transformation taking place in how products are designed and manufactured throughout the world. It is the second of two courses that focuses on the "digital thread" – the stream that starts at the creation of a product concept and continues to accumulate information and data throughout the product life cycle. Hear about the realities of implementing the digital thread, directly from someone responsible for making it happen at a company. Learn how the digital thread can fit into product development processes in an office, on a shop floor, and even across an enterprise. Be prepared to talk about the benefits, and limitations, of enacting it. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the third course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA Variability is a fact of life in manufacturing environments, impacting product quality and yield. Through this course, students will learn why performing advanced analysis of manufacturing processes is integral for diagnosing and correcting operational flaws in order to improve yields and reduce costs. Gain insights into the best ways to collect, prepare and analyze data, as well as computational platforms that can be leveraged to collect and process data over sustained periods of time. Become better prepared to participate as a member of an advanced analysis team and share valuable inputs on effective implementation. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the fourth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA Manufacturers are increasingly utilizing machine tools that are self-aware – they perceive their own states and the state of the surrounding environment – and are able to make decisions related to machine activity processes. This is called intelligent machining, and through this course students will receive a primer on its background, tools and related terminology. Learn how the integration of smart sensors and controls are helping to improve productivity. You’ll be exposed to various sensors and sensing techniques, process control strategies, and open architecture systems that can be leveraged to enable intelligent machining. This course will prepare you to contribute to the implementation of intelligent machining projects. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the fifth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA Enterprises that seek to become proficient in advanced manufacturing must incorporate manufacturing management tools and integrate data throughout the supply chain to be successful. This course will make students aware of what a digitally connected enterprise is, as they learn about the operational complexity of enterprises, business process optimization and the concept of an integrated product-process-value chain. Students will become acquainted with the available tools, technologies and techniques for aggregation and integration of data throughout the manufacturing supply chain and entire product life-cycle. They will receive foundational knowledge to assist in efforts to facilitate design, planning, and production scheduling of goods and services by applying product life cycle data. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the sixth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA The nature of digital manufacturing and design (DM&D), and its heavy reliance on creating a digital thread of product and process data and information, makes it a prime target for hackers and counterfeiters. This course will introduce students to why creating a strong and secure infrastructure should be of paramount concern for anyone operating in the DM&D domain, and measures that can be employed to protect operational technologies, systems and resources. Acquire knowledge about security needs and the application of information security systems. Build the foundational skills needed in performing a risk assessment of operational and information technology assets. Gain valuable insights of implementing controls to mitigate identified risks. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the seventh course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA This Model-Based Systems Engineering (MBSE) course and the Digital Thread courses featured earlier in this specialization bring together the concepts from across digital manufacturing and design, forming a vision in which the geometry of a product is just one way of describing it. MBSE is where the model resulting from the evolution of system requirements, design, analysis, verification and validation activities is the focus of design and manufacturing. Students will gain an understanding of systems engineering, the model-based approach to design and manufacturing, the Digital Twin, and a roadmap toward a model-based enterprise. Students will be able to explain the value and expectations of systems engineering and model-based systems engineering, and the underlying motivations and opportunities represented by a model-based enterprise. They will develop the knowledge necessary to perform a baseline assessment of an organization’s potential to leverage MBSE. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the eighth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA Learners will create a roadmap to achieve their own personal goals related to the digital manufacturing and design (DM&D) profession, which will help them leverage relevant opportunities. The culminating project provides a tangible element to include in their professional portfolios that showcases their knowledge of Industry 4.0. This project is part of the Digital Manufacturing and Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0. To learn more about the specialization and its courses, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA

9 course series

Beginner level

4 months (at 10 hours a week)

https://www.coursera.org/specializations/digital-manufacturing-design-technology

Community Engagement in Research and Population Health

Enrollment number not found

Rating not found

Theresa Green

University of Rochester

[]

Welcome to the Community Engagement in Population Health course! As you will learn, the health system is in the midst of a critical transition. The current system is not sustainable with escalating costs, mediocre health outcomes, and unacceptable disparities. This course will first discuss the current system, including definitions of population health and social determinants of health, and how the US compares to other countries on the triple aim –lower cost, better care, and a healthier population. Section 2 will review resources for both population health data and evidence-based public health interventions. Now more than ever, hospitals are addressing community needs through community benefits spending, community health improvement planning, and problem-based research networks. In the final section, the course describes community engagement in practical terms with a discussion of benefits and barriers. Community-based participatory research is presented as an effective way to engage the community in developing solutions to address problems in the health system. Establishing the Need for a New Paradigm -- The current US health care system is broken. In this introductory section, we will explore how the United States compares to other health systems in the world on both cost and health outcomes. We will discuss what is meant by good health, as well as defining the term “population health”. We will discuss what is meant by the American health paradox and how our country’s values have led to social inequities which contribute to substantial health disparities. The current US health system is not sustainable, and solutions can be discovered when we look outside of the health care delivery system for answers. 11 videos12 readings2 assignments1 discussion prompt Creating change requires an understanding of population health data. We will begin this section by reviewing data resources, including resources for mapping data to create a visual representation of population health outcomes. We will also discuss some of the ways this data is collected by reviewing public health surveys and common data collection tools. Improving the health system often involves implementing interventions, and just like in medicine, public health interventions should be evidence-based. We will review some resources for evidence-based community health interventions and discuss ways to evaluated and disseminate results that are useful to community members. 8 videos10 readings3 assignments2 discussion prompts Engaging the community is important in changing the paradigm and working to improve the US health system as a whole. In this section, we will explore ways in which health care delivery systems are engaging community and addressing community health. This community engagement is federally mandated for non-profit hospitals and health systems through community benefit reporting and community health needs assessments and improvement plans. In addition, the movement towards value based medicine has really motivated health systems to think beyond the walls of the hospital to explore the population’s health. 4 videos7 readings1 assignment1 discussion prompt In this section, we will define community-engaged research and apply the principles of effective community engagement to research as well as interventions. Community Engagement takes many forms, some much more reciprocal and collaborative than others. In this interactive discussion, our speakers will discuss the benefits of effective community engagement as well as barriers that are common, and suggestions for alleviating those challenges. 9 videos7 readings4 assignments2 discussion prompts

4 modules

Beginner level

20 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/community-engagement-research-population-health

Machine Learning Rapid Prototyping with IBM Watson Studio

1,532

4.1

Mark J Grover

IBM

['Data Science', 'Python Programming', 'Information Engineering', 'Machine Learning', 'Artificial Intelligence (AI)']

An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research. The focus will be on working with an auto-generated Python notebook. Learners will be provided with test data sets for two use cases. This course is intended for practicing Data Scientists. While it showcases the automated AI capabilies of IBM Watson Studio with AutoAI, the course does not explain Machine Learning or Data Science concepts. In order to be successful, you should have knowledge of: Data Science workflow Data Preprocessing Feature Engineering Machine Learning Algorithms Hyperparameter Optimization Evaluation measures for models Python and scikit-learn library (including Pipeline class) In this module, you'll learn about the developing landscape of AutoAI technologies. You'll also become familiar with the Watson Studio platform in order to be able to perform your own AutoAI Experiments. After observing the AutoAI tool build prototypes for two use cases, you will try out the tool for yourself to build additional prototypes. 7 videos14 readings4 assignments In this module, you will learn about the automated data preparation techniques performed by AutoAI and get a chance to experiment with different settings for data preprocessing in the AutoAI-generated Python notebook. You'll also learn about the procedure for automated model selection and experiment using different models on the datasets. 9 videos11 readings3 assignments In this module, you will learn about the algorithm for automated feature engineering and perform some exploratory data analysis to try to understand why the algorithm performed particular feature transformations. You'll also learn about sophisticated methods for optimizing hyperparameters and explore hyperparameter tuning on the datasets using the AutoAI-generated Python notebook. 9 videos11 readings3 assignments In this module, you will evaluate prototypes using the different evaluation metrics calculated by the AutoAI tool. You will also deploy the prototype for testing using the Watson Machine Learning API. 4 videos9 readings3 assignments1 peer review

4 modules

Intermediate level

8 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/ibm-rapid-prototyping-watson-studio-autoai

Product Management Essentials

35,189

4.6

Dr. James V. Green

University of Maryland, College Park

['Leadership', 'Product Management', 'Product Development', 'Marketing', 'Customer Development']

Product management is one of the fastest growing and most lucrative jobs available today. Companies have awoken to the desperate need for product managers to create products that customers love, that integrate design, functionality, and business solutions. In our course, we define the fundamentals of product management and why this role is so coveted as a launch pad for future CEOs and startup founders. To be effective, product managers need a clear understanding of their jobs and duties. They also need a clear understanding of the required skills and competencies. An appreciation of these roles, responsibilities, skills, and capabilities is also beneficial for stakeholders and team members who collaborate with product managers. This course investigates the framework for success in product management by defining the product manager’s position in an organization and the key responsibilities. We will examine the skills and competencies most critical to carrying out those responsibilities. To further improve your understanding of product management, we will discuss how product managers engage with the product team and stakeholders to create and manage successful products. Product managers must also know how to establish, organize, and lead a team. They must know the typical product development life cycle and be able to select the right development methodology for the product and the target market. To meet these challenges to product team leadership, we will consider the phases of product development and the roles that product managers play in each step. We’ll examine a variety of team structures and product development methodologies, and the importance of establishing a team charter. Lastly, we will also explore the opportunities and challenges of market development and commercialization. We’ll provide an orientation to key marketing concepts critical to developing and commercializing innovative products and services. Get acquainted with the learning experience and course format, meet the faculty, and connect with classmates from across the globe. 1 video5 readings 11 videos4 readings1 assignment1 discussion prompt 20 videos4 readings1 assignment1 discussion prompt 13 videos3 readings1 assignment1 discussion prompt

4 modules

Beginner level

https://www.coursera.org/learn/product-management-essentials

98%

AI Workflow: Feature Engineering and Bias Detection

4,797

4.4

Mark J Grover

IBM

['Artificial Intelligence (AI)', 'Data Science', 'Python Programming', 'Information Engineering', 'Machine Learning']

This is the third course in the IBM AI Enterprise Workflow Certification specialization.    You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 3 introduces you to the next stage of the workflow for our hypothetical media company.  In this stage of work you will learn best practices for feature engineering, handling class imbalances and detecting bias in the data.  Class imbalances can seriously affect the validity of your machine learning models, and the mitigation of bias in data is essential to reducing the risk associated with biased models.  These topics will be followed by sections on best practices for dimension reduction, outlier detection, and unsupervised learning techniques for finding patterns in your data.  The case studies will focus on topic modeling and data visualization.   By the end of this course you will be able to: 1.  Employ the tools that help address class and class imbalance issues 2.  Explain the ethical considerations regarding bias in data 3.  Employ ai Fairness 360 open source libraries to detect bias in models 4.  Employ dimension reduction techniques for both EDA and transformations stages 5.  Describe topic modeling techniques in natural language processing 6.  Use topic modeling and visualization to explore text data 7.  Employ outlier handling best practices in high dimension data 8.  Employ outlier detection algorithms as a quality assurance tool and a modeling tool 9.  Employ unsupervised learning techniques using pipelines as part of the AI workflow 10.  Employ basic clustering algorithms   Who should take this course? This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. If you are an aspiring Data Scientist, this course is NOT for you as you need real world expertise to benefit from the content of these courses.   What skills should you have? It is assumed that you have completed Courses 1 and 2 of the IBM AI Enterprise Workflow specialization and you have a solid understanding of the following topics prior to starting this course: Fundamental understanding of Linear Algebra; Understand sampling, probability theory, and probability distributions; Knowledge of descriptive and inferential statistical concepts; General understanding of machine learning techniques and best practices; Practiced understanding of Python and the packages commonly used in data science: NumPy, Pandas, matplotlib, scikit-learn; Familiarity with IBM Watson Studio; Familiarity with the design thinking process. This module will introduce you to skills required for effective feature engineering in today's business enterprises. The skills are presented as a series of best practices representing years of practical experience. 6 videos14 readings5 assignments1 ungraded lab This module will continue the discussion of skill related to feature engineering for practicing data scientists, with a focus on outliers and the use of unsupervised learning techniques for finding patterns. 5 videos11 readings5 assignments1 ungraded lab

2 modules

Advanced level

12 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/ibm-ai-workflow-feature-engineering-bias-detection

Tools for Security Specialists Specialization

Enrollment number not found

4.8

Max Kraev

Codio

['Linux Console', 'System Security', 'security', 'Security Strategy']

This specialization is intended for security beginners. No prior experience is needed. Learn how security works across the organizational spectrum. This includes high-level concepts like integrating security monitoring and automation, adopting well-known security standards, as well as learning how to secure a Linux machine. Applied Learning Project Many of the topics are a high-level overview of how security works at large organizations. We are unable to simulate the activity of an entire organization for the purposes of this specialization. You will also learn about common tools used to harden a Linux system. Learners will discover how to construct a proper security system, the role monitoring plays, and how to codify this through policy. Learners will discover how to protect networks and physical locations. Learners will discover how to protect information at the application and data level. Learners will discover how a security operations center helps maintain security at an organization. Learners will identify the roles of security orchestration, security automation, and incident response. Learners will define the lifecycle of a SOAR event, as well as identify the pros and cons of SOAR. Learners will discover security challenges faced by organizations, and how ISO/IEC standards (specifically the 27000 series) address them. Learners will discover the most common security standards: 27001, 27002, and 27701. Learners will discover how to manage risk with ISO and IEC standards. What are the available tools and resources for Linux Security professionals.

4 course series

Beginner level

3 months (at 10 hours a week)

https://www.coursera.org/specializations/codio-tools-for-security-specialists

Achieving Personal and Professional Success Specialization

56,116

4.7

Richard Shell

University of Pennsylvania

['goal setting', 'Communication', 'Negotiation', 'Deception', 'Happiness', 'Personality Development', 'Personal Development', 'goal setting', 'Communication', 'Negotiation', 'Deception', 'Happiness', 'Personality Development', 'Personal Development']

Based on four of the most popular courses taught at the Wharton School,Achieving Personal and Professional Successis designed to introduce the tools and techniques for defining and achieving success at home and at work. You'll learn how to find your passion and core values, how to apply these values to your own life, how to work well with others, how to communicate effectively, how to set goals, how to use influence to achieve these goals, and even how to say you are sorry. Through exercises, self-diagnostic surveys, quizzes, and many case studies, you'll discover how to define not only what you want, but also the best way to get it. While many business courses cover topics related to successful organizational practices, these courses provide key insights into successful personal practices, whether you are in the office or in your home. We all bring ourselves to work every day, and these courses will help you be your best self wherever you are. Applied Learning Project Learners will discover their core values, create a personal success plan, learn how to apply their values for the best results at home and work, and develop a method for communicating effectively and using influence to achieve their goals. These courses will help you be your best self wherever you are. Do you want to be more successful? This course was designed to help you define what success means to you, and to develop a plan for achieving it. Wharton Professor G. Richard Shell, an award-winning author and the creator of the popular Wharton School course on the meaning of success, created this course to help you answer the questions that arise when you consider how best to use your life. Drawing on his decades of research and mentoring, Shell offers personalized assessments to help you probe your past, imagine your future, and measure your strengths. He then combines these with the latest scientific insights on everything from self-confidence and happiness to relationships and careers. Throughout, he shares inspiring examples of people who found what they were meant to do by embracing their own true measure of success. Get ready for the journey of a lifetime—one that will help you reevaluate your future and envision success on your own terms. Students and executives say that Richard Shell’s courses and executive training programs have changed their lives. Let this course change yours. Learn how to communicate more effectively at work and achieve your goals. Taught by award-winning Wharton professor and best-selling author Maurice Schweitzer, Improving Communications Skills is an essential course designed to give you both the tools you need to improve your communication skills, and the most successful strategies for using them to your advantage. You'll learn how to discover if someone is lying (and how to react if they are), how to develop trust, the best method of communication for negotiation, and how to apologize. You'll also learn when to cooperate and when to compete, how to create persuasive messages, ask thoughtful questions, engage in active listening, and choose the right medium (face-to-face conversation, video conference, phone call, or email) for your messages. By the end of the course, you'll be able to understand what others want, respond strategically to their wants and needs, craft convincing and clear messages, and develop the critical communication skills you need to get ahead in business and in life. What does it mean to be influential? How does one persuade others to pursue a unified goal? How does one leverage power? In this course, you’ll learn how to develop influence and to become more effective in achieving your organizational goals. Professor Cade Massey of the Wharton School has designed this course to help you understand the framework of power and influence and the dynamics of effective networks, and shows you how to develop your skills of persuasion and leverage. By the end of this course, you’ll know your own strengths and how to use them to get what you need, how to gain power and influence, and how to leverage relationships and alliances to achieve your goals in both business and in life. In this course, you will learn crucial skills needed to understand the intricate dynamics that go into the process of negotiation, and how you can go into your negotiation confident and fully prepared. You'll learn about the framework that goes into shaping a successful negotiation, in addition to gaining the knowledge that will allow you to adapt to rapidly changing circumstances. You'll also learn about emotional control, crafting questions to help you get the information that you need, and skills that will allow you to negotiate in any setting. You will also successfully learn how to navigate a negotiation through real-world exercises, and how to best work to build trust, diffuse anger, and make rational decisions based on the information at hand. Lastly, you will learn how to prepare to negotiate in any setting and use your skills to facilitate with teams and influence outcomes. By the end of this course, you’ll be able to utilize your newly acquired skills to successfully negotiate for employment, contracts, and in any part of your life. Within this course, you will end with the knowledge of how to craft a successful negotiation strategy and manage the conflict that can arise, as well as build trust.

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/wharton-success

Statistical Thinking for Industrial Problem Solving, presented by JMP

10,109

4.9

Mia Stephens

SAS

['Statistics', 'Data Analysis', 'Experimental Design', 'Statistical Hypothesis Testing', 'Data Visualization']

Statistical Thinking for Industrial Problem Solving is an applied statistics course for scientists and engineers offered by JMP, a division of SAS. By completing this course, students will understand the importance of statistical thinking, and will be able to use data and basic statistical methods to solve many real-world problems. Students completing this course will be able to: • Explain the importance of statistical thinking in solving problems • Describe the importance of data, and the steps needed to compile and prepare data for analysis • Compare core methods for summarizing, exploring and analyzing data, and describe when to apply these methods • Recognize the importance of statistically designed experiments in understanding cause and effect In this module you learn about the course and about accessing JMP software in this course. 3 videos4 readings1 app item Statistical thinking is about understanding, controlling and reducing process variation. Learn about process maps, problem-solving tools for defining and scoping your project, and understanding the data you need to solve your problem. 26 videos3 readings16 assignments1 app item7 plugins Learn the basics of how to describe data with basic graphics and statistical summaries, and how to explore your data using more advanced visualizations. You’ll also learn some core concepts in probability, which form the foundation of many methods you learn throughout this course. 50 videos31 assignments1 app item4 plugins Learn how to use interactive visualizations to effectively communicate the story in your data. You'll also learn how to save and share your results, and how to prepare your data for analysis. 36 videos2 readings31 assignments2 app items2 plugins Learn about tools for quantifying, controlling and reducing variation in your product, service or process. Topics include control charts, process capability and measurement systems analysis. 41 videos3 readings26 assignments2 app items2 plugins Learn about tools used for drawing inferences from data. In this module you learn about statistical intervals and hypothesis tests. You also learn how to calculate sample size and see the relationship between sample size and power. 47 videos2 readings38 assignments2 app items5 plugins Learn how to use scatterplots and correlation to study the linear association between pairs of variables. Then, learn how to fit, evaluate and interpret linear and logistic regression models. 43 videos2 readings30 assignments2 app items5 plugins In this introduction to statistically designed experiments (DOE), you learn the language of DOE, and see how to design, conduct and analyze an experiment in JMP. 36 videos2 readings25 assignments2 app items4 plugins Learn how to identify possible relationships, build predictive models and derive value from free-form text. 39 videos2 readings30 assignments2 app items In this module you have an opportunity to test your understanding of what you have learned. 2 assignments1 app item

10 modules

Beginner level

https://www.coursera.org/learn/statistical-thinking-applied-statistics

96%

Being Smart about Cycling Futures

1,549

4.8

Marco te Brömmelstroet

University of Amsterdam

['Futures thinking', 'Critical Thinking', 'Bicycle planning', 'Innovation', 'Systems Thinking']

What is the future of cycling in our cities that struggle to transition to more sustainable and inclusive forms of mobility? What is the role of innovation in ensuring that cycling becomes easier, safer and more accessible for different groups of people? What are Great Bikes and what are Great Cycling Cities? In this course we tackle these questions, but we do so without providing recipes, one-size-fits-all solutions or rankings of innovations. Instead, this course helps you to develop your own approach to cycling futures and innovation. It teaches you to ask critical questions about various aspects of cycling practice and its place in mobility systems, about cycling innovation and the way in which various stakeholders imagine cycling futures. This unique course is grounded in the results of the Smart Cycling Futures project (2016-2020), conducted in the Netherlands but through readings and assignments it engages with the wider world. Course development was made possible by sponsor enviolo. What will the future of cycling be like? This module introduces you to one of the main ideas of the course: that cycling futures are multiple and contested. You will be introduced to velotopias- visions of urban future in which cycling is the key mode of transportation- and to cycling innovations. You'll learn about the Smart Cycling Futures research project and the paradoxes encountered in researching innovations. You will notice that scholars and innovators have different ideas on how cycling should become a more important part of our lives. The different futures that we envision prioritize different values and different ideas about cities, mobility and human interaction. 6 videos10 readings3 assignments1 discussion prompt In this module you will learn about how cycling and cycling innovations are part of a larger mobility system. First, should the goal of innovations always be to get people to shift to cycling from other modes? And, do innovations forget about the people who are already cycling? How does the practice of cycling fit with other modes? This module will also introduce you to the bike-train system, which has become highly developed in the Netherlands. 4 videos4 readings3 assignments1 discussion prompt1 plugin How do innovations change the experience of cycling, its meaning, and how it is governed? This week will introduce you to new technologies and smart innovations, including both bicycles themselves and also bike infrastructure, accessories, and mobile applications. You will learn to recognize how innovations are shaped by the context in which they are developed. You'll understand how innovations can shape futures of cycling, and recognize moments where we may be choosing one future over another. We will also zoom into specifically to the subject of e-bikes, through an academic paper and a conversation with bike component manufacturer enviolo. 3 videos4 readings3 assignments1 discussion prompt This module will look at cycling infrastructure, or: how are we reinventing the spaces where cycling occurs in our cities? You will reflect on what "ideal" cycling infrastructure is and recognize that different types of users, with different needs, share our cycle paths and streets. We will zoom in to the concept of cycling highways - a contested phenomenon- from the perspective of practitioners. We will hear about how smart innovations may influence how different kinds of future cycling spaces function from infrastructure company BAM. Finally, we will focus on how cycling practitioners work, exploring an agile way of working in the context of Amsterdam. 5 videos5 readings3 assignments1 discussion prompt This module is about the social context of cycling. Who cycles now, and who will in the future? Is cycling less accessible for some than for others? We will hit the tip of the iceberg on what can be done to make cycling more accessible for all. You will see how certain social groups can be excluded or negatively impacted by cycling policies or infrastructure projects, and you will see how this issue is often context dependent. We also ask you to bring your own perspective on this complex issue, and learn from your peers. 3 videos3 readings3 assignments1 discussion prompt1 plugin In this final module, you will go through an exercise in which you imagine diverging cycling futures yourself. You will then read about the positive imagined utopian futures of your peers. To wrap up the course, you will write an essay that reflects on the limits of our society's collective mobility imagination and how to overcome them. 1 reading1 peer review1 discussion prompt

6 modules

Intermediate level

23 hours to complete (3 weeks at 7 hours a week)

https://www.coursera.org/learn/being-smart-about-cycling-futures

The Total Data Quality Framework

2,688

4.5

Brady T. West

University of Michigan

['Data Analysis', 'Total Data Quality Framework', 'Data Classification']

By the end of this first course in the Total Data Quality specialization, learners will be able to: 1. Identify the essential differences between designed and gathered data and summarize the key dimensions of the Total Data Quality (TDQ) Framework; 2. Define the three measurement dimensions of the Total Data Quality framework, and describe potential threats to data quality along each of these dimensions for both gathered and designed data; 3. Define the three representation dimensions of the Total Data Quality framework, and describe potential threats to data quality along each of these dimensions for both gathered and designed data; and 4. Describe why data analysis defines an important dimension of the Total Data Quality framework, and summarize potential threats to the overall quality of an analysis plan for designed and/or gathered data. This specialization as a whole aims to explore the Total Data Quality framework in depth and provide learners with more information about the detailed evaluation of total data quality that needs to happen prior to data analysis. The goal is for learners to incorporate evaluations of data quality into their process as a critical component for all projects. We sincerely hope to disseminate knowledge about total data quality to all learners, such as data scientists and quantitative analysts, who have not had sufficient training in the initial steps of the data science process that focus on data collection and evaluation of data quality. We feel that extensive knowledge of data science techniques and statistical analysis procedures will not help a quantitative research study if the data collected/gathered are not of sufficiently high quality. This specialization will focus on the essential first steps in any type of scientific investigation using data: either generating or gathering data, understanding where the data come from, evaluating the quality of the data, and taking steps to maximize the quality of the data prior to performing any kind of statistical analysis or applying data science techniques to answer research questions. Given this focus, there will be little material on the analysis of data, which is covered in myriad existing Coursera specializations. The primary focus of this specialization will be on understanding and maximizing data quality prior to analysis. Welcome to the Total Data Quality Framework Course! This is the first course in the Total Data Quality Specialization. This week, you’ll get to know your instructors after reviewing the course syllabus and the learning goals. We will then introduce you to the basic components of the Total Data Quality (TDQ) Framework through a series of video lectures, including Designed Data, Gathered Data, and Hybrid Data. Next, we’ll provide a high-level overview of the TDQ Framework and incorporate the perspectives of global TDQ experts in both a lecture and an interview. We’ll then wrap up the week with a short quiz about measurement and representation concepts. 9 videos5 readings1 assignment In Week 2, we’ll explore the concepts of validity, data origin, and data processing. First, we’ll define validity and discuss threats to validity for designed data and gathered data. We’ll also explore validity through an interview, a real-world application, and a case study. After taking a short quiz to test your knowledge of validity, you’ll then move to the data origin module. We’ll define data processing and explore data origin threats for designed and gathered data through a series of video lectures and case studies. The data processing module will conclude with a short quiz. Week 2 will conclude with an exploration of data processing; data processing threats for designed and gathered data; case studies; and a quiz to check your understanding of data processing. 13 videos5 readings3 assignments This week, we’ll be exploring three representation dimensions of the TDQ framework along with potential threats to data quality. First, we’ll define and discuss data access - as well as data access threats for gathered and designed data - through a series of video lectures, readings, and case studies. After you complete a quiz on data access, we’ll then define data sources and explore data threats for designed and gathered data, along with two case studies. Lastly, we’ll define data missingness along with data missingness threats for designed and gathered data, and then conclude the week with a quiz. 16 videos3 readings2 assignments We’ll be wrapping up the Total Data Quality Framework course this week. We’ll be discussing why data analysis is a critical dimension of the TDQ framework and threats to data analysis quality for designed and gathered data. You’ll also be reviewing several case studies and will be able to complete an optional tutorial using free R software. After a short quiz on data analysis threats, we’ll conclude the course with a list of references from across Course 1 and we’ll ask you to complete a course survey. 5 videos6 readings1 assignment

4 modules

Beginner level

11 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/the-total-data-quality-framework

Supply Chain Management and Analytics

15,161

4.8

Unilever Team

Unilever

['Risk Management', 'Data Analysis', 'Problem Solving', 'Presentation Layer', 'Data Visualization']

In the Supply Chain Management and Analytics course, you’ll learn the foundations of supply chain management and how the Supply Chain Analyst role has an impact on the entire supply chain including making smarter, quicker, and more efficient decisions. You’ll focus on the supply chain process, how to use analytics to identify potential opportunities in all aspects of the supply chain, and how to monitor supply chain security risks to help minimize their impact on the entire supply chain. Additionally, you’ll explore the future of supply chain and how it's impacted by security and sustainability. By the end of this course, you’ll be able to: Describe the supply chain components and their importance. Describe the Supply Chain Analyst role and its impact to the entire supply chain in making smarter, quicker and more efficient decisions. Recognize how to use analytics to identify potential opportunities on all aspects of the supply chain ensuring cost and resource efficiencies and continual growth. Use data and the current status of expenses and profitability to understand the financial impact of operations, overall spend, procurement, savings realization, and future outlook. Monitor supply chain security risks and their impact and adjust overall planning and scheduling accordingly. Describe the role of the Supply Chain Analysts to assist in meeting sustainability goals. In this module, you will learn the entire supply chain management process and the key partners involved. You will also learn the history of supply chain and big events that can have an impact on customer value and you will get to take a look into future trends and technology that may impact the future of supply chain management. 11 videos7 readings3 assignments1 discussion prompt In this module, you will learn the importance of supply chain analytics and the analyst's role to align business needs with overall inventory, forecasting, scheduling and planning strategies. 11 videos6 readings4 assignments1 discussion prompt In this module, you will explore the importance of supply chain analytics and the analyst's role to identify the impact of product throughout the network, provide insightful information to secure the in full and on-time delivery, identify risks that could affect the supply chain and assist management in making decisions and provide opportunities to adjust and align as requirements change. 17 videos7 readings5 assignments1 discussion prompt In this module, you will focus on the importance of supply chain analytics and the analyst's role to know the current status of expenses and profitability and assist in modeling and reporting on financial impact of operations, overall spend, procurement, savings realization and future outlook. You will also explore warehouse and logistics operations and the impact of demand, capacity, and planning to the supply chain. 12 videos2 readings4 assignments In this module, you will focus on the importance of physical and cybersecurity in the Supply Chain and its analytics. You will also learn the importance of monitoring Supply Chain security risks and adjust accordingly to assist management decisions. You will learn the impact of the supply chain network on sustainability goals and will focus on how to use data and analytics to create or participate in process improvement initiatives for supply chain networks. 7 videos6 readings3 assignments

5 modules

Beginner level

https://www.coursera.org/learn/supply-chain-management-and-analytics

97%

Internet of Things: Sensing and Actuation From Devices

22,597

4.5

Ganz Chockalingam

University of California San Diego

[]

Have you wondered how information from physical devices in the real world gets communicated to Smartphone processors? Do you want to make informed design decisions about sampling frequencies and bit-width requirements for various kinds of sensors? Do you want to gain expertise to affect the real world with actuators such as stepper motors, LEDs and generate notifications? In this course, you will learn to interface common sensors and actuators to the DragonBoard™ 410c hardware. You will then develop software to acquire sensory data, process the data and actuate stepper motors, LEDs, etc. for use in mobile-enabled products. Along the way, you’ll learn to apply both analog-to-digital and digital-to-analog conversion concepts. Learning Goals: After completing this course, you will be able to: 1. Estimate sampling frequency and bit-width required for different sensors. 2. Program GPIOs (general purpose input/output pins) to enable communication between the DragonBoard 410c and common sensors. 3. Write data acquisition code for sensors such as passive and active infrared (IR) sensors, microphones, cameras, GPS, accelerometers, ultrasonic sensors, etc. 4. Write applications that process sensor data and take specific actions, such as stepper motors, LED matrices for digital signage and gaming, etc. 2 videos2 readings Before jumping into the lab section of this course, we would like to offer you a short lecture series. This lecture series will compliment everything you are about to do for the remainder of the course. 7 videos1 assignment In this course, you will see a lot of new words and acronyms you might not be familiar with. If you feel comfortable with your knowledge of tech terminology, feel free to skip these lessons since they will not affect the overall integrity of the course. If you see something that you want to know a little more about, feel free to watch the video to gain insight on some basic concepts. We do expect you to know the majority of this material before going into the next module, we would recommend going through the lessons as a quick brush up. 17 videos3 readings1 assignment Hello everyone and welcome to GPIO Programming! In order for the DragonBoard™ 410c to interact with the world there has to be an interface between them. For the purpose of this project the GPIO interface will serve as a way to sense and interact with the environment. In this lesson we will talk about General Purpose Input/Output pins and why they are important to this project. We will try to define them as well as provide other resources that could help further explain their purpose. In taking a look at the low speed expansion header on the DragonBoard™ 410c we will locate and explain all other GPIO interfaces. Since only the 12 GPIO will be necessary for this course, most of this lesson will focus on them. Once a greater understanding of the GPIO is achieved we will then access them via command prompt be it through a PC host or on board OS such as Ubuntu. Finally in this lesson we will show you how to make your first program/application capable of controlling a GPIO. 33 videos5 readings1 assignment Time to build your very own amplifier! In order to interact with a wide variety of components, including many of the components that will be used throughout this course the voltage output from the DragonBoard™ 410c low speed expansion header will need to be amplified. In this lesson we will talk about a very basic voltage amplifier design. This design will be used to boost the signal voltage from the GPIO’s located on the DragonBoard™ 410c low speed expansion header. Once familiar with this basic amplifier, one can make adjustments to create personalized amplifiers geared toward specific future projects. 27 videos1 reading1 assignment We are all basically made of motors, not really, but most robots are! When working with robotics, motors among several other things are some of the most important components you will chose for a project. In this lesson we will compare a variety of different motors widely used in DIY projects, especially DIY projects centered around robotics. We will take a deeper look at the stepper motor and what they are made of. We will then talk about the H-Bridge integrated circuit chip, why it is necessary for this projects and how it is used. Lastly, this lesson will guide you through the process of building a circuit capable of running a stepper motor. Schematics and code will be provided in order to gain a greater understanding of the stepper motor, as well as to facilitate the step by step instructions found in this lesson's documentation. 16 videos2 readings1 assignment It was amazing when we turned our first LED on. What if we told you one was just the beginning! In this Module we will manipulate 8x8 LED matrices to execute a variety of custom schemes. We will program and build games, and digital displays that can be used for fun or business. The 8x8 LED matrix is just the beginning. Our code and ultimately our concepts can be applied to larger more intricate projects as you grow your IoT toolbox. 22 videos2 readings1 assignment Using sensors that work on the infrared spectrum we can send and receive information. With this knowledge we are ready to program/build a way to use this to our benefit. In this Module you will gain access to code that will allow you take tremendous steps forward in your pursuit to claim of piece of the IoT movement. We are also going talk about the infrared spectrum on a higher level to gain a better understanding of how we are able to use it for these projects. By the end of this Module, you will be able to take a household remote and control various aspects of your DragonBoard™ 410c, especially peripherals through GPIO manipulation. 14 videos3 readings1 assignment If you thought the IR remote module was fun, this will take your wireless control of the DragonBoard™ 410c to a whole new level. Here we will use multiple devices to communicate and control peripherals using Bluetooth. We will walk you through the steps we took in order to send and receive data through the Bluetooth modules on multiple devices. By the end of this module you will be able to control a variety of components (including GPIOs) on your DragonBoard™ 410c from other devices using close range Bluetooth connectivity. We are very excited to share this code with you, and we are even more excited to see all of the cool stuff you will all come up with when you are finished with this Module. 12 videos1 reading1 assignment1 peer review Its time to expand on what we did in Course 2! That being said, I am sure you all had a blast creating your server and checking the status of various components on your board. What if I told you we can use some of these ideas to also control peripherals on your board! Well that is exactly what we are going to do in this Module. Its time to mix your software knowledge with your hardware skills to create a system that can both receive and send information using HTTP! Buckle up because we are about to introduce you to a new sensor while also providing you with everything you will need to officially use the internet for controlling your things (IoT pun)! 13 videos1 reading1 assignment

10 modules

16 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/internet-of-things-sensing-actuation

94%

5G Network Fundamentals

6,836

4.7

Xavier Lagrange

Institut Mines-Télécom

['5G Services and Architecture', 'network-access security', 'New Radio (NR) interface', 'Network interconnection', 'Services Based Interfaces and Architecture (SBI/SBA)']

This MOOC presents the services and the architecture of 5G networks, the main principles of the new radio interface (NR), data flow management, security and the new Service-Based Architecture (SBA). In recent years, operators have been deploying 5G technology on commercial mobile networks. The latter is announced as a major technological breakthrough with speeds beyond Gbit/s, very low latencies and above all a distribution in many sectors of activity (industry, transport, medicine, etc.). Beyond the announcement effects, this technology relies heavily on 4G. The waveform for radio transmission is identical, the management of data flows is similar. However, 5G significantly extends the possible options both in the choice of architectures and in the radio interface configurations as well as in the security mechanisms. All this is explained in the mooc. A certificate of successful completion is awarded by Coursera to learners who succeed in obtaining a mark greater than 50%. This MOOC has received financial support from the Patrick & Lina Drahi Foundation. 13 readings 7 videos1 reading7 assignments 7 videos3 readings6 assignments 7 videos2 readings9 assignments 9 videos8 assignments 8 videos9 assignments 6 videos7 assignments

7 modules

Intermediate level

19 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/5g-network-fundamentals

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

384,543

4.8

Laurence Moroney

DeepLearning.AI

['Computer Vision', 'Tensorflow', 'Machine Learning']

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the DeepLearning.AI TensorFlow Developer Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new DeepLearning.AI TensorFlow Developer Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization. Welcome to this course on going from Basics to Mastery of TensorFlow. We're excited you're here! In Week 1, you'll get a soft introduction to what Machine Learning and Deep Learning are, and how they offer you a new programming paradigm, giving you a new set of tools to open previously unexplored scenarios. All you need to know is some very basic programming skills, and you'll pick the rest up as you go along. To get started, check out the first video, a conversation between Andrew and Laurence that sets the theme for what you'll study... 4 videos8 readings1 assignment1 programming assignment1 app item1 ungraded lab1 plugin Welcome to week 2 of the course! In week 1 you learned all about how Machine Learning and Deep Learning is a new programming paradigm. This week you’re going to take that to the next level by beginning to solve problems of computer vision with just a few lines of code! Check out this conversation between Laurence and Andrew where they discuss it and introduce you to Computer Vision! 7 videos3 readings1 assignment1 programming assignment2 ungraded labs Welcome to week 3! In week 2 you saw a basic Neural Network for Computer Vision. It did the job nicely, but it was a little naive in its approach. This week we’ll see how to make it better, as discussed by Laurence and Andrew here. 6 videos3 readings1 assignment1 programming assignment2 ungraded labs Last week you saw how to improve the results from your deep neural network using convolutions. It was a good start, but the data you used was very basic. What happens when your images are larger, or if the features aren’t always in the same place? Andrew and Laurence discuss this to prepare you for what you’ll learn this week: handling complex images! 9 videos6 readings1 assignment1 programming assignment3 ungraded labs

4 modules

Intermediate level

https://www.coursera.org/learn/introduction-tensorflow

96%

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

243,914

4.8

Tim Roughgarden

Stanford University

['Algorithms', 'Randomized Algorithm', 'Sorting Algorithm', 'Divide And Conquer Algorithms']

The primary topics in this part of the specialization are: asymptotic ("Big-oh") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts). Introduction; "big-oh" notation and asymptotic analysis. 13 videos3 readings2 assignments Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms. 11 videos2 readings2 assignments The QuickSort algorithm and its analysis; probability review. 9 videos1 reading2 assignments Linear-time selection; graphs, cuts, and the contraction algorithm. 11 videos3 readings3 assignments

4 modules

Intermediate level

https://www.coursera.org/learn/algorithms-divide-conquer

94%

Introduction to Data Analytics for Accounting Professionals

7,552

4.6

AICPA

Association of International Certified Professional Accountants

[]

This course covers the foundations of data analytics and how to conduct and apply this to projects in your organization. This includes the following: - What does it mean to have a data-driven mindset? Having the right mindset will allow you to understand the problem that needs to be solved and make or recommend appropriate data-driven decisions in the context of the organization’s strategy and technologies. - What are the key considerations when identifying, establishing, and implementing a data analytics project? This course introduces and discusses important concepts and considerations, so you are ready to be effective no matter how your organization or industry changes. This includes everything from framing the problem and defining the scope, to understanding organizational requirements and gaps, to effectively working with key stakeholders. - What is the required technical knowledge you need so that you can understand data? Whether the data you’re looking at is financial or non-financial data, structured or unstructured, you need to understand the language of data analytics so that you can communicate effectively with colleagues and add value when using data analytics in your organization. By completing this course, you will be in a better position to ask the right questions, add greater value, and improve the quality of services to your stakeholders. 7 videos2 readings4 assignments3 discussion prompts 6 videos3 assignments2 discussion prompts 6 videos3 assignments2 discussion prompts

3 modules

Beginner level

7 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/intro-to-data-analytics

Advanced Embedded Linux Development Specialization

6,793

4.2

Daniel Walkes

University of Colorado Boulder

['C Programming', 'Embedded Systems', 'Embedded Software', 'Linux', 'Kernel Programming', 'C Programming', 'Embedded Systems', 'Embedded Software', 'Linux', 'Kernel Programming']

This courses in this specialization can also be taken for academic credit as ECEA 5305 - 5307, part of CU Boulder’s Master of Science in Electrical Engineering. This specialization provides students with the fundamentals of embedded operating systems including a working understanding of how to configure and deploy a Linux based Embedded System. Students will gain expertise in software tools and development methods which can be used to create applications and build custom Linux based Embedded Devices. Applied Learning Project This course will focus heavily on designing concurrent software for embedded systems applications using the Linux operating system. At the end of this course, students will be able to... Configure, build and deploy the Linux kernel and root filesystem from source. Build their own Embedded Linux distribution using Buildroot or Yocto frameworks. Use System Programming concepts to develop application software for Embedded Devices, including File I/O, Threading, Signals, and time related POSIX APIs. Write software for inter-thread and inter-process communication using sockets and signals Debug concurrent software applications with command line GDB, Valgrind, and other software tools for debug, profile and tracing. Create a custom Linux Device Driver Understand Linux Driver related development topics, including debugging techniques, concurrency techniques, timing, memory allocation. Showcase their knowledge in a final project which demonstrates course concepts on hardware. Fundamentals of Linux System Programming, including Processes and Threads. How to build a custom Linux kernel and root filesystem for an Embedded device. How to use Buildroot to build a custom Linux Kernel and root filesystem for an Embedded device. Fundamentals of Linux kernel development. How to build a custom Linux kernel driver and deploy on an Embedded Device. How to use the Yocto project to build Embedded Device images How to structure a product using Agile Scrum concepts How to deploy a Buildroot or Yocto based project on Embedded Hardware Relevant and recent concepts related to Embedded Linux development

3 course series

Intermediate level

4 months (at 15 hours a week)

https://www.coursera.org/specializations/advanced-embedded-linux-development

Innovative Governance of Large Urban Systems

5,961

4.7

Matthias Finger

École Polytechnique Fédérale de Lausanne

[]

Learn about the three phases of the urban value chain: planning, governance and regeneration. With lecturers from all around the world and concrete case studies, this course will give you a comprehensive overview about the “Innovative Governance of Large Urban Systems”. This course has assembled some of the most relevant experiences and knowledge from our Innovative Governance of Large Urban Systems (IGLUS) Executive Master’s program, which has been offered by EPFL during the past 5 years. IGLUS consists of 2-week action-learning organized in over 10 major cities around the world, during which participants acquire an in-depth understanding of the challenges cities are facing and the ways they are addressing them. This MOOC will share this knowledge with you, thanks to some of our lecturers from various disciplines and from all around the world. During this course, you will learn about the three phases of the urban value chain, which are: planning, governance and regeneration. In particular, we will address the unique challenges of the phases and ask questions such as: how to design cities? How to govern them, especially when it comes to their institutional, financial, economic and social dimensions? And how to regenerate urban spaces? 2 videos5 readings Welcome to the first week of the MOOC! This week, we will be addressing the first phase of the urban value chain: planning. Why do we talk about urban planning? Cities are human-made environments and are therefore constructed; and construction is planned. We want to understand how urban planning plays a fundamental role to make the city humane, liveable and an accessible social space to its inhabitants. The objective of the week is therefore to understand the complexities involved in the “production of space”. 7 videos5 readings6 assignments1 plugin Welcome to the second week of the MOOC! We will address the second phase of the urban value chain! Governance. What is relevant for governance? There are first the institutions and their history, the resources available and those that are to be developed; and more recently we have observed the impact on digitalization on governance. We now want to explore how digitalization can actually improve it. The objective of the second week is to analyse the institutional, organizational and financial issues of metropolitan governance. 8 videos3 readings7 assignments1 plugin Welcome to the third week of the MOOC! We are still dealing with governance, but this week, we will be addressing the economic and social perspectives. In every city, there are economic and social inequities. Different groups of population have differentiated access to urban infrastructure and services. The objective of the week is to discuss social justice issues of governing urban infrastructure and explore ways and means to address them. 7 videos3 readings6 assignments1 plugin Welcome to the last week of the MOOC! We are now dealing with the third phase of the urban value-chain: regeneration. Why is this phase important? Every city has pockets of underused land or distressed and decaying urban areas. They weaken the city’s image, liveability and productivity. Urban regeneration is a strategy to address inner cities decline and deprivation. On the other hand, local governments may be willing to expand urban areas and create new cities. The objective of the week is to understand urban regeneration strategies and analyse the creation of new cities. 7 videos5 readings6 assignments1 plugin

5 modules

Intermediate level

https://www.coursera.org/learn/iglus

94%

Python Scripting for DevOps Specialization

6,601

4.1

Aspen Olmsted

LearnQuest

['scripting', 'Computer Programming', 'Python Programming', 'Build Automation', 'Devops']

In the first course, you will learn some of the concepts of procedural programming: user input, console output, variable declaration and assignment, decision branching and iteration. The second course will introduce you to Advanced String Operations and Dates, Modeling Classes, Development of Classes and Collections. In the third course you'll learn about Files, Inheritance and external libraries. And in the final course we will look at several automation concepts in DevOps with Python. Applied Learning Project In the Python Scripting for DevOps Specialization, the hands-on labs in each course will allow you to apply the material in the lectures in simple computer programs designed to re-enforce the material in the lesson. These labs are browser-based and do not require a local environment to be installed. Develop computer programs that utilize classes and objects to solve business and mathematical problems Develop computer programs that utilize classes and objects to solve business and mathematical problems Develop computer programs that utilize classes and objects to solve business and mathematical problems Develop computer programs that utilize classes and objects to solve business and mathematical problems

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/python-scripting-devops

Creative Thinking and Innovation

3,094

4.9

Martin Tomitsch

The University of Sydney

['Strategic Thinking', 'Creativity', 'strategy', 'Innovation', 'Design Thinking']

Creative thinking is one of the most important skills in future work environments. Whether you are working in a large organisation, creating your own startup, or looking for new opportunities in your life, in this course you will learn how to practice creative thinking to come up with innovative ideas. Everyone has the capacity to be creative. You don’t have to be in the “creative” sector to use creativity in your work and life. The course provides you with simple tips and techniques to nurture and practice your creative thinking skills. You will hear how the success of Pixar and Nobel Prizes winners is linked to creative thinking and innovation, and how industry experts from Google and IBM use these skills in their work. This course is delivered with the assistance of the team at INCUBATE - The University of Sydney’s Flagship Startup Program. If you’re part of The University of Sydney community, check out their range of free startup courses and programs here: https://incubate.org.au/ Welcome to the course! This module covers common definitions of creativity, what creativity involves and what it doesn’t involve, and how it is applied in practice. 4 videos9 readings1 assignment2 discussion prompts In this module, we will look at different definitions and types of innovation. 3 videos7 readings1 assignment1 discussion prompt In this final module, we will learn how creative thinking and innovation are connected and how we can develop a mindset to foster creativity and innovation. 6 videos8 readings1 assignment1 peer review

3 modules

Beginner level

13 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/creative-thinking-and-innovation

Solar Energy System Design

29,490

4.7

Neal Abrams

The State University of New York

[]

Solar Energy System Design builds upon the introduction to PV systems from Solar Energy Basics course, which included basic system components and functions, as well as some basic system sizing using simplifying assumptions. You should at this point have a basic understanding of electrical power and energy, be able to calculate the energy needs of a site as well as energy production potential for a PV system at a given location under optimal conditions. Much of this course will focus on incorporating on the ground conditions into energy production considerations, and how to account for these conditions in system design and equipment selection. By the end of this course you should be able to incorporate losses in irradiance due to array setups with less than optimal positioning and/or shading, and account for variations in module output due to temperature variations in your system design. Welcome to the first module of Solar Energy System Design. In this module, you will be revisiting the solar resource in a bit more depth than the Solar Energy Basics course. This will entail looking more closely at some of the properties of sunlight, and what happens to that light as it travels from the Sun until it eventually reaches the Earth's surface. 8 videos1 reading4 assignments We will now look closer at the circuits and electrical characteristics of modules and arrays. In Solar Energy Basics, you used module spec sheets to calculate power using voltage and current. In this module, you will be using those module specifications again, and looking at how the different voltage and current values included are important for determining how that module will operate under different conditions. Lastly, we will be looking at the design of both the internal circuitry of modules, and the circuitry of arrays of modules. 5 videos1 reading3 assignments You calculated photovoltaic system sizes and outputs in Solar Energy Basics based on available insolation. Those insolation values were always based on the assumption of the array being set up at optimal conditions. On-the-ground conditions can often result in variations from the optimal design for capturing all the available insolation, such as the angle of a roof and the direction it is facing being fixed, or nearby trees casting shade onto part of an array. In this module you will learn how to account for the different sources of losses in insolation, because the overall productivity of a system design can change based on the positioning of the array, temperature variations, and shading on parts of the array. These variations in productivity need to be accounted for early in the planning phase of a PV system. 7 videos2 readings6 assignments In the last content module of the course you will be working on equipment selection and system sizing. The previous modules on array siting, irradiance variability, temperature effects, shading losses, and circuit design will all come into play when you are designing a system. Additionally, you will be looking at site surveying, where those pieces of information are gathered, and permitting, where they are recorded and communicated along with the recommended system design. 5 videos2 readings4 assignments The capstone project of this course will entail applying much of what you have learned in this course. You will need to design a PV system using commercially available components and calculate it's output under site specific conditions. You will have to account for the available solar radiation and losses due to the positioning of the array as well as due to shading. You will also need to design an optimal configuration to connect the PV modules with an inverter. Finally, you will evaluate a PV system design for both accuracy and safety. 1 peer review

5 modules

Intermediate level

https://www.coursera.org/learn/solar-energy-system-design

91%

Generative AI Advance Fine-Tuning for LLMs

Enrollment number not found

Rating not found

Joseph Santarcangelo

IBM

['Reinforcement Learning', 'Proximal policy optimization (PPO)', 'Reinforcement learning', 'Direct preference optimization (DPO)', 'Hugging Face', 'Instruction-tuning']

Fine-tuning a large language model (LLM) is crucial for aligning it with specific business needs, enhancing accuracy, and optimizing its performance. In turn, this gives businesses precise, actionable insights that drive efficiency and innovation. This course gives aspiring gen AI engineers valuable fine-tuning skills employers are actively seeking. During this course, you’ll explore different approaches to fine-tuning and causal LLMs with human feedback and direct preference. You’ll look at LLMs as policies for probability distributions for generating responses and the concepts of instruction-tuning with Hugging Face. You’ll learn to calculate rewards using human feedback and reward modeling with Hugging Face. Plus, you’ll explore reinforcement learning from human feedback (RLHF), proximal policy optimization (PPO) and PPO Trainer, and optimal solutions for direct preference optimization (DPO) problems. As you learn, you’ll get valuable hands-on experience in online labs where you’ll work on reward modeling, PPO, and DPO. If you’re looking to add in-demand capabilities in fine-tuning LLMs to your resume, ENROLL TODAY and build the job-ready skills employers are looking for in just two weeks! In this module, you’ll begin by defining instruction-tuning and its process. You’ll also gain insights into loading a dataset, generating text pipelines, and training arguments. Further, you’ll delve into reward modeling, where you’ll preprocess the dataset and apply low-rank adaptation (LoRA) configuration. You’ll also learn to quantify quality responses, guide model optimization, and incorporate reward preferences. You’ll also describe reward trainer, an advanced training technique to train a model, and reward model loss using Hugging Face. The labs, in this module will allow practice on instruction-tuning and reward models. 6 videos3 readings2 assignments2 app items1 plugin In this module, you’ll describe the applications of large language models (LLMs) to generate policies and probabilities for generating responses based on the input text. You’ll also gain insights into the relationship between the policy and the language model as a function of omega to generate possible responses. Further, this module will demonstrate how to calculate rewards using human feedback incorporating reward function, train response samples, and evaluate agent’s performance. You’ll also define the scoring function for sentiment analysis using PPO with Hugging Face. You’ll also explain the PPO configuration class for specific models and learning rate for PPO training and how the PPO trainer processes the query samples to optimize the chatbot’s policies to get high-quality responses. This module delves into direct preference optimization (DPO) concepts to provide optimal solutions for the generated queries based on human preferences more directly and efficiently using Hugging Face. The labs in this module provide hands-on practice on human feedback and DPO. 10 videos5 readings3 assignments2 app items3 plugins

2 modules

Intermediate level

8 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/generative-ai-advanced-fine-tuning-for-llms

Association Rules Analysis

Enrollment number not found

Rating not found

Di Wu

University of Colorado Boulder

['Association Rule Learning', 'Outlier', 'Apriori', 'Frequent Patterns', 'FP Growth']

The "Association Rules and Outliers Analysis" course introduces students to fundamental concepts of unsupervised learning methods, focusing on association rules and outlier detection. Participants will delve into frequent patterns and association rules, gaining insights into Apriori algorithms and constraint-based association rule mining. Additionally, students will explore outlier detection methods, with a deep understanding of contextual outliers. Through interactive tutorials and practical case studies, students will gain hands-on experience in applying association rules and outlier detection techniques to diverse datasets. Course Learning Objectives: By the end of this course, students will be able to: 1. Understand the principles and significance of unsupervised learning methods, specifically association rules and outlier detection. 2. Grasp the concepts and applications of frequent patterns and association rules in discovering interesting relationships between items. 3. Explore Apriori algorithms to mine frequent itemsets efficiently and generate association rules. 4. Implement and interpret support, confidence, and lift metrics in association rule mining. 5. Comprehend the concept of constraint-based association rule mining and its role in capturing specific association patterns. 6. Analyze the significance of outlier detection in data analysis and real-world applications. 7. Apply various outlier detection methods, including statistical and distance-based approaches, to identify anomalous data points. 8. Understand contextual outliers and contextual outlier detection techniques for capturing outliers in specific contexts. 9. Apply association rules and outlier detection techniques in real-world case studies to derive meaningful insights. Throughout the course, students will actively engage in tutorials and case studies, strengthening their association rule mining and outlier detection skills and gaining practical experience in applying these techniques to diverse datasets. By achieving the learning objectives, participants will be well-equipped to excel in unsupervised learning tasks and make informed decisions using association rules and outlier detection techniques. This week provides an introduction to unsupervised learning and association rules analysis. You will explore frequent itemsets, understanding their significance in discovering patterns in transactional data. You will also explore association rules, such as support, confidence, and lift metrics as key indicators of association rule quality. 2 videos4 readings1 assignment This week we will briefly discuss association rule mining, such as closed and maxed patterns. 1 video1 assignment This week focuses on the Apriori and FP Growth algorithm, a key method for efficient frequent itemset mining. 2 videos4 readings1 assignment1 discussion prompt Throughout this week, you will explore the significance of outlier detection and its role in identifying unusual data points. 1 video2 readings1 assignment1 discussion prompt The final week focuses on a comprehensive case study where you will apply association rule mining and outlier detection techniques to solve a real-world problem. 1 reading1 assignment1 discussion prompt

5 modules

Intermediate level

22 hours to complete (3 weeks at 7 hours a week)

https://www.coursera.org/learn/association-rules-analysis

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

576,565

4.9

Andrew Ng

DeepLearning.AI

['Tensorflow', 'Deep Learning', 'hyperparameter tuning', 'Mathematical Optimization']

In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI. Discover and experiment with a variety of different initialization methods, apply L2 regularization and dropout to avoid model overfitting, then apply gradient checking to identify errors in a fraud detection model. 15 videos5 readings1 assignment3 programming assignments Develop your deep learning toolbox by adding more advanced optimizations, random minibatching, and learning rate decay scheduling to speed up your models. 11 videos3 readings1 assignment1 programming assignment Explore TensorFlow, a deep learning framework that allows you to build neural networks quickly and easily, then train a neural network on a TensorFlow dataset. 11 videos7 readings1 assignment1 programming assignment

3 modules

Intermediate level

https://www.coursera.org/learn/deep-neural-network

96%

APIs

37,771

4.4

Taught by Meta Staff

Meta

['Filtering and ordering', 'Serializers and deserializers', 'Authentication and authorization', 'Debugging', 'REST APIs']

Delve deeper into the processes and concepts behind APIs and their infrastructure. Explore the key concepts that underpin API development and the principles of representational state transfer architectural style (REST) architecture. Build basic API and REST data backbones for web apps using Django. Discover emerging API technology and practice other ways to build and work with APIs. Finally, you will test, optimize and develop documentation for an API. By the end of this course you will be able to: • Work with and build APIs • Build basic API and REST data backbones for web apps using Django • Discover emerging API technology • Test, optimize and develop documentation for an API To complete this course, you will need Django experience. Additionally, it always helps to have a can-do attitude! Get to know RESTful API development. 15 videos15 readings1 quiz4 assignments1 discussion prompt1 ungraded lab Use the Django REST framework to create APIs efficiently, then learn to serialize your database models and convert, validate and render data. 12 videos8 readings4 assignments2 ungraded labs Control access to your APIs, and put systems in place to ensure you maintain their health. 11 videos9 readings4 assignments1 ungraded lab Practice and reflect on the skills you learned in this course. 4 videos4 readings1 assignment1 peer review2 discussion prompts

4 modules

Intermediate level

https://www.coursera.org/learn/apis

92%

Google Professional Workspace Administrator Professional Certificate

41,934

4.7

Google Cloud Training

Google Cloud

[]

This specialization has been developed to help administrators master the foundations of establishing and managing Google Workspace for their organization. You will set up a new Google Workspace account, and explore provisioning options. You will learn how to manage users and become familiar with organizational structures and Google Workspace core services. You will learn how to configure these services to meet your own organizational needs. You will be introduced to the best practices to protect your users and data. You will examine user and application security and become familiar with the Single Sign On options available. You will be able to use the tools provided to identify security events and mitigate problems that may arise. You will configure email compliance and implement measures to protect your organization from spam, spoofing, phishing and malware attacks. You will also become familiar with mail routing options available. Finally, you will learn the best practices for deploying Google Workspace for your organization. IMPORTANT- Before you enroll, you should be prepared to: - Provide credit card details as part of the trial account setup. No charges will be made to your card as long as you cancel the trial before the free period expires. For details, seeAbout your Google Workspace free trialOpens in a new tab. - Purchase a new domain or use one that you already own. The domain you use IS NOT included as part of a Google Workspace trial. - Use the Chrome web browser. Applied Learning Project Learners will create a Google Workspace account and through a series of exercises will build an organizational structure and add users to the account. They will become familiar with the admin console and the features offered to them as the Google Workspace administrator. They will configure groups, and calendar resources, and understand how to implement core services such as Gmail and Calendar for different parts of the organization. They will also apply Google’s security best practices and become familiar with email management and compliance. Set up a Google Workspace account and access and navigate the admin console. Manage key properties of the Google Workspace directory. Provision users, groups and calendar resources in Google Workspace and perform common user management tasks. Create an organizational structure in Google Workspace to simplify user and service management and assign pre-defined and custom admin roles. Manage and configure Google Workspace services for an organization. Manage mobile devices in Google Workspace. Retain, search and export your organization's data using Google Vault. Navigate Google Workspace admin reports and set up administrator alerts. Configure settings such as password policies and recovery options and describe best practices for implementing 2-step verification. Understand the SSO options available and identify the differences between using Google as an Identity Provider versus a 3rd party provider. Manage the Google Workspace Marketplace for your organization to ensure only trusted applications can be installed on your devices. Use the security and alert centers to identify, triage, and take action on security and privacy issues in your organization. Protect your users from inbound phishing and harmful software (malware). Control which end user access features are available to users. Apply the various compliance features provided in Google Workspace. Use the mail routing options available to Google Workspace administrators. Describe Google's 3-phase deployment methodology, and discuss how domains, users, groups and other objects are provisioned in Google Workspace. Discuss mail routing types and explain how routing should be configured during each phase of a Google Workspace deployment. Describe migration options and coexistence challenges faced during a Google Workspace deployment. Explain the importance of change management, and identify top reasons why projects fail when change management is not considered.

5 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/professional-certificates/g-suite-administration

Supply Chain Software Tools

2,601

4.8

Unilever Team

Unilever

['Data Analysis', 'Enterprise Resource Planning (ERP)', 'Problem Solving', 'Data Optimization', 'Job Search Strategies']

In the Supply Chain Software Tools course, you’ll learn about the challenges of handling large amounts of data and how to effectively gather, analyze, and use the data. You’ll learn about the latest cutting-edge technological solutions that can streamline operations, and emerging trends (such as artificial intelligence) that allow large amounts of data to be processed and summarized instantly. Additionally, you’ll prepare for a job as a supply chain analyst by building your resume, learning how to market yourself and gain insights into the job research and application process. By the end of this module, you’ll be able to: Recognize supply chain emerging trends. Describe the software tools available for supply chain analytics such as cloud-based solutions, AI-powered projections, advanced analytics, data lakes, and database management. Explain how to access real-time insights, review inventory availability and movement, replenish schedules, and review historical data. Identify how to build accurate plans and forecasts for planning, data collection, validation, aggregation, and financial consolidation. Identify how to test assumptions with scenarios to assist with forecasting decision making. Optimize supply chain operations. Identify patterns and trends in supply chain data and streamline processes. Prepare for a job as a Supply Chain Analyst. In this module, you will learn the top emerging trends in supply chain and supply chain analytics. You will also learn about emerging trends that are making the supply chain faster, more flexible, more granular, more accurate and more efficient. 12 videos3 readings4 assignments1 discussion prompt In this module, you will learn how data analyis software and technology continues to innovate and advance to mitigate risk, help manage and analyze large amounts of data, and improve supply chain growth. 12 videos9 readings4 assignments1 peer review In this module, you will focus on the types of artificial intellegence (AI) used in Supply Chain analytics, the benefits and capabilities this intellegence offers, and how AI can enhance your analytical abilities. 8 videos2 readings4 assignments Finding and applying for jobs can be exciting and challenging. This module provides you with the tools to have a successful career search as a Supply Chain Analyst. You will learn helpful tips on how to market yourself, search for job offerings, build your resume, and apply for a position. 15 videos8 readings6 assignments

4 modules

Beginner level

15 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/supply-chain-software-tools

Linux OS - Master's

2,779

4.6

Kevin Vaccaro

Illinois Tech

[]

This course provides you the opportunity to examine the features of the Linux operating system. You will also focus on the management of the operating system. The career skills acquired in this course introduce the open-source operating system Linux and its operation and support. At the end of this course, you will be able to: - Demonstrate the use of command line tools. - Explore key features of the Linux OS. - Explore service management of the Linux OS. Software requirements: Any Linux distro Welcome to Linux OS! In this course, we will cover the topics of: Linux Terminal, Linux Tools, and Managing Linux Services. This module covers the basics of working on the Linux command-line. It explores using basic commands to perform various tasks, such as manipulating files, monitoring system activities, and managing services. 6 videos6 readings5 assignments1 discussion prompt This module explores the Linux tools. It explores Linus desktop, management tools, and account management. It also explores using GUI tools to manage Linux functions. 4 videos4 readings5 assignments This module explores managing Linux services. It addresses the installation of a Linux service, configuring it, and starting and stopping services. 4 videos5 readings5 assignments This module contains the summative course assessment that has been designed to evaluate your understanding of the course material and assess your ability to apply the knowledge you have acquired throughout the course. Be sure to review the course material thoroughly before taking the assessment. 1 assignment

4 modules

Intermediate level

https://www.coursera.org/learn/illinois-tech-linux-os

Database, Big Data, and DevOps Services in GCP

Enrollment number not found

Rating not found

LearnKartS

LearnKartS

['Cloud Spanner', 'Big Data Services', 'Cloud Firestore', 'Cloud SQL', 'Cloud BigTable']

Welcome to the Database, Big Data, and DevOps Services in Google Cloud Platform (GCP) course! This course is designed to equip learners with comprehensive knowledge and practical skills in leveraging GCP's database, big data, and DevOps services. Whether you're a developer, system administrator, or data engineer, this course will delve into the essential tools and techniques offered by GCP to manage and optimize data storage, processing, and deployment workflows. Prerequisites include familiarity with cloud computing concepts and basic understanding of GCP services. By the end of this course, you will: - Gain a deep understanding of GCP's database services, including Cloud SQL, Cloud Spanner, and Firestore, and their use cases. - Master big data processing and analytics using GCP tools such as BigQuery, Dataflow, and Dataproc. Implement effective DevOps practices on GCP, integrating tools like Cloud Build, Cloud Deployment Manager, and Kubernetes Engine. - Design resilient and scalable architectures for databases and big data solutions on GCP. - Optimize performance and cost-efficiency in managing large-scale data operations on GCP. - Develop hands-on skills through practical labs, exercises, and real-world scenarios. - Prepare for Google Cloud certifications related to database management, big data, or DevOps. This course is designed with comprehensive video lectures, hands-on demos, and practical assignments to ensure a thorough understanding and practical application of GCP's database, big data, and DevOps services. This module covers a range of topics including database services such as Cloud SQL, Cloud Spanner, Cloud Datastore, Cloud Firestore, and Cloud Bigtable. By the end, learners will understand various database types, their functionalities, and will be able to utilize different Google Cloud Platform database services effectively. 15 videos2 readings4 assignments1 discussion prompt This module covers a comprehensive range of Big Data Services in Google Cloud Platform (GCP). By the end of this module, Learners will master GCP's Big Data services, implement DevOps for app development, and apply best practices for cloud app monitoring and debugging. 26 videos1 reading8 assignments1 discussion prompt

2 modules

Intermediate level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/gcp-professional-architect-database-big-data-and-devops-services

Data Processing and Optimization with Generative AI

Enrollment number not found

Rating not found

Microsoft

Microsoft

['Data cleaning', 'Synthetic data generation', 'Feature engineering', 'Data privacy', 'Dataset optimization']

This course focuses on advanced methods for data cleaning, preparation, and optimization using AI-assisted tools. You'll learn to generate synthetic data, address privacy concerns and data limitations in your projects. Discover how to leverage AI to identify and resolve complex data quality issues, ensuring your datasets are primed for analysis. Upon completion of this course, you'll be able to: Generate synthetic data using generative AI models Implement advanced data cleaning techniques with AI assistance Optimize datasets for improved analysis efficiency Apply ethical considerations in data processing and synthetic data generation Explain the process of generating synthetic data using generative AI, identifying its applications and potential benefits in addressing data limitation 10 videos8 readings6 assignments Apply generative AI tools to identify and resolve complex data quality issues, such as outliers, inconsistencies, and errors,ensuring data integrity for accurate analysis. 6 videos7 readings6 assignments Analyze the impact of data preparation on subsequent analysis and utilize generative AI tools to automate and optimize preprocessing steps, ensuring data readiness for analysis 6 videos6 readings6 assignments Describe the key components of a well-structured dataset and the role of generative AI in enhancing data quality for analysis 7 videos7 readings6 assignments Evaluate the ethical implications of data processing and synthetic data generation, developing strategies to mitigate biases and ensure responsible and transparent data practices. 10 videos6 readings4 assignments

5 modules

Intermediate level

16 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/data-processing-and-optimization-with-generative-ai

Positive Psychology: Character, Grit and Research Methods

34,307

4.4

Claire Robertson-Kraft, Ph.D.

University of Pennsylvania

[]

Learners discover how apply to research methods to their study of Positive Psychology. In this course, we study with Dr. Angela Duckworth and Dr. Claire Robertson-Kraft. Through an exploration their work "True Grit" and interviews with researchers and practitioners, you develop a research hypothesis and learn how to understand the difference between internal and external validity. You also begin to understand and apply the strengths and weaknesses associated with different types of measurements and evaluation designs. You then interpret the results in an empirical study. Suggested prerequisites: Positive Psychology: Martin E. P. Seligman’s Visionary Science and Positive Psychology: Applications and Interventions. 9 videos4 readings1 assignment1 peer review2 discussion prompts 11 videos7 readings1 assignment1 peer review2 discussion prompts 11 videos5 readings1 assignment1 peer review2 discussion prompts 9 videos4 readings1 assignment1 peer review2 discussion prompts

4 modules

Beginner level

https://www.coursera.org/learn/positive-psychology-methods

96%

Introduction to Networking and Storage

29,116

4.7

IBM Skills Network Team

IBM

['Wireless Networks', 'Network Troubleshooting', 'Network Architecture', 'Cloud Storage', 'Networking Hardware']

Jumpstart your career in Information Technology (IT) with this beginner friendly, self-paced course! By taking this course you will enhance your base knowledge of essential skills in networking, storage, and system administration. You'll first learn about networking fundamentals which include: network types, network cables, topologies, and models. Understand how data travels across a network, and discover how protocols and standards enable all network activity. Then, you’ll learn how to set up and configure devices and cables for both wired and wireless networks. Next, you’ll learn to diagnose and troubleshoot network connectivity issues and discover how to use command line utilities and network tools in Windows settings. After that, you’ll identify different types of storage drives and discover the difference between short-term and long-term memory. You’ll learn the features of local, offsite, and cloud storage and when to use each. And you’ll investigate file, block, and object storage and work out which cloud provider solutions work best for different networking scenarios. Videos, practice activities, and virtual hands-on labs will help you develop and apply the skills you need to diagnose and repair basic networking and storage issues so you can keep users connected and their data accessible. At the end of this course, you will complete a final quiz and assignment where you will demonstrate your understanding of the course content. Computer networking plays a vital role in facilitating the communication required in almost every aspect of daily life. Activities like talking with friends and family, collaborating with coworkers, paying bills, and even completing transactions at a store often depend on some form of computer networking. Computer networking is defined as the connection of people through the use of devices and cables, and sometimes wireless signals. This week, you will learn about the basic types and shapes of networks and how they are used. You will also learn about wired connections, wireless connections, and network cables. And finally, you will learn about the advantages and disadvantages of each network type. 6 videos1 reading2 assignments2 plugins Understanding the foundations of how all networks behave is achieved by investigating the rules. That includes finding out how each rule works and observing how each rule is applied to the network and how the network is affected by that rule. This week, you will learn about networking devices and the basic instructions they follow to connect us in the ways we expect. You will understand how data is packaged electronically, which rules are used to send the data, how those rules are made, and how computers determine where to send those data packages. 6 videos1 reading2 assignments3 app items1 plugin One of the key components of communicating is understanding how to communicate. That includes knowing what enables communication, and what blocks it. This is just as true for computer networking as it is for person-to-person interactions. If you don’t understand the ways to get data from one point to another, the data will never arrive where you want it to. This week you will learn the basic steps for setting up small office or home office networks—including wired, wireless, and mobile configurations. You’ll explore Network Settings in Windows and then learn what causes network connectivity problems and how to resolve those problems. Finally, you will learn how command line utilities can be used to find network information and diagnose network issues. 6 videos1 reading2 assignments3 app items2 plugins As we’ve discussed, connection plays a vital role in communication. Another key component in communication is memory; information is not useful if it can’t be recalled. Network storage is where the memory is located in computer networking. This week you will learn about different types of network storage and basic storage troubleshooting. You’ll learn about short-term and long-term memory, and the different ways that memory can be arranged to increase capacity and efficiency. You’ll also learn about local, offsite, and cloud memory and how all these different kinds of memory enable faster and more efficient interaction between people, devices, and software. 6 videos1 reading2 assignments1 app item2 plugins 2 videos2 readings1 assignment1 peer review1 discussion prompt4 plugins

5 modules

Beginner level

https://www.coursera.org/learn/introduction-to-networking-and-storage

98%

Corporate Strategy

49,375

4.7

Joe Mahoney

University of Illinois Urbana-Champaign

['Strategic Management', 'Diversification', 'Global Strategy', 'Mergers And Acquisitions (M&A)', 'Corporate Governance']

In this course you will learn how corporations create, capture, and maintain value, going beyond the management of a single line of business. It is thus a complement to (and should typically follow) a course on Business Strategy, which focuses on developing and sustaining competitive advantage for a single business unit. Here, you will be able to better understand and learn the tools to analyze and manage decisions from a corporate-level perspective, which emphasizes the management of multiple businesses and multiple stakeholders. Examples of such decisions include vertical integration, diversification, mergers and acquisitions, strategic alliances, international expansion, global strategy, corporate governance and corporate social responsibility. You will: • Understand how corporations create and capture value as multi-business enterprises. • Learn tools and frameworks to assess choices regarding corporate scope, corporate transactions and global strategy. • Learn to analyze complex business situations and develop coherent corporate strategies. • Understand the role of corporate governance and stakeholder management in modern companies. This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and onlinemba.illinois.edu. You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course. 2 videos6 readings1 quiz1 discussion prompt This module focuses on corporate strategy with particular emphasis on the scope of the firm. Both vertical integration (vertical scope) and diversification (horizontal scope) are addressed. The module seeks to explain the relative advantages of (and alternatives to) vertical integration and diversification; and when and how they can be used to create a competitive advantage. 8 videos2 readings1 quiz This module focuses on corporate strategy with particular emphasis on transactions used by companies to change or manage the scope of the firm. Mergers and acquisitions, divestitures, and strategic alliances are the specific transactions focused on. Challenges and best practices with respect to each are discussed. 11 videos2 readings1 quiz1 peer review1 discussion prompt This module focuses on global strategy and strategies for competing around the world. It explains how companies can expand into other countries using different entry modes, and why multinational enterprises adopt different global strategies. 5 videos2 readings1 quiz This module focuses on the characteristics of public firms, management of different stakeholders, and corporate social responsibility. It also describes various mechanisms of corporate governance used to mitigate agency problems and align managerial action with stakeholder (particularly shareholder) goals. 4 videos4 readings1 quiz1 plugin

5 modules

Intermediate level

https://www.coursera.org/learn/corporate-strategy

95%

Game Development and Prototyping

Enrollment number not found

Rating not found

Christopher Main

Epic Games

['video game design', 'Video Game Design', 'Video Game Development', 'Prototyping']

In this course, you will be introduced to game development and prototyping for games. Courses 1-4 are highly recommended while Courses 5-7 create the foundational Unreal Engine project, assets and code used throughout this course. This course requires no previous experience and aimed at beginners. This course explores 6 different game modes: Stealth Survival, Platformer, Capture the Flag, Action Combat, Crafting, and Story. This course will include a pre-production phase where learners will break down the design of each mode using Obsidian. Understanding the core gameplay experience each mode is intended to design. This pre-production phase will not only outline gameplay features but also how you can reuse assets and code for quick prototyping. After pre-production, there is a module dedicated to creating each game mode. This will include game mode-specific code, design and iteration. By the end of this course you will package your project to be in a visually presentable format for your portfolio. This module is all about planning. Before a game begins, there are numerous decisions that you need to think about. It is important to seek out games that are similar in design, look for success and failure stories from developer interviews. Our industry loves to share knowledge through convention talks, dev logs on YouTube and through communities like Discord. During pre-production it is important to identify your early goals for development and work in phases. Don't try to FULLY build specific features, always focus on the core game loop. It is important to keep it in specific design targets where you can take a moment and play what you are making. From there you can adjust, iterate and further understand your project progression. 14 videos1 assignment In this module we will implement all the game mechanics we need to start prototyping each game mode. We will create specific features that we can enable or disable for our game design needs. This module is built to give you a broad understanding on how to implement mechanics and systems in the future. 107 videos1 assignment In this module it is time to put everything you've learned to the test. Everything from Course 1 all the way through to Course 8. You will be tasked to design one of each game mode: Stealth Survival, Platformer, Capture the Flag, Action Combat, Crafting and Story. Understanding game design for multiple genres is part of creating innovative new ideas. When two seemingly opposite genres get combined together, it sparks something new. Try to take a loose approach at what you create, think about the ambience for your level. Decide what game mechanics do you choose to keep, or improve, for each game mode. 8 videos1 assignment6 peer reviews6 discussion prompts Your final project for Course 8 is to design a small game experience with complete creative freedom. Try to keep it simple, think about one, two or three core gameplay mechanics to focus on. Your designs should focus on supporting those features. Perhaps one of your previous game modes sparked your interest, and you can take it to the next level by expanding it further. You can try combining different game genres that you rarely see used together. Maybe there is a game type that wasn't discussed in this course that you are really interested in prototyping. Use Obsidian to plan your designs and scope accordingly. Look for references and complete research on similar genres. Your limits are only bound to your imagination! 2 videos1 assignment1 peer review1 discussion prompt

4 modules

Beginner level

31 hours to complete (3 weeks at 10 hours a week)

https://www.coursera.org/learn/game-development-and-prototyping

Embedded Software Development with C Specialization

Enrollment number not found

3.4

EDUCBA

EDUCBA

['C Programming', 'Embedded C', 'Embedded Systems', 'C Data Types (C Programming Language)', 'C Programming', 'Embedded C', 'Embedded Systems', 'C Data Types (C Programming Language)']

This specialization provides in-depth knowledge and hands-on experience in designing and programming embedded systems using C. Learners will master key concepts such as microcontroller interfacing, real-time operating systems, and system optimization. Partnered with leading industry experts, this course prepares you for real-world applications and career advancement in embedded systems engineering. Learning Objectives: 1) Understand the fundamentals of embedded systems and their applications 2) Develop proficiency in programming embedded systems using C 3) Gain expertise in microcontroller interfacing and real-time operating systems 4) Learn techniques for system optimization and performance improvement 5) Apply embedded systems knowledge to solve real-world problems Target Audience: 1) Engineering students and professionals looking to specialize in embedded systems 2) Software developers seeking to expand their skills into embedded programming 3) Hobbyists and makers interested in creating sophisticated embedded projects 4) Anyone with a passion for learning about embedded systems and their applications Prerequisites: 1) Basic knowledge of programming, preferably in C or C++ 2) Understanding of fundamental electronics concepts 3) Familiarity with microcontrollers is beneficial but not mandatory Applied Learning Project The included projects involve designing and programming embedded systems to solve real-world problems, such as developing a microcontroller-based sensor network and implementing a real-time operating system for a home automation system. Learners will apply their skills to create functional prototypes, demonstrating their ability to tackle authentic industry challenges. Understand Embedded Systems principles, architectures, and essential devices Master C programming essentials include operators, storage classes, and flow control structures Explore advanced C concepts crucial for embedded systems, such as functions, arrays, pointers, and string manipulation techniques Mastery of STM32CubeIDE and C programming fundamentals. Effective utilization of microcontrollers, debugging, and analysis techniques for robust embedded systems development. Explore foundational steps in embedded systems development, including build processes and memory management. Master data manipulation, input/output handling, and floating-point data types in C programming Implement advanced bitwise operations and control LEDs using embedded C and STM32 peripherals. Develop proficiency in loop constructs and efficient code iteration for precise embedded system control Master the fundamentals and advanced features of ARM Cortex (STM32) microcontrollers. Design, implement, and debug efficient embedded systems using professional-grade tools and techniques.

4 course series

Intermediate level

5 months (at 2 hours a week)

https://www.coursera.org/specializations/embedded-software-development-with-c

Memoir and Personal Essay: Write About Yourself Specialization

16,787

4.4

Amy Bloom

Wesleyan University

['Essay Writing', 'Creativity', 'Non-fiction Writing', 'Storytelling', 'Writing', 'Essay Writing', 'Creativity', 'Non-fiction Writing', 'Storytelling', 'Writing']

How To Write About Yourself...so that someone else wants to read it! This is the heart of this Coursera specialization in Memoir and Personal Essay. Masters of both genres share tips, prompts, exercises, readings and challenges to help every writer imagine, construct and write compelling pieces of non-fiction's most popular form: the personal narrative. Applied Learning Project Through 16 writing assignments across the four courses, and from reading the work of others, learners will develop a toolset to put pen to paper (or keys to screen) and write the story of their life. You will collect a portfolio of work that you can use as components of your memoir or essay. The blank page can be the most daunting obstacle in writing. In this course, aspiring writers will assemble a “starter kit” for approaching the blank page by developing constructive ways to think about the writing process as a whole. While subsequent courses in this series will focus on the mechanics of good writing, this course offers ways to think about the writer’s relationship to her material, and ultimately develop a writing style that is uniquely her own. If you have always wanted to tell your own story—in a memoir, first-person essay, or any other form of autobiographical non-fiction—but felt you lacked the tools or the framework, this is the class for you. We will learn how successful first-person writing is structured to offer the reader a sense of propulsive motion, and is guided by a narrator who is deliberately crafted. We will explore the ways in which language can be used to create tone, so that the emotional freight of your words is as potent as the storytelling. And crucially, we will consider the writer's responsibility to the reader: the importance of being a guide who includes the reader in the sensory, emotional, and intellectual experience you mean to share through your writing. This class is the chance to create your personal essay or extend into a full memoir -- from planning and structure to bold narrative brushstrokes to the layering of significant detail. You will develop the opportunity to find your voice and see it come alive, amplified and improved, on the page. This is the chance to tell your story in a way that invites readers in; your story, written to be read. The memoir and personal essay are two of the best-selling and most universally acclaimed genres in the world of modern creative writing. Welcome to your story. In this course, creative nonfiction writers will explore traditional storytelling methods, especially those which overlap between fiction and memoir. By looking at examples from a wide range of genres, including film, song, painting—even the theme music for Jaws!—we’ll practice exercising the creative muscle that sees ourselves as characters and the experiences we’ve had as tales. We’ll focus on critical elements, like how to begin a story, what makes for worthy content, the essential use of detail, the strengths and limits of dialogue, the power of the white space. The ultimate goal is for us to become aware of an “audience” when we write, so that the documentation of our lives will begin to resemble a “performance” crafted onto paper rather than a private entry in a journal.

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/memoir-personal-essay

Building No-code Apps using Amazon Honeycode

Enrollment number not found

Rating not found

Edureka

Edureka

['Capacity to construct data-driven applications', 'Data management & modeling', 'User interface configuration with the builder', 'Task automation & collaboration using automations']

Welcome to the Building No-code Apps using Amazon Honeycode course, where you'll embark on a journey to acquire practical expertise in no-code app development and harness the power of Amazon Web Services (AWS) for efficient data management. Throughout this short course, you'll explore the industry-specific applications of Amazon Honeycode and delve into various features and functionalities. By the end of this course, you will be able to: - Describe the characteristics and components of the Honeycode interface. - Design user interfaces, layouts, and interactive elements for applications. - Implement automation logic without coding using Honeycode Builder. - Create web and mobile applications using the no-code visual builder - Collaborate with team members, manage versions, and handle conflicts. This short course is designed for a diverse audience: freshers, database administrators, project managers, business analysts, and IT professionals who are looking to enhance their AWS database skills through Amazon Honeycode. Prior experience with database management or spreadsheet applications can be beneficial when working with Amazon Honeycode. Embark on an educational voyage to master Amazon Honeycode and enhance your skills in creating efficient applications and workflows within the AWS ecosystem. This module is designed to assist learners in creating custom applications without the need for coding. Throughout this course, learners will acquire the expertise to develop interactive, data-driven applications suitable for diverse business scenarios. 29 videos6 readings6 assignments5 discussion prompts

1 module

Beginner level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/building-no-code-apps-using-amazon-honeycode

Practical Linux Command Line 2.0

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['Bash scripting', 'terminal basics', 'Linux process management', 'Ubuntu VirtualBox', 'bash scripting', 'SSH remote access']

This course begins by introducing you to the Linux environment, guiding you through installation on VirtualBox, and getting comfortable with the terminal interface. You'll start by learning basic file navigation commands like pwd, ls, and cd to explore the Linux file system. As you progress, you'll dive deeper into the practical aspects of file management, covering everything from creating and managing files and directories to editing text files directly from the terminal using Nano and Echo. Next, you'll explore more advanced features of the Linux command line, such as managing users, permissions, and ownership with commands like chmod, chown, and sudo. You'll also discover how to install and update software using package managers like apt and yum. By the end, the course will have you optimizing your workflow through command-line shortcuts, piping, and handling multiple terminal sessions. You'll also learn about monitoring system processes, automating tasks with Cron, and connecting remotely with SSH, preparing you for real-world Linux tasks. By the end of the course, you'll have the skills necessary to confidently work in any Linux environment, boosting your productivity and opening doors to advanced Linux roles. Whether you’re a beginner or looking to refine your command-line expertise, this course equips you with the tools and knowledge to perform complex operations and automate repetitive tasks. This course is perfect for tech enthusiasts, developers, system administrators, and anyone interested in mastering the Linux command line. Basic computer literacy is recommended, but no prior Linux experience is necessary. In this module, we will introduce the course, outline the learning journey, and guide you through the essential steps to set up your Linux environment. You'll start by installing Ubuntu on VirtualBox and familiarizing yourself with the terminal interface. These foundational skills will set you up for success in the upcoming modules. 4 videos1 reading In this module, we will dive into the Linux file system and explore essential commands for navigating within it. You will learn how to move between directories, view hidden files, and leverage time-saving shortcuts like autocompletion and command history. Understanding the structure of the Linux file system, including the home directory and path types, is key to mastering file management. 6 videos In this module, we will focus on managing files and directories within the Linux environment. You will learn how to create, move, and remove files and folders, as well as explore the contents of files directly from the terminal. Additionally, you'll practice writing text into files using commands like echo, further developing your ability to work efficiently in Linux. 4 videos1 assignment In this module, we will cover file editing techniques using the terminal-based Nano editor and explore how to configure it for personalized usage. You will also learn how to create and run Bash scripts, a crucial skill for automating tasks in Linux. Finally, we’ll provide an introduction to Vim, another powerful terminal-based text editor. 4 videos In this module, we will explore how user accounts and permissions work in Linux. You'll learn about the actions you can and cannot perform as a regular user and how to elevate privileges using sudo. We will also cover file ownership and permission structures, providing you with the knowledge to modify owners and adjust access levels with commands like chown and chmod. 5 videos In this module, we will guide you through the process of installing, removing, and updating software in Linux. You’ll learn how to use popular package managers such as apt, yum, and brew, and explore how to keep your system updated. Additionally, we'll introduce Snap, a powerful tool for managing software on Ubuntu. 3 videos1 assignment In this module, we will focus on enhancing your productivity in the Linux command line. You will learn how to quickly find files, search for patterns within files, and use pipes to link commands together for more efficient processing. We'll also cover essential terminal shortcuts and how to work with multiple terminals to manage tasks more effectively. 5 videos In this module, we will explore how to manage and monitor system processes and resources in Linux. You will learn how to find and kill processes that may be consuming system resources unnecessarily. Additionally, you will gain the ability to monitor disk space, CPU usage, and power consumption to ensure your system is running efficiently. 2 videos1 assignment In this module, we will cover essential network commands to help you manage and troubleshoot network connectivity in Linux. You'll also learn how to securely connect to your Linux system remotely using SSH. Lastly, we will provide a brief introduction to Embedded Linux, highlighting its importance and how the command line is used within this context. 3 videos In this module, we will focus on automating tasks in Linux to improve efficiency. You'll learn how to schedule tasks using Cron jobs and configure services to start automatically during boot with Systemd. Additionally, we will cover how to modify existing Cron jobs for better task management. 2 videos1 assignment In this final module, we will summarize the key takeaways from the course and provide guidance on what steps to take next. You'll receive advice on continuing your Linux education, exploring advanced topics, and leveraging your newfound skills to advance your career in system administration or related fields. 1 video1 assignment

11 modules

Beginner level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/packt-practical-linux-command-line-2-0-4gmnv

Housing Justice: A View from Indian Cities

2,009

4.5

Swastik Harish

Indian Institute for Human Settlements

[]

This course will introduce learners to different approaches to thinking about housing justice, bringing together material, ecological, social and spatial approaches to thinking about housing. Rooting itself in Indian cities, but speaking more broadly to struggles for housing justice more globally, it will offer a diagnosis of what housing justice looks like as well as the modes and practices that can move us towards it ranging from activism and direct action to public policy and participatory governance. This course introduces learners to different approaches to thinking about housing justice, bringing together material, ecological, social and spatial approaches to thinking about housing. Rooting itself in Indian cities, but speaking more broadly to struggles for housing justice more globally, it will offer a diagnosis of what housing justice looks like as well as the modes and practices that can move us towards it ranging from activism and direct action to public policy and participatory governance. Listen to the introductory video to get a sense of how its organised and our three key learning elements: lecture videos, interactive dashboards with additional resources materials, and then exercises to aid understanding. Then, take a second to introduce yourself in the Discussion Forum labelled 'Introductions'. In case you have any questions for us, use the Discussion Prompt on Course Admin FAQs! And finally, we have a Pre-course Survey for you through which we would like understand more about your motivations and objectives. Do spend a few minutes on this survey questionnaire to help us improve the course as we go along! 1 video2 readings2 discussion prompts1 plugin This module starts us off by unpacking our two key terms: housing, and housing justice. This course makes a fundamental move to say that housing is more than just houses. Housing is fundamentally economic, material, social, spatial and political at the same time. So start with the first video on the Introduction to Housing, spend time with the Interactive Dashboard and take Quiz 1 that will help you consolidate your understanding of this frame. Then move to the second video for the week - What is Housing Justice? Finish Quiz 2 after you hear the lecture. Then, spend some time on the discussion forum to debate these approaches to thinking about housing justice. Think about your own approach to these issues, as well as the frameworks we have offered you. There can be no one understanding of housing justice, so this is the week to debate and discuss! 2 videos1 reading2 assignments1 discussion prompt1 plugin This module offers a framework to think about just, or good, housing. Such housing must be affordable, adequate, and viable. We describe what these words mean, and then offer case studies from across the world on attempts to make housing affordable, adequate and viable. The Module is structured a bit differently this week. Hear the video (What makes housing inadequate?) first. It will describe the logics of the case studies we have presented in our Interactive Dashboard. Then head over to the dashboard, and click on the highlighted countries to download case studies of housing programmes, practices, and policies from all over the world. Finally, take the quick Quiz 3 to consolidate your learnings. 1 video1 reading1 assignment1 plugin Ownership is not necessarily the only path to resolving housing inequity. This module will introduce you to rental housing and other tenure systems, while elaborating on the well-known and lesser-known aspects of the rental housing market and how it is supposed to aid in the delivery of housing justice. Watch the videos on Rental Housing with respect to its three core stakeholders: the tenants, landlords and the city. Then spend some time crystallising your understanding of these systems and relating them with your own experiences and environments through the discussion thread. Finally, take the graded quiz 4 to consolidate your learning from this module. 4 videos1 assignment1 discussion prompt There can be no talk of housing justice without organising and struggle. This module reminds us that modes of change towards housing justice are never just technical solutions or changes in policy but as much the coming together of people and movements to fight inequalities. We have a video heavy week this time to hear from activists and organisers themselves as part of our faculty. Start from the Introduction video that introduces the activists. Then move on to each of the four. Reflect on these first-person accounts from organisers who have collectivised and organised to address the question of housing justice for themselves and others in the absence of support from other stakeholders in the housing ecosystem. What can we learn from their practices about ways to organise for housing justice in our own cities? 5 videos1 assignment1 discussion prompt In the first four modules, we have discussed housing justice and various ways to address it from different lenses. This module, with an emphasis on the public sector and other stakeholders, will provide an overview on the modes of action across laws, policies, programmes and projects to understand where we can intervene and start working on housing justice. Watch the videos to gain an overview of the scale of action required to solving the housing justice question and how the approach can be broken down in terms of law, policies, programmes and projects. Watch the three lectures on the different scales and modes of action and build on the themes through participation in the discussion forum. The final graded quiz rounds off your course. 4 videos1 assignment1 discussion prompt This is the final module of the course. This module comprises of a final assignment through which you can demonstrate your understanding of the various frameworks, concepts and constructs on housing, your analyses of housing justice relative to your own experiences and the broad landscape encompassing different stakeholders. Through this assignment, you will integrate your composite learning from the course and try to form a cogent narrative that outlines your views and ideas on housing justice and possibly access a gateway to further build on your learning from the course. The assignment will be peer-graded, which means you will get to review and grade your fellow learners and vice versa. This will also provide an opportunity for you to explore different themes and perspectives emanating from the global learner audience and to exchange and collaborate with each other. 1 peer review1 discussion prompt1 plugin

7 modules

Beginner level

17 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/housing-justice-a-view-from-indian-cities

Politics and Ethics of Data Analytics in the Public Sector

Enrollment number not found

4.9

Christopher Brooks

University of Michigan

['Public Policy', 'Data Analysis', 'Politics and ethics', 'case study']

Deepen your understanding of the power and politics of data in the public sector, including how values — in addition to data and evidence — are always part of public sector decision-making. In this course, you will explore common ethical challenges associated with data, data analytics, and randomized controlled trials in the public sector. You will also navigate and understand the ethical issues related to data systems and data analysis by understanding frameworks, codes of ethics, and professional guidelines. Using two technical case studies, you will understand common ethical issues, including participation bias in populations and how slicing analysis is used to identify bias in predictive machine learning models. This course also serves as a capstone experience for the Data Analytics in the Public Sector with R Specialization, where you will conduct an applied policy options analysis using authentic data from a real-world case study. In this capstone exercise, you will review data as part of policy options analysis, create a visualization of the results, and make a recommendation. All coursework is completed in RStudio in Coursera without the need to install additional software. This is the fourth and final course within the Data Analytics in the Public Sector with R Specialization. The series is ideal for current or early-career professionals working in the public sector looking to gain skills in analyzing public data effectively. It is also ideal for current data analytics professionals or students looking to enter the public sector. Welcome to the fourth and the last course in the Data Analytics in the Public Sector with R Certificate— Politics and Ethics of Data Analytics in the Public Sector. This week, you will begin to develop a competent understanding of politics and ethical challenges in data analytics. 7 videos5 readings1 assignment2 discussion prompts1 ungraded lab Welcome to Week 2! This week you will dive deeper into the ethical challenges in the profession of data analyst and learn how to respond to these ethical challenges. You will get learn through authentic examples and case studies. 12 videos1 reading1 assignment3 discussion prompts1 ungraded lab Welcome to Week 3, the last week of this course! This week you will get to apply all that you learned in this course and the Data Analytics in the Public Sector with R Certificate through a capstone project. You will work with an authentic case study of “Providing Pensions for the Poor in Mexico.” 4 videos4 readings1 assignment1 app item

3 modules

Intermediate level

14 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/politics-and-ethics-of-data-analytics-in-the-public-sector

Fundamentals of Good Clinical Practice: Prep and Personnel

3,892

4.7

Novartis Learning

Novartis

['Drug Development', 'Regulatory frameworks', 'Good Clinical Practices (GCP)', 'Clinical trial basics', 'Clinical trial diversity']

Welcome to 'Fundamentals of Good Clinical Practice: Prep and Personnel'! This course is designed to introduce you to preparing for a clinical trial. This is Course Two in the Clinical Trial Teams series - the first course 'Introduction to Good Clinical Practice' provides background on what clinical trials are as well as the basic principles and practices of GCP. If you are new to the world of clinical research, we suggest starting your journey with Course One. In Course Two, we turn our attention to the conduct of clinical trials, exploring in detail the role of the Investigator and site staff throughout a study. Whether you are new to the field or seeking to refresh your knowledge, this course will equip you with the necessary understanding to begin to navigate the complex world of clinical research. The course is divided into several modules, each covering specific stages of a clinical trial. The modules include a variety of videos, a fictional case study and interactive quizzes to reinforce your learning. We are excited to embark on this learning journey with you as we delve into the world of Good Clinical Practice. Enroll now and start building a strong foundation in the conduct of clinical research! In Week One, you'll learn about the preparations and qualification criteria required for an Investigator and their site to participate in a Clinical Trial, and learn about Site Selection Visits. 3 videos1 reading1 assignment In Week Two, you'll continue to learn about the preparations and qualification criteria required for an Investigator and their site to participate in a Clinical Trial. Topics include essential documents, the role of the Institutional Review Board / Independent Ethics Committee (IRB / IEC), and source data and ALCOA+. 9 videos2 readings2 assignments In Week Three, you'll learn about the role and responsibilities of a Primary Investigator, including practical advice and guidance on how to succeed in the role. You'll also learn about how site staff support a clinical trial. 5 videos2 readings3 assignments

3 modules

Beginner level

2 hours to complete

https://www.coursera.org/learn/fundamentals-of-gcp-prep-staffing

Networking and Security Architecture with VMware NSX

53,261

4.7

Chris McCain

VMware

[]

This 8 week online course equips learners with the basics of network virtualization with VMware NSX. To get the most of this course, you should have familiarity with generic IT concepts of routing, switching, firewalling, disaster recovery, business continuity, cloud and security. At the end of the course, you will be able to: • Understand network virtualization basics • Describe NSX business value and use cases • Explain how NSX is different from traditional networking • Summarize networking and security solution architecture with VMware NSX around these key areas: + Micro-segmentation + Automation with OpenStack + Automation with VMware vRealize Automation + Disaster Recovery and Business Continuity + Operational Transformation • Demonstrate understanding through hands-on experience • Develop a learning plan for network virtualization certification If you are new to network virtualization, download our Network Virtualization for Dummies guide. http://learn.vmware.com/36350_NSX_ITAutomation_Reg?src=af_5acfd24cebb90&cid=70134000001YR9b All Hands on Labs referenced in this course are OPTIONAL and available for FREE. Direct links to free labs can be found on the Resources Tab or you can access our full library at https://labs.hol.vmware.com/HOL/catalogs/catalog/877 We'll introduce you to the course and VMware NSX, as well as provide a brief history of how VMware has evolved into the company that it is today. 3 videos1 reading1 assignment This module explains the architectural components that make up VMware NSX. These components are the foundation for understanding how VMware NSX is deployed into a data center. 1 video1 reading1 assignment1 peer review This module dives into VMware NSX as a security platform that provides a defensive in depth solution. The content compares traditional security solutions with the in-kernel firewall provided by VMware NSX. In addition, this module covers application behavior monitoring and the ecosystem of partners that integrate with VMware NSX to provide a comprehensive security solution. 10 videos1 reading1 assignment2 peer reviews This module provides details on using VMware NSX to create highly available data center designs. 5 videos2 peer reviews The content covers stretched clusters and disaster recovery designs using VMware NSX. In addition, this module takes a look at how VMware Cloud on Amazon Web Services allows public cloud solutions to be managed the same way an on-prem data center is managed. 5 videos1 reading1 assignment1 peer review The Operations modules explain the evolution of people, process and tooling. 6 videos2 peer reviews The content covers process automation with VMware NSX using common cloud management platforms like OpenStack and vRealize Automation. In addition the content describes the need for new tooling that provides converged and correlated data of new data center technologies. Finally, the module explains the importance a growth mindset and the evolution of IT organizations away from rigid, well-defined silos to a more collaborative, cross-functional workforce. 12 videos1 reading1 assignment 2 videos2 readings

8 modules

Intermediate level

https://www.coursera.org/learn/networking-security-architecture-vmware-nsx

96%

Deploy containers by using Azure Kubernetes Service

Enrollment number not found

Rating not found

Microsoft

Microsoft

['Clusters', 'container', 'CLI', 'Nodes', 'Pods', 'Container']

Upon completion of this course, yoy will be adequately prepared to take Microsoft's Deploy containers by using Azure Kubernetes Service Applied Skill assessment. This course covers all necessary content and provides essential practice to boost your confidence and ensure success in the final assessment. Azure Kubernetes Service (AKS) isn't just a tool; it’s the strategic catalyst for orchestrating containers. Imagine it as the keystone that seamlessly aligns microservices, scales with precision, and ensures high availability. This short course will provide hands-on experience creating, deploying, pushing, and deleting the most commonly used functionalities of Azure Kubernetes Services (AKS). deploying these core Azure networking services. Through hands-on learning, you'll gain the expertise needed to navigate AKS with confidence for your real-world environment. By the end of this 2-hour long course, you will be able to: • Prepare the Microsoft Azure Lab Environment • Create an Azure Kubernetes Service (AKS) Cluster and Nodes • Deploy Pods and Build a Docker Image • Build an Azure Kubernetes Container (AKS) and Push Images to the Registry This course is unique because the customized hands-on learning experiences are tailored to the learner for success in using Azure Kubernetes Services and introduce some useful tools to gain the possible results. To be successful in this short course and the labs in it, you should have: Expertise navigating the Azure Portal to create resources. Familiarity with security concepts like identity management, permissions, and encryption. Understand Networking terminologies such as Virtual Networks, IP Addressing, Firewalls and DNS. A basic knowledge of Kubernetes and Azure Kubernetes Services concepts Note: To perform the labs, you will need an active Azure subscription. After completing this short course, you will be able to deploy containers using orchestration, manage clusters in Azure Kubernetes Services, and scale Azure Kubernetes Services clusters. Additionally, you will be able to deploy an Azure Kubernetes application into an Azure Kubernetes Service cluster. 1 reading In this lesson, you will prepare your own lab environment by obtaining a free trial to work with Microsoft Azure. We will discuss the options that come with the free trial and remember to never practice labs from this or any other Microsoft course in the real world environment. After creating a login and password, utilize them to log into the Azure portal. Once this has been completed, we are ready to jump into this short course. 2 videos2 readings1 assignment1 ungraded lab In this lesson, you will navigate through the Azure Portal to create an Azure Kubernetes Service (AKS) container and configure its properties and options to hold system images. You will also start the process of deploying an AKS cluster. The lesson will conclude with setting properties for the contained nodes. 2 videos1 reading1 assignment1 ungraded lab In this lesson, you will explore the full power of deploying pods, using YAML files, and building Docker images—key skills for working with Azure Kubernetes Services. You will download a YAML file and learn how it guides the deployment of images, gaining hands-on experience in these essential processes. 1 video1 reading1 assignment1 ungraded lab In this lesson, you will learn the final step in working with Azure Kubernetes Services in Azure. This crucial step can be performed by both developers and administrators. It is important to understand and practice these concepts in the labs, so you can develop standards and best practices for your own real-world environment. 1 video2 readings2 assignments1 ungraded lab

5 modules

Intermediate level

2 hours to complete

https://www.coursera.org/learn/deploy-containers-with-azure-kubernetes-service

Tricky English Grammar

110,029

4.8

Tamy Chapman

University of California, Irvine

[]

English is a difficult language to learn because of its many obscure grammatical rules, which are fairly easy to mess up--even for native speakers. While it’s easy for non-native speakers to get overwhelmed by confusing grammar rules, in this course, we'll provide you with tips that will help you understand the rules more easily and give you lots of practice with the tricky grammar of everyday English. Please note that the free version of this class gives you access to all of the instructional videos and handouts. The peer feedback and quizzes are only available in the paid version. This is the third course in the Learn English: Intermediate Grammar specialization. Learning English can be tricky, and in this class you'll focus on some of those tricky issues. You'll get clear explanations about the difficult grammar points and practice in using them correctly. 2 videos1 reading1 peer review This week, you'll learn about tricky nouns, articles, and quantifiers. When should you put "a" or "the" in front of a noun? When should you put nothing in front of the noun? In this module, you'll find the answers to these questions, and you'll get lots of practice to help you use nouns and articles correctly. 12 videos13 readings4 assignments1 peer review This week will not be as intense as last week was, but you will still have the chance to learn about some tricky grammar. First, you'll learn about using gerunds and infinitives correctly. Then you'll learn about making requests and asking for permission, something that English learners often misuse. 4 videos4 readings3 assignments1 peer review You've learned about some tricky grammar, but there are other things that make English hard to learn. This week, you'll learn about some word forms that cause confusion. You'll soon understand the difference between some pairs of words that always seem tricky. 7 videos8 readings5 assignments1 peer review There are a few more tricky English points that we want you to learn. In the final week, you will learn about phrasal verbs and collocations. These are two big grammar points that often give language learners difficulty, but you will get lots of practice with them. Finally, you’ll have a review lesson of all of the tricky English grammar that you have learned in this course. 6 videos7 readings4 assignments1 peer review

5 modules

25 hours to complete (3 weeks at 8 hours a week)

https://www.coursera.org/learn/tricky-english-grammar

98%

Artificial Intelligence

Enrollment number not found

Rating not found

Siva Balasubramanian

Illinois Tech

[]

Designed as an introduction to the evolving area of AI, this course emphasizes potential business applications and related managerial insights. Artificial Intelligence (AI) is the science behind systems that can program themselves to classify, predict, and offer solutions based on structured and unstructured data. For millennia, humans have pondered the idea of building intelligent machines. Ever since, AI has had highs and lows, demonstrated successes and unfulfilled potential. Today, AI is empowering people and changing our world. Netflix recommends movies, Amazon recommends popular products, and several EV manufacturers are working to perfect self-driving cars that can navigate safely around other vehicles without human assistance. More recently, Generative AI (e.g., OpenAI’s GPT-4, and variants of this concept such as Google’s Gemini, Anthropic’s Claude or Microsoft’s Copilot) has revolutionized and energized imaginations and expectations with multi-modal capabilities. Businesses are scrambling to suitably adjust AI strategies across multiple domains and industries. This course focuses on how AI systems understand, reason, learn and interact; learn from industry’s experience on several AI use cases. It seeks to help students develop a deeper understanding of machine learning (ML) techniques and the algorithms that power those systems and propose solutions to real-world scenarios leveraging AI methodologies. Students will also learn the estimated size and scope of the AI market, its growth rate, expected contribution to productivity metrics in business operations. Welcome to AI in Business! Designed as an introduction to the evolving area of AI, this course emphasizes potential business applications and related managerial insights. Artificial Intelligence (AI) is the science behind systems that can program themselves to classify, predict, and offer solutions based on structured and unstructured data. For millennia, humans have pondered the idea of building intelligent machines. Ever since, AI has had highs and lows, demonstrated successes and unfulfilled potential. Today, AI is empowering people and changing our world. Netflix recommends movies, Amazon recommends popular products, and several EV manufacturers are working to perfect self-driving cars that can navigate safely around other vehicles without human assistance. More recently, Generative AI (e.g., OpenAI’s GPT-4, and variants of this concept such as Google’s Gemini, Anthropic’s Claude or Microsoft’s Copilot) has revolutionized and energized imaginations and expectations with multi-modal capabilities. Businesses are scrambling to suitably adjust AI strategies across multiple domains and industries. This course focuses on how AI systems understand, reason, learn and interact; learn from industry’s experience on several AI use cases. It seeks to help students develop a deeper understanding of machine learning (ML) techniques and the algorithms that power those systems, and propose solutions to real world scenarios leveraging AI methodologies. Students will also learn the estimated size and scope of the AI market, its growth rate, expected contribution to productivity metrics in business operations. In Module 1, in addition to introducing AI, this module familiarizes students with (a) key aspects of AI’s evolutionary history and the related advances in semiconductor computer chips, (b) current global AI market size, expected compounded annual growth rate (CAGR) and market forecasts until 2030 and beyond, and (c) corresponding trends that contributed to AI’s impressive growth potential. 12 videos5 readings4 assignments1 discussion prompt In this module, students learn several components embedded within the broad AI domain; they will also understand (a) several types of machine learning (supervised, unsupervised, reinforcement and deep learning); (b) types of Artificial Neural Networks; (c) System1/System 2 thinking, legal issues in AI/ML and problems in aligning machine and human goals in AI/ML applications. 11 videos4 readings4 assignments In this module, students will learn about contributions to AI progress from (a) fully-evolved and midstream (and still evolving) technologies; (b) midstream and still-evolving technologies, as well as emergent technologies, and (c) insights from Kurzweil’s Law of Accelerating Returns to learn how the creative integration of multiple technologies over time accelerates AI progress. 10 videos5 readings4 assignments The focus of this module is on the abilities of AI that are assessed in the context of what we know about human abilities; students will learn about human-AI collaboration, understand key advantages and disadvantages associated with AI. Additionally, students will be exposed to a variety of AI/ML use cases (or application examples in the business context); this will help increase their familiarity with AI/ML deployment across several industries, and companies within an industry. 9 videos4 readings4 assignments In this module, we assess AI’s impact from two opposing perspectives: first, students will learn the very impressive productivity gains expected from AI for the foreseeable future along with the corresponding rise in AI investments/infrastructure and GDP growth; second, predictions of dramatic job losses from AI/ML adoption that unfortunately presents a sobering view. Finally, students will assess the challenges associated with modeling human judgment with machine learning, explore the implications of automation and the AI Chasm. 11 videos6 readings4 assignments This module focuses on comparisons and contrasts at multiple levels; for example, at the company level, focusing on company-specific AI strategies may generate insights on successful approaches to leverage the company’s strengths. Similarly, focusing on nations sensitizes students to regional/cultural/political forces shaping the adoption and deployment of AI; an industry specific focus may generate many use cases that students can learn from; and finally, focusing on specific business functions within a company may be an thoughtful exercise to tightly integrate AI deployment within a company across its business functions. The discussion in this module emphasizes many AI use cases. 11 videos4 readings4 assignments This module focuses on areas within the AI industry that are growing fast because of their very promising potential for aiding new discoveries and new use cases. Students will learn about the history of Generative AI, market size and growth rate, exciting avenues for potential innovations in Generative AI applications. In addition, students will explore the concept of Explainable AI as a potential tool to overcome inherent limitations underlying AI/ML predictions and recommendations i.e., the lack of explanations or rationales underlying those predictions and recommendations. 7 videos4 readings4 assignments Students will understand key elements of two important concepts in AI practice: AI Ethics and Responsible AI. Students will be able to describe the basics of AI Ethics and Anthropomorphism; they will learn about moral/ethical dilemmas or bias issues that may confront AI systems or devices; within the broad realm of Responsible AI, students will develop an understanding of fairness, transparency, accountability and safety concepts. Finally, given the emergent and current regulatory framework for AI at the global level, students will learn about responsible AI practices in the context of managing Data, Privacy and Compliance issues. 8 videos4 readings4 assignments This module contains the summative course assessment that has been designed to evaluate your understanding of the course material and assess your ability to apply the knowledge you have acquired throughout the course. 1 assignment

9 modules

Beginner level

58 hours to complete (3 weeks at 19 hours a week)

https://www.coursera.org/learn/illinois-tech-artificial-intelligence

Algebra: Elementary to Advanced - Functions & Applications

10,012

4.8

Joseph W. Cutrone, PhD

Johns Hopkins University

[]

After completing this course, students will learn how to successfully apply functions to model different data and real world occurrences. This course reviews the concept of a function and then provide multiple examples of common and uncommon types of functions used in a variety of disciplines. Formulas, domains, ranges, graphs, intercepts, and fundamental behavior are all analyzed using both algebraic and analytic techniques. From this core set of functions, new functions are created by arithmetic operations and function composition. These functions are then applied to solve real world problems. The ability to picture many different types of functions will help students learn how and when to apply these functions, as well as give students the geometric intuition to understand the algebraic techniques. The skills and objectives from this course improve problem solving abilities. A linear relationship between two variables occurs when there is a constant increase or constant decrease in one variable with respect to the other. Linear functions have the property that any chance in the independent variable results in a proportional change in the dependent variable. Many physical situations can be modeled using a linear relationship. Adding an extra term of the form ax^2 to a linear function creates a quadratic function, and its graph is the parabola. We will see examples of linear and quadratic functions and their applications in the sections that follow. 2 videos5 readings2 assignments In the last module we introduced the important concept of a function and considered the linear and quadratic functions. In this module, we discuss methods for building new functions from those that are already familiar to use. One method will use the graph shifting techniques already introduced. These methods are developed further and applied to new functions. Constructing a graph is often an important first step in solving a problem. The more functions you can picture, the better problem solver you will be. 3 videos5 readings2 assignments Congratulations on reaching the final exam! This final assessment will be cumulative in nature, covering all aspects of the course. Use this final as a teaching tool: justify what you know and identify areas for improvement. Use scrap paper as you take this final. Try to use any formula sheets or outside resources as a tool and not a crutch. Check your answers before you submit. After the test, review any incorrect answers to find your mistakes. Try to separate "silly" mistakes from the more substantial mistakes in understanding. Good luck! 1 assignment

3 modules

Beginner level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/algebra-ii

AWS DynamoDB Fundamentals

Enrollment number not found

Rating not found

Whizlabs Instructor

Whizlabs

['Amazon Dynamodb', 'aws', 'Table operations', 'DynamoDB Backups', 'DynamoDB Indexes and Global Tables']

Amazon DynamoDB Fundamentals is a skill enhancement course designed for candidates aiming to enhance their knowledge as Database professionals. This course will help learners understand working with NoSQL databases. Furthermore, fluency in basic concepts of AWS DynamoDB brings long-term opportunities with a specialization in database designing on the cloud. This course provides 7+ hours of training videos which are segmented into modules. The course concepts are easy to understand through lab demonstrations. Learners could find a total of 55 lectures in the training course with comprehensive coverage of the features and concepts of DynamoDB. The course is divided into 6 Modules and each module is further split into lessons. In order to test the understanding of learners, every module includes Assessments in the form of Quizzes and In Video Questions. A mandatory Graded Questions Quiz is also provided at the end of every module. Module 1: NoSQL Introduction Module 2: DynamoDB Tables Module 3: DynamoDB Items Module 4: DynamoDB Indexes Module 5: DynamoDB Global Tables Module 6: DynamoDB Backups This course aims to achieve multiple AWS Certifications. Some of the important benefits of achieving these certifications include: - Validating your knowledge and understanding of serverless NoSQL databases. - Providing you with global recognition for your knowledge, skills, and experience. - Getting more chances of being promoted in your current job or getting a new job with a high paycheck. So, enroll in our Amazon DynamoDB Fundamentals Course and attain career growth by becoming a Database Professional. In addition, you can also explore many other opportunities in various job roles in the AWS landscape. Welcome to the NoSQL Introduction. In the first week of the course. we'll learn the importance of NoSQL database. We will also learn the difference between SQL and NoSQL databases. This course will help the learners to understand the relation between NoSQL and Amazon DynamoDB. 3 videos2 readings2 assignments1 discussion prompt In the second week of this course, we'll learn about CRUD operations performed on DynamoDB Tables. We'll also explore the concepts of Auto Scaling and different types of storage capacities used with DynamoDB tables. 15 videos1 reading4 assignments In the third week of the course, we'll get an overview of Get, Put and Delete items operations in DynamoDB tables. We'll understand certain operations that allows to perform batch reads or writes on data stored in from one or more DynamoDB tables. In the end, you will learn to manage complex business workflows using DynamoDB transactional read and write APIs 15 videos1 reading3 assignments Welcome to the fourth week of the course. Here, we'll learn few more Item Level Operations such as Scan, Query and UpdateItem. We'll also explore expressions in DynamoDB and its related operations. By the end of this module, we'll be in position to describe Item Level Operations in DynamoDB. 12 videos1 reading3 assignments In the fifth week of the course, we'll undertand the concept of indexes and global tables used in DynamoDB. We will be able to differentiate between Local Secondary Indexes and Global Secondry Indexes. We'll also demonstrate the working of indexes and global tables using a real-world example. 15 videos1 reading3 assignments In the sixth week of the course, we'll learn about on-demand backup capability for DynamoDB. We will also explore and demonstarte another type of backup capability used in DynamoDB that is point-in-time recovery (PITR). By the end of this week, you wil understand the concept of backups used in DynamoDB. 7 videos2 readings2 assignments

6 modules

Beginner level

14 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/aws-dynamodb-fundamentals

Introduction to Google Workspace Administration

57,729

4.7

Google Cloud Training

Google Cloud

[]

Introduction to Google Workspace Administration is the first course in the Google Workspace Administration series of courses. This series will serve as the starting place for any new Google Workspace admin as they begin their journey of managing and establishing Google Workspace best practices for their organization. These courses together will leave you feeling confident to utilize the basic functions of the admin console to manage users, control access to services, configure security settings, and much more. Through a series of readings and step-by-step hands-on exercises, and knowledge checks, learners can expect to leave this training with all of the skills they need to get started as Google Workspace administrators. In this course you will sign up for a Google Workspace account and configure your DNS records for Google Workspace. You will learn how to provision and manage your users, and will create groups and calendar resources for your organization. You will be introduced to your Cloud Directory and will learn how to split your organization into organizational units to simplify user and service management. Finally you will learn how to delegate admin privileges to other users in your organization. IMPORTANT - To get the most out of this training course, learners should be prepared to: - Purchase a new domain through a registrar such as enom or GoDaddy. Note: If you already have a domain that you would like to use for the trial you can do this but this course does not provide detailed steps on how to associate an existing domain with a Google Workspace trial account. For detailed instructions on how to do that, please refer to this Help Center article: https://support.google.com/a/topic/9196 - Provide credit card details as part of the Google Workspace account setup. You will be using a 14 day trial Google Workspace account during this course. As part of the sign up flow you will be required to provide credit card details. No charges for Google Workspace are made to your credit card until the trial period has ended. You must ensure that you CANCEL YOUR SUBSCRIPTION before the trial period ends to avoid and charges. This is very IMPORTANT so don't forget! - Install and be ready to use the latest version of Chrome web browser available at https://www.google.com/chrome/ In this course you will sign up for a Google Workspace account and configure your DNS records for Google Workspace. You will learn how to provision and manage your users, and will create groups and calendar resources for your organization. You will be introduced to your Cloud Directory and will learn how to split your organization into organizational units to simplify user and service management. Finally you will learn how to delegate admin privileges to other users in your organization. 16 videos22 readings8 assignments

1 module

Beginner level

https://www.coursera.org/learn/introduction-google-workspace

96%

The Road to Autonomy: Exploring EV Technologies

Enrollment number not found

Rating not found

Prasanth Kumar Palani

Coursera Instructor Network

['Safety Systems of Electric Vehicles', 'Design of Sensor Systems', 'Technology Systems in AEV', 'Design of Autonomous Electric Vehicles']

Electric Vehicle Autonomous Technologies is a dynamic and forward-looking course that covers the transformative realm of autonomous electric vehicles (AEVs). In an era where transportation is on the brink of a revolution, this course provides a setting to analyze the fusion of electric propulsion and autonomous driving. It explores the convergence of cutting-edge technologies that are reshaping the automotive landscape, offering learners a journey into the future of mobility. In the first part of this course, we embark on an exploration of the foundations of AEVs. We take a deep dive into the history and evolution of autonomous electric vehicles, tracing their roots from early experiments to the present day. Learners will gain an appreciation of the importance of AEVs in reducing emissions, enhancing safety, and revolutionizing transportation in urban environments. The second segment of the course immerses learners in the heart of AEV technology—the sensor systems, perception algorithms, and decision-making processes that enable vehicles to navigate autonomously. In the final part of the course, we confront the critical aspects of safety and the challenges that lie ahead for AEVs. Safety is paramount in autonomous driving, as we explore the regulatory frameworks and measures in place to ensure the well-being of passengers and pedestrians alike. This course is designed for electric vehicle (EV) enthusiasts interested in the future of electric and autonomous vehicles. It is recommended to complete the basic course on electric vehicle technology before taking this course. Electric Vehicle Autonomous Technologies is a dynamic and forward-looking course that covers the transformative realm of autonomous electric vehicles (AEVs). In an era where transportation is on the brink of a revolution, this course provides a setting to analyze the fusion of electric propulsion and autonomous driving. It explores the convergence of cutting-edge technologies that are reshaping the automotive landscape, offering learners a journey into the future of mobility. 11 videos4 readings1 assignment

1 module

Beginner level

2 hours to complete

https://www.coursera.org/learn/the-road-to-autonomy-exploring-ev-technologies

Teaching Writing Final Project

Enrollment number not found

Rating not found

Mark Farrington

Johns Hopkins University

[]

One of the goals of the Teaching Writing specialization has been to help every learner consider ways to adapt what they are learning and apply it to their specific situation, needs and interests. The theories, strategies and practices presented in these courses are sound, and can work with any student of any age and skill level, provided each learner is able to adapt their learning and apply it to their specific students, current or future. In this final project, learners will select one component from each of the four courses that are among the most important things they learned from that course. They will describe what these components are, explain why they are important to the learner, and create a plan for incorporating that new learning into their teaching or their own writing going forward. One of the goals of the Teaching Writing specialization has been to help every learner consider ways to adapt what they are learning and apply it to their specific situation, needs and interests, and in this final project, you’ll apply your learning to your current or future teaching. The project consists of a series of writings. In this first module, you’ll select four of the most valuable takeaways you have gained from these courses. In subsequent modules, you'll construct learning objectives, create a lesson plan that you could use in your classes, and finally, you'll evaluate this specialization as if you were the designer and instructor. The project is separated into four modules, with a peer review assignment in each module. 2 videos1 peer review The most significant assignment in this final project is a lesson plan you will create. We'll focus on lesson plans in module 3, but for now, we'll start by looking at learning objectives: what you want your students to learn from the lessons you teach. 1 video5 readings1 peer review When I first started teaching, my greatest fear was, What am I going to do with these students for an hour every day? How will I fill up the time? Soon enough, I realized there was more than enough to do, and in fact, an hour a day wasn’t enough time to cover everything I wanted to include. But in those early days, the most welcome tool I discovered was the lesson plan. Through lesson plans, I could map out the day or the week or the month ahead and feel confident that I was teaching my students the most important things I believed they needed to learn. Of course, no class ever followed one of my lesson plans perfectly, and flexibility – learning to adjust on the fly – is one of the most valuable attributes for teachers to have. But the lesson plan gave me a map that helped me and my students reach the desired destination. I still use them, all these many years later. In this module, you’ll create a lesson plan based on some topic discussed in one or more of the courses in this specialization that you could use with your current or future students. This lesson plan will be most major assignment of this final project, and you’ll have lots of time to work on it. 3 videos4 readings1 peer review Now congratulations really are in order! You’re just one step away from completing the Teaching Writing Specialization. My final request is for you to help me evaluate these courses you have just completed, with an eye toward making them as effective, valuable, and relevant as possible for the learners who follow you. 1 video1 peer review

4 modules

Beginner level

21 hours to complete (3 weeks at 7 hours a week)

https://www.coursera.org/learn/teaching-writing-final-project

Learn Bootstrap

Enrollment number not found

Rating not found

Per Harald Borgen

Scrimba

['Bootstrap', 'Responsive Web Design', 'Web Development', 'Cascading Style Sheets (CSS)', 'HTML Tables']

This instructional course guides you through the essential knowledge required to build comprehensive websites using Bootstrap v4. Bootstrap is an open-source front-end framework designed for responsive development, prioritizing mobile-first websites and web applications. The Scrimba course offers interactive code engagement within tutorials, providing an opportunity to reinforce concepts as you learn. Learn everything you need to know in order to create full-blown websites with Bootstrap v4. 1 assignment11 plugins

1 module

Intermediate level

1 hour to complete

https://www.coursera.org/learn/learn-bootstrap

Major Depression in the Population: A Public Health Approach

41,494

4.7

William Eaton, PhD

Johns Hopkins University

[]

Public Mental Health is the application of the principles of medicine and social science to prevent the occurrence of mental and behavioral disorders and to promote mental health of the population. This course illustrates the principles of public health applied to depressive disorder, including principles of epidemiology, transcultural psychiatry, health services research, and prevention. It is predicted that by 2020 depressive disorder will be the most important cause of disease burden in the entire world! Every human being suffers from feeling depressed at some point or other, but only about one fifth of the population will experience an episode of depressive disorder over the course of their lives. This course illuminates the public health approach to disease, and the particular complexities of applying this approach to mental disorders, using depression as the exemplar. Welcome to Major Depression in the Population: A Public Health Approach. Let's take a few moments to introduce the course before we dive into our first lessons. 1 video2 readings This week, we will be focusing on the definition of major depression and the methods that we use for measuring its effect on populations. 5 videos1 assignment1 discussion prompt This week we will be covering depression from a global public health perspective. 4 videos1 assignment1 discussion prompt This week we take advantage of what we know about major depressive disorder to examine major epidemiologic research designs, including the case control design, the cohort design, and the study of diseases in time and space. 5 videos1 assignment1 discussion prompt This week the focus is on possible causes for depressive disorder, including inheritance, stress, social life, work life, and the evolution of modern living. 5 videos1 assignment1 discussion prompt Choice 1: You are the coordinator of an international nutrition program in refugee camps, including a refugee camp in Tanzania. Most of the refugees in this camp have fled violence from the Democratic Republic of the Congo, and the size of the camp is increasing because of the intensification of armed violence there. The nutrition organization that you have been working for has been implementing programs to promote breastfeeding, and appropriate infant and young child feeding practices. You have been told that program staff are facing difficulties, and you decide to visit the site to see for yourself what is going on. In your meeting with some of the community health workers who are implementing the program, you hear of women living in very challenging circumstances. A group of women seems to be very tired and have lost the energy to engage with daily routines. You suspect that mental health may play a role, and decide to ask further questions and write a report about this to your organization’s headquarters. | Choice 2: A young entrepreneur from Oklahoma named Rodney Johnson created a household cleaning product made from byproducts of the corn industry. This product, called Solvit, is very good at cleaning up grease and dirt, and was more effective than many other well-known products such as Mr. Clean, Fantastik, and Lysol. Mr. Johnson started marketing the product in 1992 at stores in his native Oklahoma, and also on the World Wide Web. Twenty years later this product is the most widely used cleaning agent in North America, although it still has not been introduced in several states. In 2012 Consumer Reports magazine determined that the product contained solvents that might cause depressive disorder. It asked the Consumer Products Safety Commission to ban the product. The Institute of Medicine was asked for its advice. The IOM learned that you had taken this course and has asked you to consult on epidemiologic evidence and methods that might support the claim that Solvit produces depressive disorder. 2 peer reviews In this module, we discuss unmet need for treatment and treatment seeking and present a public health view of depression treatment. 4 videos2 assignments2 discussion prompts 1 peer review

8 modules

Beginner level

https://www.coursera.org/learn/public-health-depression

97%

Building Web Applications in Django

52,922

4.7

Charles Russell Severance

University of Michigan

['Django (Web Framework)', 'GET & POST', 'Cross-Site Scripting Forgery (CSRF)', 'Object-Oriented Programming (OOP)', 'Django Template Language']

In this course, you will learn how Django communicates with a database through model objects. You will explore Object-Relational Mapping (ORM) for database access and how Django models implement this pattern. We will review the Object-Oriented (OO) pattern in Python. You will learn basic Structured Query Language (SQL) and database modeling, including one-to-many and many-to-many relationships and how they work in both the SQL and Django models. You will learn how to use the Django console and scripts to work with your application objects interactively. This section explores how we define models in Django and then we build the data models and explore the administration interface for our application. Data models are how Django interacts with the underlying database to store and retrieve data. 8 videos4 readings2 assignments1 app item Views are the aspect of Django applications that produce the web pages that are shown to our users. Views are one of several core elements of Django applications. 9 videos1 reading2 assignments1 app item We review Python Object Orientation and look at the generic views capability within Django. We use generic views by extending Django classes to make a new view class. 7 videos2 readings2 assignments We cover how GET and POST work, how forms are constructed from HTML, how we protect our applications against Cross-Site Scripting Forgery (CSRF), and how we handle browser refreshes after POST. 8 videos3 readings2 assignments1 app item

4 modules

Intermediate level

https://www.coursera.org/learn/django-build-web-apps

97%

Managing Human Capital in Retail

2,988

4.6

Matthew Bidwell

University of Pennsylvania

[]

In this course, you will cover the fundamentals of human capital management with a focus on the retail industry. Professor Matthew Bidwell will start by examining the critical role that people play in creating value within any business, and will then assess how that value is fostered by various organizational practices. Professor Bidwell then does a deep-dive into some of the practices that drive organizational success: how to hire effectively; how to develop and retain a skilled workforce; and to motivate employees to contribute to organizational success. By the end of this course, you will have a better understanding of how human capital contributes to the success of the business, a critical role in shaping your organizational capacity. In this module, you will begin to assess the links between managing people and organizational performance and how human capital can drive value. You will examine methods of managing people in ways that create value. using the ability-motivation-opportunities framework. By the end of this module, you will have a clearer understanding of how human capital management operates as a system, the ways these systems interrelate across a company, and how it all relates to a broader organizational strategy. 8 videos1 reading1 assignment In this module, you will examine various elements of high performance staffing, an important concept in effective human capital management. You will delve into specific best practices for making the right decision in your hiring process and how the internal hiring pipeline plays a role in this decision making process. By the end of this module, you will be able to identify the benefits of adopting effective hiring practices and understand how this contributes to to well-established internal hiring channels in the future. 8 videos1 reading1 assignment In this module, you will consider the best ways to develop and retain current employees. You'll think critically about job skills as well as the the drawbacks and benefits of job training depending on your approach. You'll examine the impact of turnover, and the loss of organizational investment in an employee associated with attrition. By the end of this module, you'll be able to identify reasons why an employee leaves an organization and develop a plan for retaining valuable members of your team. 7 videos1 reading1 assignment In this module, you will continue examining human capital in the organizational workforce. You'll utilize your knowledge about employee retention to now focus on employee motivation, identifying multiple factors that play a role in employee satisfaction. You'll discuss how to pay employees effectively and how to design a job so that employees feel motivated on a day-to-day basis. By the end of this module, you will possess a wide array of tools to incentivize employees to work effectively over longer periods of time with a company. 7 videos1 reading1 assignment

4 modules

Beginner level

8 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/wharton-managing-human-capital-retail

Virtual Reality Specialization

39,014

4.7

Prof Marco Gillies

University of London

['Interaction Design', '3d computer graphics', 'Virtual World', 'Virtual Reality', 'Interaction Design', '3d computer graphics', 'Virtual World', 'Virtual Reality']

This specialisation from theUniversity of LondonOpens in a new tabwill introduce you to virtual reality. Virtual reality is one of the most highly requested skill sets in the jobs market, and this specialisation will give you an introduction to the subject and key skills in the field. You will hear from world-leading lecturers and industry experts, use Unity to develop your own VR environment, and end the specialisation by creating your first VR game. Applied Learning Project By the end of the specialisation you will be able to develop your very own Virtual Reality game. You will take the skills you have developed in each of the preceding courses and, using Unity, you will put these into practice to create your first virtual reality game. This course will introduce you to Virtual Reality (VR). The course will teach you everything from the basics of VR- the hardware and the history of VR- to different applications of VR, the psychology of Virtual Reality, and the challenges of the medium. The course is designed for people who are new to VR as a medium. You may have experienced some virtual reality before, and may have some hardware- but this course is suitable to individuals who have never experienced VR and those who do not have much hardware- we will explain Mobile VR as well as devices such as the Oculus Rift and HTC Vive. Introduction to Virtual Reality is the first course in the Virtual Reality Specialisation. A learner with no previous experience in Virtual Reality and/or game programming will be able to evaluate existing VR applications, and design, test, and implement their own VR experiences/games using Unity by the end of the specialisation. This course will begin your journey to creating Virtual Reality experiences. A Virtual Reality experience is a new world that you step into and are entirely immersed in. Creating a VR experience means creating that world and all the objects in it. In this course you will learn the basics of 3D graphics: how we create objects and how to lay them out to create an environment. You will learn techniques like materials and texturing that make your objects appear realistic. You will also learn about audio techniques to ensure that your experiences sound great as well as looking great. In all of these topics we will pay attention to the particular requirements of Virtual Reality, including pitfalls and performance issues: making sure your environment runs fast enough in VR. You will learn all of this using the professional game and VR engine, Unity3D. Unity is one of the most used game engine and is a relatively easy, but fully featured, introduction to 3D development. The course will culminate in a project in which you will create your own VR scene. VR development is something you can only learn by doing it yourself, so working on your project will be the best way to learn. This course will teach you about one of the most important aspects of VR, how you interact with a VR world. Virtual Reality is completely different from an on screen app or game. You are completely immersed in a VR world, so it doesn't make sense to interact only through buttons or menus. You will get the most out of VR if you can interact with the world just as you would with the real world: with your natural body movements. You will learn about the basic concepts and technologies of VR Interaction. You will then get hands on, learning about how to move around in VR and how to interact with the objects in your world. The course will finish with some advice from experts on VR interaction design and you will do a project where you will get real experience of developing VR Interaction. Meeting another person is one of the most amazing experiences you can have in Virtual Reality. It is quite unlike communicating through any other medium except a real life face-to-face conversation. Because the other person is life size and shares a virtual space with you, body language works in a way that cannot be done on a flat screen. This course will enable you to create realistic social interactions in VR. You will learn about both the psychology of social interaction and the practical skills to implement it in Unity3D. We will take you through the basics of 3D character animation and how to create body language. You will learn about how to make characters that can respond to players’ speech and body language. You will also learn about avatars: the virtual representation of other players, and agents: computer controlled NPC characters and how to implement both of them. As many people have said before us, social is the future of VR. This course will help you become part of the future of Virtual Reality social experiences. Virtual Reality is one of the most exciting experiences that technology can give us. The immersion and presence you can have in VR is quite unlike any other medium. Like many others, you are excited about the possibilities of this new medium and want to get started developing your own VR experiences. This course will take you through all of the steps you need to create a VR game or other project. This is the final course in our Specialisation: Virtual Reality. The previous courses teach you the skills you need to make a VR game. This course brings them all together to create a project of your own. We will guide you through all the steps of a VR project: coming up with an idea, storyboarding, prototyping, testing and implementation. By the end of this course you will have a complete VR project that demonstrates your skills and could be the first step in creating a professional game. We hope this course can be your entry into professional VR development. To help you get started, some good advice always helps. That is why we have interviewed VR experts from all over the world, ranging from technology pioneers with over 30 years experience in VR to the latest cutting edge VR creators. We have asked all of them to give you their advice and we hope it inspires you to become part of the future of VR.

5 course series

Beginner level

2 months (at 10 hours a week)

https://www.coursera.org/specializations/virtual-reality

Acute and Chronic Rhinosinusitis: A Comprehensive Review

20,397

4.8

Satish Govindaraj, MD

Icahn School of Medicine at Mount Sinai

['Chronic Rhinosinusitis', 'Surgery', 'Acute Rhinosinusitis', 'Diagnostic Evaluation']

Welcome to Acute and Chronic Rhinosinusitis: A Comprehensive Review This course, offered by the Department of Otolaryngology – Head and Neck Surgery at the Icahn School of Medicine at Mount Sinai, is designed to inform primary care physicians and general otolaryngologists, as well as nurses, physician assistants and medical assistants, about the differences between acute and chronic rhinosinusitis and how to distinguish and treat them. It is also applicable to individuals who wish to broaden their knowledge and vernacular about this disease process, especially those who may suffer from this condition. The course has been divided into four modules, each of which is followed by multiple choice questions to help attendees further understand this condition: Week 1 - CME Information, Accreditation and Introduction Week 2 - Module 1: Normal Sinus Anatomy and Function (15 min. + quiz) Week 3 - Module 2: Acute Rhinosinusitis: Diagnosis and Treatment (17 min. + quiz) Week 4 - Module 3: Chronic Rhinoinusitis: Diagnosis and Treatment (18 min. + quiz) Week 5 - Module 4: The Role of Surgery for Sinusitis and Activity Evaluation (36 min. + 2 quizzes) The primary objective of this course is to provide physicians with a thorough understanding of how to better diagnose and treat patients who suffer from acute and chronic rhinosinusitis. Note: This course is no longer available for CME Credit. Please review the CME Information and Accreditation prior to proceeding with the course modules. Release Date: January 16, 2018 Expiration Date: January 16, 2020 Estimated Time to Complete: One Hour and Forty Five Minutes CME Fee: $30.00 CME Credits Offered: 1.75 CME Reviewer: Marita S. Teng, MD How to Receive CME Credit: For physicians who are interested in earning CME credits and other allied health professions who wish to receive a Verification of Attendance certificate, you must: a. Complete Signature Track (details to follow after enrolling in this course) b. Complete registration process through the Icahn School of Medicine at Mount Sinai, CME Office using the following link: http://bit.ly/Acute_Chronic (WARNING: This course is no longer available for CME Credit.) (You will be required to pay an additional non-refundable fee of $30.00 in addition to the $49.00 fee for signature track.) c. Email an attached copy of your Verified Certificate from Coursera to the CME office at the Icahn School of Medicine at [email protected] and request your CME certificate. d. You will be provided with the instructions for downloading your CME/CE certificate. Technical Design and Development Lynette Bobbitt Lisa Chase Jill Gregory Paul Lawrence Charles Psarreas Rory Sacks 2 readings 1 video2 readings Dr. Govindaraj of the Department of Otolaryngology – Head and Neck Surgery at the Icahn School of Medicine at Mount Sinai, describes an overview of the normal sinus anatomy and function. Illustrated images and CT scans are used to review the anatomy of the paranasal sinuses. The microscopic appearance of the sinus mucosa is reviewed, utilizing dynamic multimedia to enhance the viewer’s understanding. The module concludes with a review of the various sinus drainage pathways. Upon completion of this activity, participants will be able to: a) Describe the normal anatomy of the sinuses. b) Describe normal sinus function. c) Assess the importance of mucociliary function. 1 video1 reading1 assignment In this module about acute sinusitis Dr. Govindaraj will focus on diagnosis and management. This will help you distinguish between acute bacterial from viral rhinosinusitis. The bacterial pathogens responsible for acute sinusitis are covered in-depth, as well as when antibiotic therapy can be withheld in select cases. In addition, the current Academy Guidelines for the management of acute sinusitis are reviewed, focusing on the diagnostic criteria, as well as evidence-based management of this disease process. Upon completion of this activity, participants will be able to: a) Explain difference between acute and chronic rhinosinusitis. b) Appropriately diagnose acute and chronic rhinosinusitis. c) Recognize the proposed pathogenesis of acute and chronic rhinosinusitis. 1 video1 reading1 assignment Dr. Govindaraj focuses on the diagnosis and management of chronic rhinosinusitis. The diagnostic criteria is reviewed and compared to acute sinusitis which will help to clearly distinguish between these two entities. Associated disorders that predispose patients to chronic sinusitis are discussed, as well as the diagnostic evaluation that should be performed in the workup of these patients. The role of systemic and topical therapies is also reviewed. Additionally, the current Academy Guidelines are covered in-depth, as well as the evidence-based medical management of this disease process. Upon completion of this activity, participants will be able to: a) Identify the causative agents for acute and chronic rhinosinusitis. b) Assess the medical management of acute and chronic rhinosinusitis. c) Evaluate the recommended antibiotic choices for acute and chronic rhinosinusitis 1 video1 reading1 assignment We will focus on the role of surgery and the management of refractory acute and/or chronic rhinosinusitis. We hope you will appreciate the potential benefits offered by sinus surgery, as well as the indications to pursue this treatment modality. The latter half of this module is geared toward the general otolaryngologist, who performs sinus surgery. The necessary preparation and steps of the procedure are reviewed, as well as important anatomic landmarks during surgical dissection. Short video segments are used in order to enhance the viewer’s understanding. Themodule concludes with a brief discussion of the potential complications associated with sinus surgery. Upon completion of this activity, participants will be able to: a) Identify the indications for sinus surgery. b) Assess the potential complications of endoscopic sinus surgery. c) To perform and recognize the components of an endoscopic sinus surgery. 3 videos1 reading1 assignment All learners are urged to complete an evaluation. Your comments are essential for improving the effectiveness of Icahn School of Medicine at Mount Sinai’s continuing medical education activities. 1 reading

7 modules

Intermediate level

https://www.coursera.org/learn/icahn-school-of-medicine-at-mount-sinai-acute-and-chronic-rhinosinusitis

98%

Diabetes – the Essential Facts

87,565

4.7

Nicolai Jacob Wewer Albrechtsen

University of Copenhagen

[]

Across the world more than 420 million people are living with diabetes. Two thirds of these have not yet been diagnosed. When discovered late or managed incorrectly, diabetes can damage your heart, blood vessels, eyes, kidneys, and nerves, leading to disability and premature death. In fact, more people are dying of diabetes related diseases than of diseases as HIV/AIDS, malaria and tuberculosis combined. This course will provide you with an introduction to the most recent research in the field of prevention and treatment of diabetes as well as a broader understanding of the situation in different communities, rich and poor, across the world, where diabetes threatens public health. What kind of disease is diabetes, who has it, and who is at risk of getting it? And what are the roles of medicine, exercise and nutrition when trying to prevent, delay or treat diabetes? During the course you will meet researchers and experts from Imperial College London, Emory University in Atlanta, Steno Diabetes Center in Copenhagen as well as the School of Global Health and the Center for Basic Metabolic Research at the University of Copenhagen. They work with very different aspects of diabetes, from microbiology to global public health, but what ties them together is the belief that it is a global responsibility to combat diabetes, and this fight can only be won through new knowledge and global collaboration. We hope you will join us in the course and equip yourself to take part in the ongoing discussions of this truly global and individual health challenge. This course is also part of the EIT Health programme. In this first module you will be introduced to the fundamentals about diabetes. This includes both the biomedical and public health aspects, such as a description of the different types of diabetes, a profile of the most at risk people and populations as well as an introduction to the epidemiological trends that have changed dramatically over the last decades. 4 videos4 assignments1 discussion prompt In this second module you will be introduced to the important roles of nutrition and exercise when preventing and treating diabetes. We will have a more detailed look at the role of obesity and overweight and also focus on the challenges of fighting diabetes in low- and middle-income countries. 3 videos4 assignments1 discussion prompt In this final module we will discuss some of the new research and treatment methods for diabetes, such as surgery or microships, and then we will ask the researchers where they see the field going in the future. The last lesson will be followed by a short peer-review assignment, where you have to submit a short text, and afterwards review the submissions of your peers. 3 videos2 assignments1 peer review2 discussion prompts

3 modules

Beginner level

https://www.coursera.org/learn/diabetes-essential-facts

97%

Healthcare Trends for Business Professionals Specialization

7,147

4.5

George “Russ” Moran

Northeastern University

['Predictive Analytics', 'Analytics', 'Decision Support System', 'Workflow', 'Predictive Analytics', 'Analytics', 'Decision Support System', 'Workflow']

This Specialization will provide learners with the knowledge and skills to recognize key shifts in the industry and to have an agile perspective on how these shifts might impact their organizations. Learners will be exposed to the key drivers in the global healthcare industry today so they might apply what they have learned to help their organizations. Applied Learning Project In each course you will have an opportunity to solve real-world problems facing the healthcare industry, for example: In Course 1 you will suggest operational changes to improve the quality of care for consumers. In Course 2 you will take on the role of a CEO to solve a real-world healthcare payment issue within the company. In Course 3 you will investigate healthcare websites and compare hospital report cards to determine if they are meeting expectations. In Course 4 you will take on the role of a consultant to present opportunities and benefits of integrating AI for a specific business. In this course we will examine the changing role of the consumer in healthcare. Consumers are asking for more accountability in how healthcare is delivered and paid for. Healthcare professionals must make sure that they are delivering high quality, personalized care. Some of the topics we'll cover are: the healthcare ecosystem, new technologies in healthcare, the development of new payment models, change management in healthcare, data analytics. By the end of this course, you will be able to: 1. Explain the new role of consumers in healthcare delivery in order to respond to the demands in this changing industry 2. Identify the key players in the healthcare ecosystem 3. Describe how the healthcare system operates and its impact on consumer-driven healthcare. 4. Articulate the challenges facing consumers and providers in order to find potential solutions for these challenges. Identify the drivers and trends of healthcare spending from the perspective of various stakeholders. Critically assess the impact of strategic and financial approaches that have been put in place by the ACA and the various modifications. Evaluate how healthcare payment models currently work and the new direction that value-based payment is taking. Identify how financial and non-financial metrics can be appropriately combined to improve a healthcare stakeholders’ value proposition. Explain key developments regarding how quality of care is measured and evaluated in the US. Discuss scientific issues and challenges for evaluating quality of care and methods for addressing these challenges. Identify and apply resources and tools for comparing the quality of care of providers. Articulate basic framework for evaluating quality of outcomes of care for evaluating and comparing providers. Determine the factors involved in decision support that can improve business performance across the provider/payer ecosystem Identify opportunities for business applications in healthcare by applying journey mapping and pain point analysis in a real world context Identify differences in methods and techniques in order to appropriately apply to pain points using case studies Critically assess the opportunities to leverage decision support in adapting to trends in the industry

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/healthcare-trends-business-professionals

Research Methodologies

19,316

4.7

Athanasia Lampraki

Queen Mary University of London

['Collect primary and secondary data', 'Use qualitative and quantitative research methodologies', 'Adopt different sampling approaches', 'Evaluate different data collection approaches']

This course focuses on research methodologies. In this vein, the focus will be placed on qualitative and quantitative research methodologies, sampling approaches, and primary and secondary data collection. The course begins with a discussion on qualitative research approaches, looking at focus groups, personal interviews, ethnography, case studies and action research. We will also discuss quantitative research methods with a focus on experimental research design and survey methodology. There will be an exploration of the sampling design process and different sampling approaches, including probability and non-probability sampling as well as sample size and non-response issues. We will look at the nature and scope of primary and secondary data, and the importance of measurement. We will look at the role of the Internet in market research as well as non-comparative scaling techniques. The course ends with a discussion on different data collection approaches, with a focus on observation, content analysis, narrative research, phenomenology, and the collection of data using ethnography. This week begins with a discussion on qualitative research approaches, looking at focus groups, personal interviews, ethnography, case study and action research. The week ends with a discussion of quantitative research methods with a focus on experimental research design and survey methodology. 4 videos6 readings5 assignments5 discussion prompts The week begins with a discussion on the sampling design process and continues with different sampling approaches, including probability and non-probability sampling. The week ends with a discussion on sample size and non-response issues. 4 videos6 readings6 assignments4 discussion prompts The week begins with a discussion of the nature and scope of secondary data and continues with a discussion of primary data and the importance of measurement. The week ends with the role of the Internet in market research and a discussion about non-comparative scaling techniques. 4 videos6 readings6 assignments4 discussion prompts The week starts a discussion on different data collection approaches with a focus on observation, case study and content analysis. The week continues with a focus on narrative research, phenomenology and the action research project. The week ends with a discussion of collecting data using ethnography. 4 videos5 readings5 assignments1 peer review5 discussion prompts

4 modules

Beginner level

https://www.coursera.org/learn/research-methodologies

98%

Introduction to Generative AI

10,368

4.6

Noah Gift

Duke University

['Artificial Intelligence (AI)', 'Python Programming', 'Machine Learning', 'GenAI', 'LLMs']

This introductory course is designed for beginners with no prior knowledge of generative AI. You will start by gaining a high-level understanding of what generative AI is and how it works. Through interactive lessons and hands-on examples, you will learn fundamental skills like providing effective prompts and iteratively improving the generated outputs. As the course progresses, you will dive deeper into specific major generative AI models, including their unique capabilities and limitations. Finally,, you will get practical experience using leading systems like GitHub Copilot, DALL-E, and OpenAI to generate code, images, and text. By the end, you will have developed core knowledge to start experimenting with generative AI in a responsible and effective way for a variety of applications. This course aims to provide a friendly introduction to prepare complete beginners for further exploration of this rapidly evolving technology. In this module, you will learn what generative AI is and how it has evolved from early AI to the large language models used today. You'll understand how these models work in applications by learning about model architectures and the training process. The module provides an overview of major foundation models like ChatGPT and Hugging Face, highlighting their capabilities and limitations. You'll explore the generative AI landscape, comparing options like open source models, local models, and cloud APIs. By the end, you'll have a solid base of knowledge about the foundations of this technology and options for accessing and leveraging different AI systems. 21 videos10 readings4 assignments1 discussion prompt In this module, you will learn the fundamentals of prompt engineering to interact effectively with generative AI models. You'll understand the concept of few-shot prompting and practice basic prompting techniques using context and examples. Building on this, you'll learn methods for improving prompts through personas, detailed instructions, and iteration based on feedback. Finally, you'll explore more advanced skills like breaking down tasks, chaining prompts, and other useful techniques to overcome context limitations. 18 videos5 readings4 assignments In this module, you will explore different types of generative AI applications, including API-based, embedded model, and multi-model systems. You'll learn the fundamentals of building robust applications using techniques like Retrieval Augmented Generation (RAG) to improve context. Through hands-on exercises, you'll gain experience testing an application locally and deploying it on the cloud. 19 videos5 readings3 assignments1 ungraded lab Here, you will learn the key capabilities of the OpenAI API. You will generate images with OpenAI’s DALL-E, “fine tuning” LLM models to Reddit questions and answers and summarize videos with OpenAI’s Whisper Model. 19 videos8 readings4 assignments1 ungraded lab

4 modules

Beginner level

37 hours to complete (3 weeks at 12 hours a week)

https://www.coursera.org/learn/intro-gen-ai

Financial Analysis of Scenarios and Decisions

9,853

4.8

Gies College of Business, University of Illinois

University of Illinois Urbana-Champaign

['Decision-Making', 'Financial Analysis', 'Data Analysis', 'Budget', 'Planning']

This course focuses on adopting and implementing a financially analytic mindset when engaged in organizational decision-making and scenario analysis. The course begins with an overview of the "internal" perspective of the organization, in which you will learn fundamental concepts, including the importance of how cost information is organized for different decision scenarios. You will then learn about scenario analysis, including cost-volume-profit analysis and other fundamental concepts that help facilitate financial organizational decision-making. Next, you will learn about planning and budgeting, a key function that allows organizations to identify and allocate resources necessary to achieve organizational goals. You will then learn how to assess actual performance against these budgets using variance analysis. Finally, you will learn about the organization’s performance measurement, evaluation, and compensation system. Specifically, you will learn about the advantages and disadvantages of common financial performance measures and understand how an organization uses non-financial performance measures within its strategic performance measurement system to complement the financial perspective. In this module, you will become familiar with the course, your instructor, your classmates, and our learning environment. Then, you will be introduced to Managerial Accounting and Costing Concepts. Next, you will explore cost-volume-profit (CVP) analysis. CVP analysis is a tool that managers can use to better understand the answers to "what-if" questions in order to make better decisions for their companies. You will also explore the nature and role of relevant information in common business decisions, two key related concepts, and how to avoid common decision-making "pitfalls." 17 videos6 readings9 assignments1 discussion prompt At the heart of an organization’s planning and control function is its budget. In this module, you will explore the purpose of budgeting, the role of managers and employees in budgeting, and related implications. You will also develop an organization’s budget, ultimately understanding the iterative nature among the budget’s key components. 12 videos2 readings4 assignments After establishing goals, setting targets, and the budget, upper management uses variance analysis to compare, assess, and investigate differences between actual and expected performance. In this module, you will learn how upper management uses variance analysis to motivate and monitor managers and employees, how to perform variance analysis on any aspect of the organization, and ultimately understand the power of this important tool for planning and control. 10 videos2 readings5 assignments Accountants help implement, communicate, and evolve organizational strategy via the information they provide to owners, managers, and employees. Specifically, they help plan, monitor, and control decisions via the performance measurement, evaluation, and compensation system. In this module, you will explore many aspects of this important system, including decentralization, financial and non-financial performance measurement, strategic performance measurement systems, and subjective performance evaluation. 10 videos2 readings3 assignments

4 modules

Beginner level

17 hours to complete (3 weeks at 5 hours a week)

https://www.coursera.org/learn/financial-analysis-of-scenarios-and-decisions

Exam Prep: AWS Certified Cloud Practitioner Foundations

22,430

4.6

Morgan Willis

Amazon Web Services

['Cloud Computing', 'AWS cloud']

This new foundational-level course from Amazon Web Services (AWS), is designed to help you to assess your preparedness for the AWS Certified Cloud Practitioner certification exam. You will learn how to prepare for the exam by exploring the exam’s topic areas and how they map to both AWS Cloud practitioner roles and to specific areas of study. You will review sample certification questions in each domain, practice skills with hands-on exercises, test your knowledge with practice question sets, and learn strategies for identifying incorrect responses by interpreting the concepts that are being tested in the exam. At the end of this course you will have all the knowledge and tools to help you identity your strengths and weaknesses in each certification domain areas that are being tested on the certification exam. The AWS Certified Cloud Foundations Certification the AWS Certified Cloud Practitioner (CLF-C01) exam is intended for individuals who can effectively demonstrate an overall knowledge of the AWS Cloud independent of a specific job role. The exam validates a candidate’s ability to complete the following tasks: Explain the value of the AWS Cloud, Understand and explain the AWS shared responsibility model, understand security best practices, Understand AWS Cloud costs, economics, and billing practices, Describe and position the core AWS services, including compute, network, databases, and storage and identify AWS services for common use cases Welcome to Exam Prep: AWS Certified Cloud Practitioner! In this course, we present content on all four knowledge domains that are covered in the exam. It's important to understand that on the exam, questions from all domains are presented in random order. In this week, you will get an overview of relevant concepts and services for Cloud Concepts (Domain 1). For this domain, question walkthroughs cover defining the benefits of the AWS Cloud, aspects of AWS Cloud economics, and explaining the different design principles for cloud architecture. In addition, this week features a simulation where you explore the AWS Management Console and navigate through helpful places to find information. 8 videos4 readings2 plugins Welcome to Week 2! This week, you will review relevant concepts and services for Security and Compliance (Domain 2) so you can get a benchmark of your knowledge in this area. Question walkthroughs for this domain address the topics of defining the AWS shared responsibility model, defining concepts about AWS Cloud security and compliance, and identifying capabilities for AWS access management. In the simulation for the Security and Compliance domain, you get an opportunity to understand the purpose of user and identity management by reviewing AWS Identity and Access Management (IAM) groups, users, roles, and policies. 9 videos2 readings Welcome to Week 3! This week, you will get an overview of relevant concepts and services for Technology (Domain 3) so you can get a benchmark of your knowledge in this area. For this domain, the question walkthroughs focus on defining methods of deploying and operating in the AWS Cloud, defining the AWS global infrastructure, and identifying the core AWS services. This week features an optional, hands-on exercise for the Technology domain, where you will create an Amazon Elastic Compute Cloud (Amazon EC2) instance and an Amazon Elastic Block Store (Amazon EBS) volume. You will then create an Amazon Machine Image (AMI) from the instance. Finally, you will terminate the instance and clean up any volumes or snapshots that remain. An accompanying video walkthrough shows one possible solution for addressing the exercise requirements. 11 videos2 readings Welcome to Week 4! This week, you will review relevant concepts and services on Billing and Pricing (Domain 4) so you can get a benchmark of your knowledge in this area. The question walkthroughs for this domain compare the various pricing models for AWS, review the various account structures in relation to AWS billing and pricing, and identify resources available for billing support. In this week’s optional exercise, you will create an Amazon Simple Storage Service (Amazon S3) bucket that is configured to block all public access. You will then upload an object to verify that your access is blocked. Finally, you will make the object public, and then verify that you can view it. This week also includes a practice assessment that includes questions from all exam domains. 11 videos3 readings1 assignment1 plugin

4 modules

Beginner level

9 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/cloud-practitioner-exam-prep

Bulletproof 1. Accepting rejection

Enrollment number not found

Rating not found

Nathaniel Powers

SAE Institute México

[]

Describe the various manifestations and effects of rejection, understanding its transformative potential as a catalyst for personal growth, and develop skills to manage it constructively, applying strategies to ultivate resilience and grace, as well as cognitive and affective skills to face challenges with confidence. Introduction to Bulletproof 1 video2 readings1 discussion prompt Lesson 1: Accepting Rejection 2 videos1 reading1 assignment Practice & Evaluation 1 video2 readings1 assignment1 discussion prompt

3 modules

Beginner level

4 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/bulletproof-1-accepting-rejection

Machine Learning on Google Cloud Specialization

94,420

4.6

Google Cloud Training

Google Cloud

['Tensorflow', 'Machine Learning', 'Feature Engineering', 'Cloud Computing', 'Vertex AI']

What is machine learning, and what kinds of problems can it solve? How can you build, train, and deploy machine learning models at scale without writing a single line of code?  When should you use automated machine learning or custom training? This course teaches you how to build Vertex AI AutoML models without writing a single line of code; build BigQuery ML models knowing basic SQL; create Vertex AI custom training jobs you deploy using containers (with little knowledge of Docker); use Feature Store for data management and governance; use feature engineering for model improvement; determine the appropriate data preprocessing options for your use case; use Vertex Vizier hyperparameter tuning to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems, write distributed ML models that scale in TensorFlow; and leverage best practices to implement machine learning on Google Cloud. > By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at:https://qwiklabs.com/terms_of_serviceOpens in a new tab< Applied Learning Project This specialization incorporates hands-on labs using our Qwiklabs platform. These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google Cloud Platform products, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules. Describe Vertex AI Platform and how it's used to quickly build, train, and deploy AutoML machine learning models without writing any code Describe best practices for implementing machine learning on Google Cloud Leverage Google Cloud tools and environment to do ML Articulate Responsible AI best practices Describe how to improve data quality and perform exploratory data analysis Build and train AutoML Models using Vertex AI and BigQuery ML Optimize and evaluate models using loss functions and performance metrics Create repeatable and scalable training, evaluation, and test datasets Design and build a TensorFlow input data pipeline. Use the tf.data library to manipulate data in large datasets. Use the Keras Sequential and Functional APIs for simple and advanced model creation. Train, deploy, and productionalize ML models at scale with Vertex AI. Describe Vertex AI Feature Store and compare the key required aspects of a good feature. Perform feature engineering using BigQuery ML, Keras, and TensorFlow. Discuss how to preprocess and explore features with Dataflow and Dataprep. Use tf.Transform. Describe data management, governance, and preprocessing options Identify when to use Vertex AutoML, BigQuery ML, and custom training Implement Vertex Vizier Hyperparameter Tuning Explain how to create batch and online predictions, setup model monitoring, and create pipelines using Vertex AI

5 course series

Intermediate level

2 months (at 10 hours a week)

https://www.coursera.org/specializations/machine-learning-tensorflow-gcp

Intelligent Machining

29,612

4.6

Rahul Rai

University at Buffalo

[]

Manufacturers are increasingly utilizing machine tools that are self-aware – they perceive their own states and the state of the surrounding environment – and are able to make decisions related to machine activity processes. This is called intelligent machining, and through this course students will receive a primer on its background, tools and related terminology. Learn how the integration of smart sensors and controls are helping to improve productivity. You’ll be exposed to various sensors and sensing techniques, process control strategies, and open architecture systems that can be leveraged to enable intelligent machining. This course will prepare you to contribute to the implementation of intelligent machining projects. Main concepts of this course will be delivered through lectures, readings, discussions and various videos. This is the fifth course in the Digital Manufacturing & Design Technology specialization that explores the many facets of manufacturing’s “Fourth Revolution,” aka Industry 4.0, and features a culminating project involving creation of a roadmap to achieve a self-established DMD-related professional goal. To learn more about the Digital Manufacturing and Design Technology specialization, please watch the overview video by copying and pasting the following link into your web browser: https://youtu.be/wETK1O9c-CA The purpose of this module is to introduce the concepts related to intelligent machining paradigm. The key focus will be discussing two key components of intelligent machining, i.e., sensing and control. 4 videos4 readings4 assignments The purpose of this module is to introduce spectrum of sensors used to implement intelligent machining. The module will also discuss the basics of signal processing and analysis techniques that has brought intelligent machining paradigm closer to industrial realization. Following issues pertaining to sensors and sensing techniques will be elaborated up: (1) Which sensors are to be used in each application? (2) How to acquire and process sensor signals? 4 videos3 readings5 assignments1 discussion prompt The purpose of this module is to introduce the concept of Programmable Logic Controllers (PLCs) that co-ordinate the real-time control functions. 4 videos4 readings5 assignments The purpose of this module is to introduce the background related to open architecture software systems to implement intelligent machining. 3 videos5 readings2 assignments1 discussion prompt

4 modules

Beginner level

https://www.coursera.org/learn/intelligent-machining

96%

Preparing for the SAS® Viya® Programming Certification Exam

Enrollment number not found

Rating not found

Stacey Syphus

SAS

['CASL', 'Statistical Analysis System (SAS) (Software)', 'SAS Viya', 'SAS Programming', 'SAS Studio']

Welcome to the Preparing for the SAS Viya Programming Certification Exam course. This is the third and final course in the Coursera SAS Programmer specialization. You will apply what you have learned in the first two courses by writing code to execute in SAS Cloud Analytic Services and practicing for the SAS certification exams. This is an advanced course, intended for learners who have completed the first two courses in the Coursera SAS Programmer specialization: SAS Programming for Distributed Computing in SAS Viya and CASL Programming for Distributed Computing in SAS Viya. By the end of the course, you be prepared to take either of these SAS credential exams: - SAS® Viya® Programming Associate - SAS® Viya® Programming Specialist In this module you set up your practice data for this course. 2 videos2 readings1 app item In this module you practice you what you learned in the SAS Viya Programming course by using the software to complete programming tasks. 1 reading8 assignments1 app item In this module you practice what you learned in the CASL Programming course by using software to perform tasks. 1 reading7 assignments1 app item In this module you learn how to get certified in SAS Viya Programming and take one or both SAS Certification practice exams. 2 readings2 app items

4 modules

Advanced level

13 hours to complete (3 weeks at 4 hours a week)

https://www.coursera.org/learn/sas-viya-programming-certification-prep

Introduction to Network Automation

5,905

4.7

Cisco Learning & Certifications

Cisco Learning and Certifications

['Network Planning And Design', 'Python Programming', 'Python Scripting', 'network automation', 'Automation']

The Network infrastructure industry has undergone a significant transformation in recent years, with an increasing need for automation due to factors such as a demand for faster and more reliable network deployments. Therefore, there is a growing need for network engineers skilled in automation and programmability. This course is primarily intended for network engineers, systems engineers, network architects, and managers interested in learning the fundamentals of network automation. By the end of the course, you will be able to: - Articulate the role network automation and programmability plays in the context of end-to-end network management and operations. - Interpret Python scripts with fundamental programming constructs built for network automation use cases. To be successful in this course, you should be proficient in fundamental network routing & switching technologies, understand the basics of Python programming (3-6 mos exp.), and have some familiarity with Linux. In this module, we will review the topics and what you will learn in this course. 1 video2 readings Network operations have not changed in decades. For years, the console, Telnet, and Secure Shell (SSH) along with the CLI were the primary methods for managing and operating networks of any size. With the rise of programmatic interfaces on network devices and the growing need for enhanced reliability, assurance, and predictability, network operations are now in the midst of a radical shift in how devices are deployed and operated. This section reviews how devices have been managed historically and provides a glimpse into the future of network operations. 7 videos14 readings7 assignments Network automation is the future of network operation. Today, network engineers need to know how to interact with their network devices using application programming interfaces (APIs) and programmatic interfaces, and at a minimum, they must understand some fundamentals of coding. In this section, you will explore a programming language that is widely used in network automation—Python. You will start by learning different data types that Python supports, and then learn the differences between modules and packages and how to use them to your benefit. Next, you will learn about a module that lets you interact with devices with code. Finally, you will create your own module and interact with the code inside it. 6 videos7 readings5 assignments

3 modules

Intermediate level

2 hours to complete

https://www.coursera.org/learn/introduction-to-network-automation

Satellite Remote Sensing Data Bootcamp With Opensource Tools

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['Google Earth Engine', 'Geospatial Analysis', 'Remote Sensing', 'QGIS, R Programming', 'Google Earth Engine', 'Data Bootcamp']

Explore the dynamic world of satellite remote sensing data through a comprehensive bootcamp that equips you with essential skills using open-source tools. Beginning with the fundamentals, you'll be introduced to the core concepts of remote sensing, including various data types and the tools essential for their analysis, such as R and QGIS. As you progress, you will delve into the intricacies of optical remote sensing, learning to download, preprocess, and interpret Landsat data while mastering tools like the Semi-Automatic Classification Plugin in QGIS. The course then guides you through more advanced topics, including the many uses of optical data for various indices and transformations, using a range of tools like GRASS GIS, ESA SNAP, and R. You will explore critical processes such as texture indices, tasseled cap transformations, and dimension reduction, ensuring a thorough understanding of how to handle and manipulate data for your specific geospatial needs. Each section builds upon the last, culminating in the application of machine learning techniques to classify remote sensing satellite data. To round out your expertise, the course introduces active remote sensing with Synthetic Aperture Radar (SAR). You'll learn the practical aspects of obtaining and preprocessing ALOS PALSAR data, filtering for speckles, and deriving valuable backscatter information. By the end of this bootcamp, you'll be fully equipped to analyze and interpret both optical and SAR data, making you a valuable asset in the field of geospatial analysis. This course is ideal for geospatial professionals, environmental scientists, and data analysts looking to expand their expertise in satellite remote sensing. A basic understanding of GIS and remote sensing concepts is recommended but not required. In this module, we will lay the groundwork for your journey into satellite remote sensing data analysis. You'll begin by learning about the course structure, then explore the fundamentals of remote sensing, different data types, and the essential tools you will use throughout the course. By the end of this module, you'll have a solid understanding of the basics and be ready to dive deeper into the practical aspects of the field. 7 videos1 reading In this module, we will delve into the world of optical remote sensing data, starting with the fundamental principles that govern its collection. You'll examine the different types of optical data and how they are used, particularly focusing on Landsat data. Additionally, you'll explore the specifics of Landsat sensors and gain hands-on experience in using QGIS to download and view this data. By the end of this section, you'll be equipped with the knowledge and skills needed to work with optical remote sensing data in your analyses. 6 videos In this module, we will focus on the crucial steps involved in pre-processing optical remote sensing data. You'll learn why pre-processing is essential, particularly for improving data accuracy. The module will guide you through performing atmospheric correction on Landsat data using R, and introduce you to the Semi-Automatic Classification Plugin in QGIS for efficient pre-processing. Additionally, you'll assess the quality of atmospherically corrected outputs and explore the practical applications of pre-processed data. By the end of this section, you'll have the skills to refine raw satellite data for meaningful analysis. 6 videos1 assignment In this module, we will explore the diverse applications of optical remote sensing data across various analytical processes. You'll begin by mastering band manipulation in QGIS, followed by the application of band math to derive critical insights. The module will introduce you to texture indices and tasseled cap transformations, offering both theoretical knowledge and practical implementation using GRASS GIS and ESA SNAP. Additionally, you'll delve into vegetation indices and learn how to reduce data dimensionality for more efficient analysis. By the end of this section, you'll be well-versed in multiple advanced techniques for leveraging optical data in your projects 13 videos In this module, we will delve into the classification of remote sensing satellite data, covering both unsupervised and supervised methods. You’ll begin by exploring the theory behind these approaches, followed by practical applications using ESA SNAP and QGIS. The module also introduces machine learning concepts and their integration into remote sensing classification, guiding you through creating training data and applying advanced algorithms to satellite imagery. By the end of this section, you’ll be equipped with comprehensive skills to classify and analyze remote sensing data accurately and efficiently 9 videos In this module, we will explore active remote sensing data, focusing on Synthetic Aperture Radar (SAR). You'll begin by understanding the reasons for using active remote sensing over passive methods, with a particular emphasis on SAR technology. The module will guide you through the process of obtaining ALOS PALSAR data and applying essential pre-processing steps. You'll also learn to filter speckles from SAR imagery to improve data quality, and finally, you'll extract back-scatter values, a critical step for interpreting SAR data. By the end of this section, you'll have a solid foundation in working with active remote-sensing data 5 videos2 assignments

6 modules

Intermediate level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/packt-satellite-remote-sensing-data-bootcamp-with-opensource-tools-ny19m

Think like a CFO Specialization

18,819

4.8

Marc Badia

IESE Business School

['Bonds', 'Corporate Finance', 'Dividend Policy', 'Market Efficiency', 'Stocks', 'Dupont Analysis', 'Management Accounting', 'Business Analysis', 'Finance', 'Financial Accounting', 'Accounting', 'Financial Statement']

The Think like a CFO Specialization will help you learn the language of finance. You will gain a firm understanding in Accountability, Operational Finance and Corporate Finance. By the end of the specialization, you’ll know what questions to ask and how to fit the different pieces together in order to develop a diagnosis and action plan to resolve a company’s financing dilemmas. You will have gain the necessary skills to understand basic concepts and feel comfortable reading, interpreting and discussing financial statements for decision making and you will understand the hey financial issues related to companies, investors, and the interaction between them in the capital markets. When you complete the Specialization, you’ll be able to better understand both business financial problems to make better decisions and your own personal financial decisions Applied Learning Project Learners will need to complete a Quiz of 25 questions related to Principles of Accountability, Operational Finance and Corporate Finance Essentials. Additionally, the students will have to prepare a Cash Flow Statement. Before responding to the quiz, please make sure that you review all the essential concepts and materials showed through the 4 courses that conform the Specializacion. You will need to reach a 80% of correct responses in order to be able to get the Certificate. Financial Accounting is often called the language of business; it is the language that managers use to communicate the firm's financial and economic information to external parties such as shareholders and creditors. Nobody working in business can afford financial illiteracy. Whether you run your own business, work as a manager or are just starting your career, you want to understand financial information and be able to interact with accountants, controllers, and financial managers. You want to talk business! This course will provide you with the accounting language's essentials. Upon completion, you should be able to read and interpret financial statements for business diagnosis and decision-making. More importantly, you will possess the conceptual base to keep learning more sophisticated accounting and finance on your own. Do not forget that, as with any other language, becoming proficient with accounting requires constant practice. When it comes to numbers, there is always more than meets the eye. In operational finance, you will learn how to read the “story” that the balance sheet and income statement tells about the company’s operations. The insights you gain from this “financial story” will then become a tool for short-term decision-making at the top management level relating to current assets, current liabilities and the management of working capital. Finally, by the end of the course you will understand the financial consequences of managerial decisions on operations, marketing, etc. Corporate Finance Essentials will enable you to understand key financial issues related to companies, investors, and the interaction between them in the capital markets. By the end of this course you should be able to understand most of what you read in the financial press and use the essential financial vocabulary of companies and finance professionals.

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/thinklikeacfo

Healthcare Organizations and the Health System

25,614

4.6

Margaret Kilduff, Ph.D.

Rutgers the State University of New Jersey

['Public Health and Wellness Healthcare Organization Operations', 'Pharmacy Healthcare Organization Operations', 'Healthcare Administration', 'Medical Healthcare Organization Operations']

Have you ever been in a healthcare waiting room and thought about how the organization could be more efficient? For example, have you found yourself thinking about how to reduce the amount of time spent waiting? Or do you work in a healthcare organization and find yourself thinking about how to improve the organization? If you have, this course is for you. Course content includes an overview of healthcare organizations, their administration and management, and their governance. The course provides links to external sites to connect you to the larger "real world" of healthcare organizations. The links also serve as resources you can take with you after you complete the course experience. And because everyone loves a road trip/field trip, there are also "virtual field trips" to the often hidden places of interest on the web. The course format is readings, videos, quizzes, and an electronic poster project. The poster project requires you to synthesize course material to design a healthcare organization and governance structure the way you would have things run in the best of all worlds. The electronic poster file is an artifact of the course which you can circulate to colleagues or use for a talk or presentation event. This lesson provides an overview of the course as well as an overview of healthcare organizations and the health system. 15 readings2 assignments1 peer review4 discussion prompts6 plugins This lesson provides an overview of healthcare administration and management. 9 readings1 assignment2 peer reviews2 discussion prompts6 plugins This lesson provides an overview of organizational governance and functions. 9 readings1 assignment3 peer reviews2 discussion prompts6 plugins This lesson is a synthesis of the course material to design and present a healthcare organization and governance structure the way you would have things run in the best of all worlds. 8 readings2 assignments1 peer review4 discussion prompts5 plugins

4 modules

Beginner level

https://www.coursera.org/learn/healthcare-organizations-health-system

98%

Mathematics for Engineers Specialization

21,050

4.9

Jeffrey R. Chasnov

The Hong Kong University of Science and Technology

['Matrix Algebra', 'Differential Equations', 'Vector Calculus', 'Numerical Analysis', 'Computational Fluid Dynamics (CFD)']

This specialization was developed for engineering students to self-study engineering mathematics. We expect students to already be familiar with single variable calculus and computer programming. Through this specialization, students will learn matrix algebra, differential equations, vector calculus, numerical methods, and MATLAB programming. This will provide them with the tools to effectively apply mathematics to engineering problems and to become well-equipped to pursue a degree in engineering. To get a better understanding of what this specialization has to offer, be sure to watch thePromotional VideoOpens in a new tab! Applied Learning Project Learners will write MATLAB programs to solve the computational fluid dynamics problem of the flow around a cylinder. At the end of the "Mathematics for Engineers: The Capstone Course", learners will be able to compute the iconic Kármán vortex street. To watch a video of the Kármán vortex street, you can watch the following video:https://youtu.be/FlM1de9Sxh0Opens in a new tab Matrices Systems of Linear Equations Vector Spaces Eigenvalues and eigenvectors First-order differential equations Second-order differential equations The Laplace transform and series solution methods Systems of differential equations and partial differential equations Vectors, the dot product and cross product The gradient, divergence, curl, and Laplacian Multivariable integration, polar, cylindrical and spherical coordinates Line integrals, surface integrals, the gradient theorem, the divergence theorem and Stokes' theorem MATLAB and Scientific Computing Root Finding and Numerical Matrix Algebra Quadrature and Interpolation Numerical Solution of Ordinary and Partial Differential Equations Computational Fluid Dynamics Scientific Computing

5 course series

Beginner level

3 months (at 10 hours a week)

https://www.coursera.org/specializations/mathematics-engineers

Strategic Brand Management

Enrollment number not found

Rating not found

Dr. Ashita Aggarwal

S.P. Jain Institute of Management and Research

['Tools to Define Positioning', 'Brand Valuation', 'Brand and Branding', 'Brand Portfolio and Brand Roles', 'Integrated Brand Experience', 'Brand Extensions', 'Brand Architecture & Relationships']

Welcome to the world of strategic brand management, where you'll explore the art and science of creating, maintaining, and enhancing powerful brands. This course offers a comprehensive guide to mastering the principles of brand management, transforming it into more than just a valuable skill. Gain essential knowledge and tools to build strong brands, differentiate in competitive markets, and drive business success. This course is designed for a wide range of individuals, including business professionals, brand managers, marketing enthusiasts, students, or simply curious learners eager to delve into the dynamics of branding. This course will provide you with strategic brand management tools to gain a competitive edge. It will enable leveraging advanced techniques and practical frameworks applicable to real-world branding scenarios. Upon completing this course, you will: 1. Understand and appreciation of the role of brands in in creating business and shareholder value. 2. Develop understanding of frameworks and concepts that can help in brand planning and execution. 3. Enhance the ability to plan and execute impactful brand strategies. 4. Think critically about the strategies and tactics involved in building, managing, leveraging, and sustaining strong brands. The course covers essential topics such as defining brand identity, the role of branding across different sectors, and the importance of brand design elements. You will also learn about brand differentiation, positioning, and how to sustain a brand's position in the market. Furthermore, the course delves into brand portfolio and architecture, providing a comprehensive understanding of brand extensions and their potential impact. Join us to unlock the full potential of strategic brand management and drive your success in the competitive business world. The module gives an introduction to the world of brands and why branding is important to create value for stakeholders and business. The module will also highlight the role of brands in driving business valuation and hence their importance in company strategy. 17 videos5 readings5 assignments2 discussion prompts The module focuses on the importance of creating differentiation and focus. In the competitive environment, brands that are differentiated are preferred and remembered, and hence, brand positioning plays a key role in building brand equity. 10 videos3 readings4 assignments1 discussion prompt This module focuses on strategic choices around building the brand architecture and managing the portfolio. Brands are assets that can be leverged to grow and expand business. When a business has multiple brands in its portfolio, it requires a well thpough through systematic approach to structure the portfolio and explore opportunities for exaqpnding into new territories 10 videos3 readings4 assignments This module deals with brand storytelling and creating an experience for the customer, which will helps brands remain in customers' consideration portfolio. Consumers today absorb and process information through all senses and through multiple channels and hence the brands need to communicate their differentiation across channels and by incorporating multiple senses. 8 videos3 readings4 assignments Launching and building a successful brand is only the first step in the brand's journey. Brand managers must have a strategic plan to grow, nurture, and maintain brands over a period of time. As business contexts and consumers evolve, brands also need to evolve their strategy and execution plan. This module explores the focus areas and strategic alternatives, brand managers can analyze to sustain value over a period of time acorss differetn stages in the brand's life cycle. 9 videos3 readings4 assignments This module would cover the concepts of brand audit, measuring brand equity to maintain a healthy P&L. We will also try to understand the various methods of brand valuation which is key ingredient in driving business growth and stakeholder value. 9 videos4 readings4 assignments

6 modules

Beginner level

33 hours to complete (3 weeks at 11 hours a week)

https://www.coursera.org/learn/strategic-brand-management-

Product Management: An Introduction

36,800

4.6

Matt Versdahl

IBM

['Product Management', 'Value Proposition', 'Product manager', 'Product Management Lifecycle', 'ProdBOK']

In today’s fast-changing global market, companies need skilled product managers to develop breakthrough products or to expand their existing offerings. By the end of this course, you will understand what a product manager does in their role and the skills you need to become one. This introductory course is a valuable investment for those looking to start a career in product management. Learn key product management concepts such as the product lifecycle, personas, value creation, and SWOT analysis. Gain an understanding of the job opportunities in product management and the industry-standard Guide to the Product Management Body of Knowledge, ProdBoK®. The hands-on labs provide opportunities to investigate product management in simulated real-world settings. You’ll hear from industry experts discussing their points of view, so you learn about their first-hand experiences. This course is the first in a series of courses, which, once completed, will earn you the IBM Product Management Professional Certificate. Anyone can take this beginner-level course, which does not require any prior Product Management skills or background. In this module, you will learn about the role of the product manager and the key skills that are important for success. You will learn about a product manager's responsibilities and persona. You will also list the skills, knowledge, and business acumen required to be an effective product manager. 10 videos2 readings2 assignments1 discussion prompt5 plugins In this module, you will be introduced to product and product management. You will learn about what a product is and what a typical day in the life of a product manager looks like. You will also learn which personality traits are most critical for a product manager, what the role of a product manager looks like in an organization, and what kind of challenges the product managers face. Next, you will focus on the life cycle of a product. You will learn about the four phases of the product lifecycle, the seven-step product management lifecycle, and the key deliverables of the product management life cycle. You will also learn about the most critical tasks product managers accomplish, the key functional area expertise that they must have, and the key roles and stakeholders they must collaborate with. 13 videos1 reading3 assignments1 discussion prompt6 plugins In this module, you will learn about the fundamental concepts of product management. It focuses on value creation. You will learn about value creation and entrepreneurship and the connection between a product manager and an entrepreneur. You will also learn about critical thinking and the product manager. It also introduces you to the product management and marketing body of knowledge or ProdBOK. It has a practice quiz on product management opportunities. It also focuses on the link between portfolio management and project management. You will learn about the portfolio approach, its benefits and challenges, and the challenges to develop a product strategy effectively. You will also learn where the roles of a product manager and project manager intersect. It also covers project management’s predictive and adaptive lifecycles and a product manager’s role. 11 videos1 reading3 assignments1 discussion prompt5 plugins In this module, you will explore the product management opportunities and certifications. It summarizes the current employment opportunities in today’s work environment and covers the Product Management and Marketing Body of Knowledge (ProdBOK) and the Association of International Product Marketing and Management (AIPMM). You will also learn about the best way to prepare for a product manager role and the background experience required to become a product manager. It also covers certifications and resume building. You will learn about the certificates available in the product management career. 4 videos1 reading2 assignments1 discussion prompt4 plugins Welcome to Module 5. This module introduces your final project. You will analyze a product management scenario, after that, you are expected to give a retrospective of the team's successes and areas of improvement related to the product development team. Additionally, you will attempt a 25-question graded quiz to assess your comprehension of the key concepts taught in the course. We end the module with our congratulations and recommend the next steps to continue your product management journey. 2 readings1 assignment2 plugins

5 modules

Beginner level

https://www.coursera.org/learn/product-management-an-introduction

98%

Earth Economics

10,693

4.6

Peter A.G. van Bergeijk

Erasmus University Rotterdam

['Policy Analysis', 'Policy Development', 'Data Analysis', 'Earth Economics']

After this course you will be an Earth Economist that can provide evidence-based advise on the best global policy. As an Earth Economist you will better understand the behavior and advice of economists, have become a better economist yourself and know where to find Earth's data and how to analyze these world observations. Our planet is too important: we need you to get engaged! Earth Economics offers a completely new angle to policy analysis by its focus on the truly global level and its empirical orientation on very recent data. Sustainability (environmental and related to the UN's SDGs), equality and heterodox (that is: non mainstream) views on the economy are important for an Earth Economist. Taking stock of emerging planet data and analyzing policies during and following the Global Crisis, Earth Economics provides both a topical introduction into basic economic tools and concepts as well as insights in highly relevant problems and recent developments in planet production, growth and governance. An important issue is the provision of global public goods. Earth Economics highlights the importance of the United Nations, International Monetary Fund, the World Health Organization and the World Trade Organization. Earth Economics offers a completely new angle to policy analyses by its focus on the truly global level and its empirical orientation on very recent data. Each week offers "Reflections on the economic impact of the Corona virus" (COVID-19) allowing you to apply what you have learned. But we have to look beyond the pandamic. Sustainability (environmental and related to the UN's SDGs), equality and hetrodox (non mainstream) views on the economy are important for an Earth Economist. Taking stock of emerging planet data and analyzing policies during and following the Global Crisis, Earth economics provides both a topical introduction into basic macroeconomic tools and concepts and insights in highly relevant problems and recent developments in planet production, growth and governance. You will also better understand the behavior and advice of economists, become a better economist and know where to find Earth's data and how to analyse these world observations. Our planet is too important: we need you to get engaged! 2 videos3 readings1 assignment1 discussion prompt This set of three lectures provides you with a good introduction to the most often used data sources for the Earth Economy and their strengths and weaknesses. We study which activities generate value added and discuss both the merits and the drawbacks of the concept of Gross Planet Product (GPP). We will get a good idea about changes in the economic condition of our planet, both from business cycles and from changes in the world's unemployment rate. You will discover that economists are too optimistic about the reliability of their data but also that economist in the past have been too pessimistic about the development of the world economy. 6 videos7 readings1 assignment1 discussion prompt We start with a discussion of the equilibrium concept and relate (in)stability to policy relevant questions such as (over)population, global warming and hyperinflation. We encounter comparative statics and scenario analysis. We discuss investment, saving and consumption and relate these concepts to the development of the Earth economy. At the end of these three lectures you will be able to build a model of the Earth economy and use that model to analyze the Great Recession of 2008/0. That is pretty cool. 7 videos7 readings2 assignments In this Module we take a closer look at government. We study government spending and taxation and will discover any instances where government expenditures and receipts move in the same direction. An important issue is the development of public debt that has reached unprecedented levels for our planet. Finally we study money and its functions in the Earth Economy. 6 videos7 readings1 assignment In this module we look at the money market and the role and impact of monetary policy. We start with the liquidity trap where interest rates are so low that monetary policy becomes impotent. Next we relate the money market and the product market in the so-called ISLM model. We use this model to shed light on economic debates about the role of government. 5 videos6 readings1 assignment Earth Economics is especially relevant when we take a look at the long run because it enables us to analyse sustainability of economic processes and to understand how productivity is key for economic development. We will discover why Earth Economics is important for monitoring and understanding Sustainable Development Goals from a truly global perspective 5 videos6 readings2 assignments1 peer review

6 modules

Beginner level

20 hours to complete (3 weeks at 6 hours a week)

https://www.coursera.org/learn/earth-economics

Convolutional Neural Networks in TensorFlow

153,906

4.7

Laurence Moroney

DeepLearning.AI

['Tensorflow', 'Convolutional Neural Network', 'Transfer Learning', 'Machine Learning', 'Dropouts', 'Data Augmentation']

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the DeepLearning.AI TensorFlow Developer Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In Course 2 of the DeepLearning.AI TensorFlow Developer Specialization, you will learn advanced techniques to improve the computer vision model you built in Course 1. You will explore how to work with real-world images in different shapes and sizes, visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including augmentation and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization. In the first course in this specialization, you had an introduction to TensorFlow, and how, with its high level APIs you could do basic image classification, and you learned a little bit about Convolutional Neural Networks (ConvNets). In this course you'll go deeper into using ConvNets with real-world data, and learn about techniques that you can use to improve your ConvNet performance, particularly when doing image classification! In Week 1, this week, you'll get started by looking at a much larger dataset than you've been using thus far: The Cats and Dogs dataset which had been a Kaggle Challenge in image classification! 8 videos8 readings1 assignment1 programming assignment1 ungraded lab You've heard the term overfitting a number of times to this point. Overfitting is simply the concept of being over specialized in training -- namely that your model is very good at classifying what it is trained for, but not so good at classifying things that it hasn't seen. In order to generalize your model more effectively, you will of course need a greater breadth of samples to train it on. That's not always possible, but a nice potential shortcut to this is Image Augmentation, where you tweak the training set to potentially increase the diversity of subjects it covers. You'll learn all about that this week! 7 videos4 readings1 assignment1 programming assignment2 ungraded labs Building models for yourself is great, and can be very powerful. But, as you've seen, you can be limited by the data you have on hand. Not everybody has access to massive datasets or the compute power that's needed to train them effectively. Transfer learning can help solve this -- where people with models trained on large datasets train them, so that you can either use them directly, or, you can use the features that they have learned and apply them to your scenario. This is Transfer learning, and you'll look into that this week! 7 videos4 readings1 assignment1 programming assignment1 ungraded lab You've come a long way, Congratulations! One more thing to do before we move off of ConvNets to the next module, and that's to go beyond binary classification. Each of the examples you've done so far involved classifying one thing or another -- horse or human, cat or dog. When moving beyond binary into Categorical classification there are some coding considerations you need to take into account. You'll look at them this week! 6 videos7 readings1 assignment1 programming assignment1 ungraded lab

4 modules

Intermediate level

https://www.coursera.org/learn/convolutional-neural-networks-tensorflow

96%

Preparing for Google Cloud Certification: Machine Learning Engineer Professional Certificate

49,197

4.5

Google Cloud Training

Google Cloud

['Tensorflow', 'Bigquery', 'Machine Learning', 'Data Cleansing', 'Cloud Computing', 'Python Programming', 'keras', 'Build Input Data Pipeline', 'Tensorflow', 'Bigquery', 'Machine Learning', 'Data Cleansing', 'Cloud Computing', 'Python Programming', 'keras', 'Build Input Data Pipeline']

87% of Google Cloud certified users feel more confident in their cloud skills. This program provides the skills you need to advance your career and provides training to support your preparation for the industry-recognizedGoogle Cloud Professional Machine Learning EngineerOpens in a new tabcertification. Here's what you have to do 1) Complete the Preparing for Google Cloud Machine Learning Engineer Professional Certificate 2) Review other recommended resources for theGoogle Cloud Professional Machine Learning EngineerOpens in a new tabexam 3) Review theProfessional Machine Learning Engineer exam guideOpens in a new tab 4) CompleteProfessional Machine Learning EngineerOpens in a new tabsample questions 5)RegisterOpens in a new tabfor the Google Cloud certification exam (remotely or at a test center) Applied Learning Project This professional certificate incorporates hands-on labs using Qwiklabs platform.These hands on components will let you apply the skills you learn. Projects incorporate Google Cloud Platform products used within Qwiklabs. You will gain practical hands-on experience with the concepts explained throughout the modules. Applied Learning Project This specialization incorporates hands-on labs using Google's Qwiklabs platform. These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google Cloud Platform products, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules. Recognize the data-to-AI technologies and tools offered by Google Cloud. Use generative AI capabilities in applications. Choose between different options to develop an AI project on Google Cloud. Build ML models end-to-end by using Vertex AI. Describe how to improve data quality and perform exploratory data analysis Build and train AutoML Models using Vertex AI and BigQuery ML Optimize and evaluate models using loss functions and performance metrics Create repeatable and scalable training, evaluation, and test datasets Design and build a TensorFlow input data pipeline. Use the tf.data library to manipulate data in large datasets. Use the Keras Sequential and Functional APIs for simple and advanced model creation. Train, deploy, and productionalize ML models at scale with Vertex AI. Describe Vertex AI Feature Store and compare the key required aspects of a good feature. Perform feature engineering using BigQuery ML, Keras, and TensorFlow. Discuss how to preprocess and explore features with Dataflow and Dataprep. Use tf.Transform. Describe data management, governance, and preprocessing options Identify when to use Vertex AutoML, BigQuery ML, and custom training Implement Vertex Vizier Hyperparameter Tuning Explain how to create batch and online predictions, setup model monitoring, and create pipelines using Vertex AI Compare static versus dynamic training and inference Manage model dependencies Set up distributed training for fault tolerance, replication, and more Export models for portability Identify and use core technologies required to support effective MLOps. Adopt the best CI/CD practices in the context of ML systems. Configure and provision Google Cloud architectures for reliable and effective MLOps environments. Implement reliable and repeatable training and inference workflows. In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. You will learn about pipeline components and pipeline orchestration with TFX. You will also learn how you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata. Then we will change focus to discuss how we can automate and reuse ML pipelines across multiple ML frameworks such as tensorflow, pytorch, scikit learn, and xgboost. You will also learn how to use another tool on Google Cloud, Cloud Composer, to orchestrate your continuous training pipelines. And finally, we will go over how to use MLflow for managing the complete machine learning life cycle. Please take note that this is an advanced level course and to get the most out of this course, ideally you have the following prerequisites: You have a good ML background and have been creating/deploying ML pipelines You have completed the courses in the ML with Tensorflow on GCP specialization (or at least a few courses) You have completed the MLOps Fundamentals course. >>> By enrolling in this course you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service <<<

8 course series

Intermediate level

2 months (at 10 hours a week)

https://www.coursera.org/professional-certificates/preparing-for-google-cloud-machine-learning-engineer-professional-certificate

Container and Container Orchestration Fundamentals

Enrollment number not found

Rating not found

LearnKartS

LearnKartS

['Microservices', 'Container Management', 'Docker Swarm', 'Docker (Software)']

Welcome to the Container and Container Orchestration Fundamentals course! The course aligns with the Certified Kubernetes Application Developer certification exam preparation. This course will introduce you to essential concepts and practical skills essential for working with containers and container orchestration technologies. The course is specifically designed for developers, software engineers, and DevOps professionals who work with Kubernetes and want to showcase their skills in deploying and managing applications This course needs a good understanding of Linux. By the end of this course, you will be able to: - Understand the fundamentals of microservices, virtualization, and containerization. - Master Docker installation, container deployment, and networking. - Explore container orchestration using Docker Swarm and Kubernetes. - Gain practical experience through hands-on demos and real-world scenarios. This course contains engaging videos, readings, and knowledge checks for a high-quality learning experience. This module explores microservices and containerization, covering topics like their significance, Docker and Kubernetes. By the end of the module, learners will understand and deploy advanced containerization with Docker and Kubernetes. 13 videos4 readings4 assignments1 discussion prompt This module covers Docker basics including installation and container management, and advanced topics like orchestration with Docker Swarm and Kubernetes. By the end of this module, learners will gain proficiency in deploying, managing, and orchestrating containers. 22 videos3 readings6 assignments1 discussion prompt

2 modules

Beginner level

5 hours to complete (3 weeks at 1 hour a week)

https://www.coursera.org/learn/ckad-container-and-container-orchestration-fundamentals

Social Network Analysis

15,988

4.7

Martin Hilbert

University of California, Davis

[]

This course is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. Humans are natural network scientists, as we compute new network configurations all the time, almost unaware, when thinking about friends and family (which are particular forms of social networks), about colleagues and organizational relations (other, overlapping network structures), and about how to navigate delicate or opportunistic network configurations to save guard or advance in our social standing (with society being one big social network itself). While such network structures always existed, computational social science has helped to reveal and to study them more systematically. In the first part of the course we focus on network structure. This looks as static snapshots of networks, which can be intricate and reveal important aspects of social systems. In our hands-on lab, you will also visualize and analyze a network with a software yourself, which will help to appreciate the complexity social networks can take on. During the second part of the course, we will look at how networks evolve in time. We ask how we can predict what kind of network will form and if and how we could influence network dynamics. In this module, you will be introduced to the concept of networks. You will be able to define networks and identify how data is transformed and analyzed in a network. You will able be able to discuss how to formalize networks. 8 videos2 readings1 assignment1 discussion prompt In this module, you will be able to discuss the structure of networks and be able to explain how a person can be the center of one. You will be able to discover the different types of language that networks use and be able to identify the three types of network measurements. 12 videos1 reading1 assignment In this module, you will begin with a social network analysis lab activity. You will be able to do data wrangling of databases and visualize a network. You will be able to analyze a social network and also be able to examine other social network analysis through case studies. 9 videos4 readings1 assignment1 peer review In this module, you will be able to identify the different types of social networks. You will be able to discuss what mechanisms generates these different types of networks and you will be able to explain how networks move from being static to dynamic. 8 videos1 assignment In this module, you will be able to examine theoretical predictions of networks. You will be able to calculate basic math problems and be able to discuss how to make networks more efficient and stable. 9 videos1 assignment1 discussion prompt

5 modules

Beginner level

10 hours to complete (3 weeks at 3 hours a week)

https://www.coursera.org/learn/social-network-analysis

Project Management Project

72,473

4.8

Margaret Meloni, MBA, PMP

University of California, Irvine

['Schedule', 'Project Management', 'Risk Management', 'Budget']

This capstone project is designed to allow you to take the knowledge you have gained through the Specialization and put that knowledge into practice. In the capstone, you will create several of the key planning deliverables that have been discussed in these courses and either work on a project you choose or use a suggested case study. You will begin the capstone project by writing part of the project charter. You will build on that information to define your project, and then ultimately create a schedule, budget and responses for the risks you identify. The goal is for you to use what you have learned in the previous courses and to perform your own research on how to best move forward with the capstone project. Your work will be peer reviewed by your classmates. In turn you will peer review the work of other classmates. Instructions on how to conduct peer reviews will be included in the course. Upon completing this series, you will be able to (1) write a narrative charter statement, (2) create a work breakdown structure, (3) sequence project activities,(4) build a project schedule, (5) create a project budget, (6) create a responsibility assignment matrix, (7) identify project risks and (8) define responses for those risks. Upon completing this course, you will be able to: 1. Write a narrative charter statement 2. Create a work breakdown structure 3. Sequence project activities 4. Build a project schedule 5. Create a project budget 6. Create a responsibility assignment matrix 7. Identify project risks and define responses for those risks This section will prepare you for your capstone project and final peer review. It will also answer any questions you might have about the project assignment, the grading rubric, and what you can expect in the upcoming weeks together. 2 videos5 readings This section will take you for a deep dive into each course objective that makes up the project components of the final assignment for the capstone course. It will include a description and directions for each component as well as grading rubrics to help prepare you for the upcoming Feedback Peer Review and Final Peer Review Assignment. 8 readings This section will provide review course content that you have seen in the Introduction to Project Management Principles and Practices Specialization in hopes of giving you a helping hand in preparing your final capstone project. 1 reading Join our new Applied Project Management Certificate program. This week, learn more about the program, requirements for PDU’s and Contact Hours from PMI®, and explore frequently asked questions of Coursera learners. 1 reading This section is learners who want to have additional feedback on their project assignment prior to the Final Peer Review submission and evaluation. 1 peer review This is your final peer review assignment submission portion of the course. Please be mindful that there will be no extension given to learners for any deadlines set. 1 peer review This is your final peer review assignment evaluation portion of the course. Please be mindful that there will be no extension given to learners for any deadlines set. 1 reading Let's wrap up our time together as we have traveled through the Introduction to Project Management Principles and Practices Specialization. 1 reading

8 modules

6 hours to complete (3 weeks at 2 hours a week)

https://www.coursera.org/learn/project-management-capstone

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