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Fundamentals of AI, Machine Learning, and Python Programming

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['neural networks', 'NumPy', 'Python programming', 'deep learning', 'TensorFlow']

Embark on a transformative learning experience designed to equip you with a robust understanding of AI, machine learning, and Python programming. This course begins with a thorough introduction to artificial intelligence and machine learning, demystifying the core concepts and exploring how algorithms and data-driven techniques empower computers to learn and adapt. As you progress, you'll delve into the architecture of deep learning and neural networks, grasping how these advanced structures mimic human cognition to process complex data and make accurate predictions. Transitioning from theory to practical application, the course guides you through setting up your development environment with Anaconda, laying the groundwork for efficient coding and package management. You'll then immerse yourself in Python programming, mastering flow control mechanisms, data structures, and functions. The journey continues with an exploration of essential Python libraries such as NumPy, Matplotlib, and Pandas, providing you with the tools to handle data manipulation and visualization effectively. The latter part of the course focuses on advanced AI topics, including the installation and application of deep learning libraries like TensorFlow and PyTorch. You'll learn about the fundamental structures of artificial neurons and neural networks, and the crucial roles of activation functions, loss functions, and optimizers in training models. Through hands-on projects, such as building regression models for house price prediction and binary classification models for heart disease prediction, you'll apply your knowledge to real-world scenarios, reinforcing your learning and enhancing your practical skills. This course is designed for aspiring data scientists, machine learning enthusiasts, and Python programmers. It is ideal for beginners seeking a comprehensive introduction to AI and machine learning, as well as professionals looking to deepen their understanding of these technologies. Prerequisites include basic programming knowledge and a keen interest in artificial intelligence and data science. In this module, we will provide a comprehensive introduction to the course. We’ll outline the key topics covered, focusing on deep learning, neural networks, and Generative Adversarial Networks (GANs). This overview will set the stage for your learning journey, giving you a clear roadmap of what to expect. 1 video2 readings In this module, we will introduce you to the fundamental concepts of artificial intelligence and machine learning. You will learn how AI and machine learning algorithms empower computers to learn, adapt, and make informed decisions based on data. 1 video In this module, we will delve into the basics of deep learning and neural networks. We’ll explore how these powerful models are structured and how they process complex data to make predictions, mimicking the way humans learn. 1 video1 assignment In this module, we will guide you through the process of setting up your computer by installing Anaconda. You will learn how to create isolated environments and manage packages, laying a solid foundation for your data science and machine learning projects. 1 video In this module, we will cover the essentials of Python flow control mechanisms. You will learn how to manipulate the sequence of code execution, using conditional statements and loops to manage the flow of your programs effectively. 2 videos In this module, we will explore the basics of Python lists and tuples. You will understand their properties and how they can be used to organize and manipulate data efficiently in your Python programs. 1 video1 assignment In this module, we will delve into Python dictionaries and functions. You will learn how to use dictionaries for dynamic data storage and how to create and utilize functions to streamline your code and improve efficiency. 2 videos In this module, we will introduce you to NumPy, a critical library for numerical computations in Python. You will learn how to create and manipulate multidimensional arrays, gaining tools to perform efficient data analysis. 2 videos In this module, we will explore the Matplotlib library for data visualization. You will learn how to transform data into insightful visual representations, using plots and histograms to better understand data distributions and patterns. 2 videos1 assignment In this module, we will dive into the Pandas library, focusing on its powerful data structures: series and data frames. You will learn how to leverage these tools for effective data analysis and manipulation. 2 videos In this module, we will guide you through installing essential deep learning libraries such as TensorFlow and PyTorch. You will learn how to set up these libraries, preparing you for your deep learning journey. 1 video In this module, we will explore the basic structure of artificial neurons and neural networks. You will learn about the building blocks of these models and how they work together to perform complex computations and pattern recognition. 1 video1 assignment In this module, we will introduce you to activation functions, which are crucial in shaping the outputs of neural networks. You will understand their role in the learning process and how they impact model performance. 1 video In this module, we will explore popular types of activation functions used in neural networks. You will learn how these functions drive information flow and affect the overall performance of your models. 1 video In this module, we will demystify popular loss functions used in training neural networks. You will learn about mean squared error, cross-entropy, and more, understanding how these functions help in refining model predictions. 1 video1 assignment In this module, we will unravel the world of popular optimizers. You will learn how various algorithms optimize the training of neural networks, improving model accuracy and efficiency. 1 video In this module, we will explore popular types of neural networks. You will learn about feedforward, convolutional, recurrent networks, and more, understanding their unique architectures and applications in machine learning and AI. 1 video In this module, we will begin the process of building a regression model to predict house prices in King County, USA. You will learn how to fetch and load datasets, setting the stage for effective data analysis and model training. 1 video1 assignment In this module, we will dive into exploratory data analysis (EDA) and data preparation. You will learn how to clean and transform data, ensuring it is ready for building accurate and effective machine learning models. 2 videos In this module, we will define the Keras model for our regression task. You will learn how to architect the model, setting up the input, hidden, and output layers to create a robust neural network. 2 videos In this module, we will compile and fit our Keras model. You will learn how to configure the model’s parameters and train it using the prepared dataset, optimizing its performance for accurate predictions. 1 video1 assignment In this module, we will focus on visualizing the training progress and metrics of our model. You will learn how to use graphs and plots to gain insights into model performance and make necessary adjustments for improvement. 1 video In this module, we will use our trained regression model to predict house prices. You will see the model in action, applying machine learning principles to real-world data and making accurate predictions. 1 video In this module, we will introduce the creation of a binary classification model for heart disease prediction. You will learn the importance of such models in healthcare and the steps involved in building one. 1 video1 assignment In this module, we will guide you through fetching and loading the necessary data for heart disease prediction. You will learn how to prepare the data, setting a solid foundation for building an effective classification model. 1 video In this module, we will delve into exploratory data analysis (EDA) and data preparation for our heart disease classification model. You will learn how to clean and transform the data, ensuring it is ready for model training. 2 videos In this module, we will define the architecture of our heart disease classification model. You will learn how to set up the neural network, configuring layers and activations for optimal performance. 1 video1 assignment In this module, we will compile, fit, and plot our heart disease classification model. You will learn how to train the model and visualize its performance using key metrics and plots. 1 video In this module, we will use our trained classification model to predict heart disease. You will see the model in action, applying machine learning principles to healthcare data and making accurate classifications. 1 video In this module, we will test and evaluate our heart disease classification model using new data. You will learn how to assess the model’s accuracy and refine it for better performance in predicting heart disease. 2 videos1 reading2 assignments

30 modules

Beginner level

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

https://www.coursera.org/learn/packt-keras-deep-learning-and-generative-adversarial-networks-gan-ilsxz

Lean Management Fundamentals

4,172

4.7

Kelley O'Connell

Starweaver

['Process Optimization', 'Leadership', 'Metrics Analysis', 'Kaizen', 'Visual Management']

The Lean Management Fundamentals course is designed to provide participants with a comprehensive understanding of Lean principles and practices. Lean management is a systematic approach that focuses on eliminating waste, optimizing processes, and creating value for customers. This course will equip participants with the knowledge and skills to apply Lean methodologies in their organizations, leading to improved efficiency, productivity, and customer satisfaction. Throughout the course, participants will learn the key concepts of Lean management and how to identify and eliminate waste in various business processes. They will explore different Lean tools and techniques, such as value stream mapping, 5S, Kaizen, and Kanban, and understand their application in process improvement. The course will also cover topics like Lean leadership, employee engagement, and creating a culture of continuous improvement. Through a deep exploration of real-world case studies, participants will acquire valuable insights into the challenges of implementing Lean methodologies and effective strategies for achieving success. This course equips attendees with the skills to analyze processes, pinpoint opportunities for improvement, and craft Lean solutions that optimize operations and bolster overall performance. Emphasizing the pivotal concept of continuous improvement, this program empowers participants with the tools and methodologies needed to drive enduring change within their organizations. This course is designed for business professionals, information technologists, product managers, business analysts, and anyone involved in defining, streamlining, and working within business, information technology, or manufacturing processes. There are no specific prerequisites for this course. A general understanding of business process definition and business concepts will be beneficial, but not mandatory. An eagerness to drive business growth will enhance the learning experience. The Lean Management Fundamentals course is designed to provide participants with a comprehensive understanding of Lean principles and practices. Lean management is a systematic approach that focuses on eliminating waste, optimizing processes, and creating value for customers. This course will equip participants with the knowledge and skills to apply Lean methodologies in their organizations, leading to improved efficiency, productivity, and customer satisfaction. 35 videos11 readings11 assignments3 discussion prompts

1 module

Beginner level

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

https://www.coursera.org/learn/lean-management-fundamental

Operations and Process Management

4,048

4.8

Jeffrey Berk

Illinois Tech

['Rate Of Return', 'Project Management', 'Action Plans', 'Risk Management', 'Change Management', 'Business Process Mapping', 'Performance Measurement', 'Performance Improvement', 'Continuous Improvement Process']

The course focuses on teaching students how to successfully analyze a business process, research methods of improving a process, and adapt/integrate the improvement. methods into the business process in a prioritized and actionable manner. The goal of the course is to expose students to a universal set of business processes and provide them with a formal approach to improving and monitoring the health of those processes that they can apply in a current or future opportunity. Welcome to Operations and Process Management! The course focuses on teaching students how to successfully analyze a business process, research methods of improving a process, and adapt/integrate the improvement methods into the business process in a prioritized and actionable manner. The goal of the course is to expose students to a universal set of business processes and provide them with a formal approach to improving and monitoring the health of those processes. Module 1 presents an overview of a six-step process improvement methodology. Lesson one will review the overall model and focus on defining the problem. Lesson two is a detailed discussion of the As Is and Should Be processes to help understand the current and desired states. Lesson three is understanding how to prioritize gaps, create business-ready action plans and use key performance indicators to measure and monitor changes. 10 videos5 readings4 assignments1 discussion prompt This module will compare and contrast quality models. It will also discuss the use of qualitative and quantitative tools to analyze the As Is process. Lesson one will review Six Sigma, ISO and Baldridge models to understand quality, policies and procedures and process excellence frameworks. Lessons two and three will review reengineering tools like Affinity Diagrams, Pareto Charts, Cause and Effect Diagrams, and Control Charts. These tools are mutually exclusive and collectively exhaustive to help diagnose the current state of a process. 8 videos4 readings4 assignments This module discusses that process mapping is not a flow chart but rather the inputs, activities and outputs that create a process. During this module we also cover the use of historic data to understand the As Is environment better and how to leverage performance measures to monitor changes once made. Lesson one is dedicated to process mapping and covers keys to effective interviewing as it is central to mapping a process. Lesson two reviews a model to collect and use historic data. The third lesson presents an approach to creating performance measures and effectively using them. 9 videos5 readings4 assignments This module will review why it is important to balance operational efficiency with business risk. It will also discuss how operations management are a series of projects that must be managed. In Lesson one risk management is covered and reviews the adverse impacts risk can have on business processes. In the Lesson two project management practices are reviewed and attributes of the ideal project manager is revealed. Lesson three is a case from the finance and accounting function going through the full process methodology to see it work in action. 8 videos4 readings4 assignments This module uncovers leading operational process audit techniques used by real-world practitioners. The first lesson is a review of multiple topics like customer orientation, business requirements, cost management and a focus on simplicity. The second lesson is a fun review of the prior lessons' concepts in the form of an engaging game. The third lesson is another detailed case study, this time from the marketing function, that will review the process methodology in detail via a real-world example. 8 videos4 readings4 assignments This module is about action plans and change management. In the first lesson action plans are explored. These plans are not only mini project plans but a business case to turn an idea into an action. The second lesson covers change management and that is understanding the human side of improvements. It covers practices to prevent creating a toxic culture that can sometimes envelop operational changes. The third lesson is an exercise along with a detailed case using the HR function as a way to further illustrate class concepts in real-world scenarios. 9 videos4 readings4 assignments This module is about quantifying the business impact and financial value of operational changes. The first lesson is defining value and presenting the ROI Process model to quantify value. The second lesson provides an in-depth case example of the ROI Process in action. It will go through mechanical computations to estimate, isolate and adjust numbers to create an ROI. The third lesson is exercises you will work on to ensure you fully understand how to use the ROI Process model. 9 videos4 readings4 assignments This module begins with a discussion of operations trends including resiliency, agility and sustainability. As the module progresses to the second lesson more details are reviewed around emerging technologies and how these can be excellent enablers for operational and process changes. Technologies like AI, IoT, Blockchain, Digitization, and Robotics will be covered. The final module is a review of major teachable moments from our course recapping the model, change management, action plans, Risk, ROI, project management and other concepts. 9 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 assignment1 plugin

9 modules

Intermediate level

https://www.coursera.org/learn/illinois-tech-operations-process-management

Culture-Driven Team Building Specialization

11,809

4.6

Dr. Aviva Legatt

University of Pennsylvania

['Team Building', 'Intercultural Communication', 'Collaboration', 'Team dynamics', 'Organizational Anthropology']

Master the strategies and tools that enable you to form, join and lead teams more effectively. In this five-course specialization, you learn how to: · Recognize aspects of team culture · Draw out the collective wisdom of diverse teams · Handle conflict · Establish common ground rules · Maximize team performance · Create a team culture of continuous learning The program culminates in a capstone project in which you apply the skills you learned. You observe, diagnose and make recommendations to solve a team culture problem in a real-world case provided by N2Growth, a global consultancy focused on cultural transformation and leadership development. Applied Learning Project Students will analyze a real world case provided by N2Growth, a global firm that helps clients create a culture of leadership through practice areas like strategy, cultural transformation, and organizational design. Based on the N2Growth case, students will be expected to identify and diagnose organizational issues, select a senior leader, and make recommendations in a culminating PowerPoint or Prezi presentation. Behind the success and failure of teams lies team culture. But what exactly is culture? How and why does it contribute to success and failure? In this course, you learn how to recognize aspects of team culture of which most people are typically unaware. It is often these seemingly unimportant aspects that have the greatest effect on the outcomes of group tasks. Your recognition of them enables you to form, join and lead teams more effectively. You also come to appreciate the role of ritual and symbols in the daily operation of teams, as well as in situations of change and crisis. Knowledge of the ideas and information in this class enables you to be a better team player and a more effective team leader. Teams are essential to the modern organization, but most never reach their potential. Co-workers miscommunicate, and groups struggle to adapt to changes in the market or their organizations. When teams lack self-awareness about these challenges, performance suffers. Based on years of team culture research and consulting experience, this course helps you understand the problems that hurt productivity, and gives you tools for creating positive change. This course also guides you through creating the ground rules and structure needed to set your team up for success. You gain the skills to diagnose issues such as conflicts, groupthink and lack of commitment in your team before they get out of control. The course offers frameworks to adjust team behaviors and get the best performance out of your people. You also understand frequent stumbling blocks for common team types, such as startups and virtual teams, and learn solutions tailored to each one. By drawing on social science perspectives, this course enables you to learn what diversity is, and how to use it to maximize team performance, innovation and creativity. You also learn how to draw out the collective wisdom of diverse teams, handle conflict and establish common ground rules through real-world cases and peer-to-peer discussions. In addition, you discover how to overcome common biases faced in diverse teams. Systems of power, reward and rhetoric are discussed to help you create prosperous teams where differences flourish. There is mounting concern that organizational groups and teams often fail to learn from their past experiences. It’s pertinent to address this issue as groups and teams are often the main ways that work gets done in organizations. In this course, we examine the main reasons that groups and teams are often ineffective, which include: • The lack of organizational structures and support for teams and groups • The lack of understanding and emphasis on learning • Misaligned reward structures So, what can be done to create an enabling learning culture in teams? This course emphasizes practical and impactful ways to begin to address this state of affairs. Through the use of stories, scenarios with actors simulating different team issues, examples and dialogue, you learn how to: • Understand teams in their larger organizational context • Diagnose the learning strengths and barriers to learning on teams • Identify ways to develop a team and group that continually learns and impacts the larger organization positively • Create an organizational environment that encourages learning and innovation In this capstone project class, you analyze a real-world case provided by N2Growth, a global firm that helps clients create a culture of leadership through practice areas like strategy, cultural transformation and organizational design. Based on the N2Growth case, you are expected to identify and diagnose organizational issues, select a senior leader and make recommendations in a culminating PowerPoint or Prezi presentation.

5 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/team-building

The DIY Musician Specialization

19,165

4.7

Stephen Webber

Berklee

['Social Media', 'Songwriting', 'Music production', 'Crowdfunding', 'Music recording']

With social media platforms and powerful recording technology at your fingertips, it’s easier now than ever before to create music and share it with your fans. But where do you begin and how do you get started? This specialization will take you through the process of writing, recording, and producing your own music in order to gain the practical skills you need to record music within ProTools, which is the industry standard Digital Audio Workstation. You’ll also work to develop an artist identity, vision, and brand for your music and learn how to run a successful crowdfunding campaign to fund your music career. Applied Learning Project You will write, record, and produce an original song using real instruments, MIDI, and effects such as equalization, compression, and reverb. You will also create a short business plan that will outline your web presence, potential brand partnerships, and a crowdfunding campaign. Define and identify the point of view, form, and the "who, what, where, when, and how" in a song Identify whether a lyric is stable or unstable through the use of line lengths, number of lines, stressed and unstressed syllables, and melody Utilize the various rhyming techniques to evoke specific emotions in a song and define the difference between Assonance and Consonance rhyme Use phrasing to clarify your ideas Discuss why one musical recording is more compelling than another and identify the unique elements of the recording that contribute to it Begin to assess and establish your identity, vision, and intention as an artist and producer Write and develop a compelling piece of music by utilizing various tools Establish the sonic signature of your production by utilizing specific production techniques Identify the various components in the Pro Tools interface and organize session files Discuss difference between a synthesizer and sampler and know how to use each of them Record a live performance into Pro Tools Balance your production mix by adjusting levels, using pan, and applying effects such as EQ, reverb, and compression Describe and discuss your identity, vision, and intention and identify strategies to balance the management of the band and the creation of the music Develop your musical brand, build and leverage a network of industry professionals, and discuss the benefits of partnering with other brands Develop a vision for a recording project and engage in a professional conversation with producers Plan, design, and launch a crowdfunding campaign

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/diy-musician

Apache Spark with Scala – Hands-On with Big Data!

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['Spark Streaming', 'Spark SQL', 'Dataset', 'dataset', 'Big Data', 'Apache Spark']

Embark on a journey to master big data processing with Apache Spark and Scala. This course begins with setting up your development environment, ensuring you have a solid foundation in both Spark and Scala. You will dive into a Scala crash course that covers syntax, flow control, functions, and data structures, giving you the essential skills needed to work with Spark. Next, you will explore Spark's core concept, the Resilient Distributed Dataset (RDD). Through a series of hands-on activities and exercises, you will learn to manipulate RDDs, implement key/value operations, and perform complex data transformations. The course then transitions into SparkSQL, DataFrames, and DataSets, where you will practice querying structured data efficiently. You'll also tackle advanced Spark programming, where you’ll apply algorithms to real-world datasets, work with clusters, and optimize performance. As you progress, you will delve into machine learning with Spark MLlib and explore how to build recommendation systems, perform regression analysis, and implement decision trees. Finally, the course introduces Spark Streaming and GraphX, allowing you to process real-time data streams and graph-based data efficiently. By the end of this course, you will have the expertise to leverage Spark and Scala for complex data processing tasks in any industry. This course is designed for software engineers who want to expand their skills into the world of big data processing on a cluster. It is necessary to have some prior programming or scripting knowledge. In this module, we will focus on installing the necessary tools like IntelliJ and Scala on your local system, followed by a brief introduction to the Apache Spark framework and its key concepts. 2 videos1 reading In this module, we will dive into Scala programming, covering its unique syntax, control flow, and key data structures like Map and List. You’ll get plenty of practice to ensure you’re comfortable with the language before jumping into Spark. 4 videos In this module, we will break down the structure and usage of RDDs, the building blocks of Spark applications. You’ll work on real-world examples, including building histograms and analyzing social network data. 13 videos1 assignment In this module, we will introduce SparkSQL, DataFrames, and Datasets, which provide a higher-level abstraction for working with structured data. You’ll also compare and contrast the use of RDDs with these APIs. 9 videos In this module, we will tackle advanced Spark programming examples, such as finding popular movies and superheroes in a social graph. We will also cover optimization techniques using broadcast variables and accumulators. 11 videos In this module, we will move from running Spark on a local desktop to deploying and scaling it on a real cluster using Amazon Elastic MapReduce (EMR). You’ll learn how to submit jobs, manage dependencies, and troubleshoot issues. 9 videos1 assignment In this module, we will explore Spark MLlib for machine learning. You’ll work through examples like generating movie recommendations and performing linear regression on large datasets. 6 videos In this module, we will focus on real-time data processing using Spark Streaming. You’ll build streaming applications and learn to handle data in motion, both with DStreams and the newer Structured Streaming API. 6 videos In this module, we will cover Spark’s GraphX library for graph-parallel processing, using it to explore social network data and understand how connected entities are through complex algorithms like breadth-first search. 3 videos1 assignment In this final module, we will provide additional learning resources and give you tips on leveraging your new skills to advance your career in the field of big data. 1 video1 assignment

10 modules

Intermediate level

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

https://www.coursera.org/learn/packt-apache-spark-with-scala-hands-on-with-big-data-hilnz

Global Health and Humanitarianism

12,301

4.7

Prof Tim Jacoby

University of Manchester

[]

Welcome to the Global Health and Humanitarianism MOOC. We are delighted to have you with us, and hope that the next six weeks will provide an interesting and thoughtful experience for you. We hope the course will give you an overview of global health and humanitarianism in theory and in practice. These fields overlap, and are connected, in many significant ways. However, we have used three key themes to explore our subjects: each key theme will be discussed over two week blocks by specialist course lecturers, and supported by unique video perspectives by three keynote speakers who are leading specialists in the field. - Weeks 1 & 2: An Introduction to Global Health Dr Amy Hughes MBE; - Weeks 3 & 4: Humanitarian Responses and Dilemmas Dr Tim Jacoby; - Weeks 5 & 6: The Right to Humanitarian Assistance and the Responsibility to Protect Dr Kirsten Howarth. To get the best out of the course we encourage you to try and set aside a few hours each week. This will give you time to work through videos, written materials and linked resources, and to get involved with discussion with other learners. We have provided a variety of different readings, resources and suggested activity based on the course content. Some will be essential to your understanding of the MOOC themes, and to assessment (if you have chosen to take part in assessment activity). Others will be for those of you who want to discover more about a particular subject or perspective, or to make your own study of global health or humanitarianism in action. Check through the weekly resources and content to find out which best suit your needs. During the course we will look at a range of different opinions and debates, linked to key themes and addressing ethics and moral issues. We hope you will be inspired and encouraged to explore and share your own perspectives, and those of others, throughout the course. Different viewpoints are essential to understanding global health and humanitarian practice. We hope you enjoy the next six weeks finding out about Global Health and Humanitarianism, and look forward to hearing from you on the discussion boards. These first two weeks will introduce you to the concept of global health through a range of perspectives from three keynote speakers, draw out some of their key thoughts, explore these with examples, and determine whether we can clearly conclude upon a definition of Global Health. We will be using various educational platforms to navigate the question 'What is Global Health?' - some short video narrations from me, expert thoughts from our three keynote speakers and some external documentary videos and articles. 6 videos7 readings1 discussion prompt We will first re-visit part of last week's keynote video and discuss their thoughts on what global health is, and bring particular focus to the origin and evolution of the term, the main organisations and agencies involved in global health and the influence of private and commercial organisations on global health. 5 videos4 readings1 assignment2 discussion prompts This week we will consider what gives rise to a humanitarian emergency. We will look at different types of hazard, and how these combine with vulnerability to give rise to a disaster. We will then go on to think about how responses to such phenomena are organised: Who undertakes these? What phases do they go through? 3 videos2 readings1 discussion prompt Last week we looked at the nature of 'disasters' and examined a possible set of humanitarian responses to disaster. We concluded by considering the problem of mitigation, leading us to complex ethical questions that make the main focus of the course this week. In particular we will look at the way humanitarian agencies bear witness to the actions of others, and the problem, or requirement, of holding people accountable for these actions. 3 videos2 readings1 assignment1 discussion prompt In the previous weeks of this course, you learned about the origins, key agencies and different approaches of humanitarianism. As the world becomes more interconnected as a result of globalisation, increased migration and technology, disasters (both natural and man-made) are no longer of local but global concern. The right to assistance for those affected by armed conflict and natural disasters is at the forefront of humanitarian action. 4 videos4 readings1 discussion prompt Moving on from last week, where we examined the right to humanitarian assistance and the obstacles and challenges surrounding its practice, this week we explore another controversial issue within humanitarianism: the responsibility to protect, or more commonly known as R2P. 5 videos5 readings1 assignment1 discussion prompt

6 modules

Beginner level

https://www.coursera.org/learn/health-humanitarianism

98%

Pharmacy Technician Essentials

3,832

4.7

Dr. Sherrie B. Moore

MedCerts

['Working in a Pharmacy Setting', 'Using Pharmacy Software', 'Reading Prescriptions', 'Understanding Pharmacy Terminology', 'Common Drugs and Usages']

The Pharmacy Technician Essentials course provides an in-depth look at what a career in a pharmacy will look like. Through several lessons, students learn the ins and outs of a pharmacy setting and the meaning of the terminology used daily within a pharmacy environment. This course also provides a deep dive into the purpose of the top 200 most commonly prescribed medications and drug routes and formulations. Students will be able to demonstrate correct processing of medication orders, preparation, storage, and distribution of medications, by the end of the course. On top of knowing the medications being prescribed, students must also learn how to use pharmacy equipment, including management software and reading of prescriptions. At the completion of this course, students should have a solid understanding of what their day-to-day tasks will be within a pharmacy environment and how to use the necessary tools to excel in their new career. Course objectives include: - Identify the primary functions of different pharmacy organizations - Discuss the different roles of the pharmacy technician - Describe the common drugs and their uses, drug routes and formulations, and factor affecting drug activity - Understand pharmacy management software, as well as reading and interpreting prescriptions Become acquainted with various pharmacy settings from the hospital to the community retail pharmacy to mail order drug distribution and the characteristics, advantages, and disadvantages of these settings. 5 videos2 readings3 assignments Gain an understanding of the basic aptitudes and personal attributes that are needed for a successful Pharmacy Technician; the daily job duties and responsibilities, as well as training, competency testing and performance measures. Additionally, review common medical terminology, drug classifications and abbreviations used in the pharmacy, and the body systems and their common disorders that are treated with medication. 8 videos2 readings4 assignments Learn about how drugs are developed, patented and named, understand drug classes, drug reference books, and common medications and their uses. Additionally, gain an understanding of the different forms that drugs are dispensed in (tablet, powder, solutions, syrups, etc.) and the various routes of administration (oral, dermal, parenteral, etc.). 25 videos3 readings8 assignments Become acquainted with the various tools and equipment used in a pharmacy setting to weigh, mix, count, and dispense medication. Additionally, gain an awareness of working with computers and software programs within the pharmacy setting and the different fields utilized to fill a prescription and run basic reports. The goal is not to master any specific software but to understand overall functionality. 10 videos4 readings5 assignments

4 modules

Beginner level

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

https://www.coursera.org/learn/pharmacy-technician-essentials

Unreal Engine Fundamentals

1,985

4.9

Logan Pinney

Epic Games

['Unreal Engine', 'Video Game Development', 'Unreal Engine', 'Video Game Design', 'World Building']

Welcome to Unreal Engine Fundamentals course: Your gateway to the world of game design using Unreal Engine 5. In this introductory course, we'll equip you with essential skills to navigate Unreal Engine from a new user to a proficient game designer. We'll start by guiding you through setting up your account, downloading the engine, and familiarizing you with the interface. Then, we'll explore Quixel Megascans, asset importing, materials, world building, lighting, sound, and source control. Throughout the course, you'll learn to sculpt immersive environments, implement dynamic lighting, basic audio effects, and collaborate effectively with team members using source control. Are you ready to begin your game design journey with Unreal Engine? Let's dive in and discover the exciting possibilities this fantastic platform offers! This course is meant for learners who are looking to learn the basics of getting started with Unreal Engine. To take this course learners won't need any experience with Unreal Engine. In this introductory module, we lay the groundwork for your Unreal Engine 5 journey by guiding you through the essential setup and familiarizing you with the core interfaces and workflow. You'll learn how to install UE5, navigate the editor's UI, manage assets and content, integrate with Quixel Bridge for high-quality scans, and dive into creating basic materials. By the end, you'll have a strong foundation in UE5's fundamentals, preparing you for more advanced topics. 45 videos2 readings12 assignments2 discussion prompts This module covers the fundamentals of world building in Unreal Engine 5, including terrain sculpting, landscape material creation, foliage placement, water system tools, and asset management techniques. Gain practical skills in creating immersive environments, from sculpting landmasses to procedurally populating scenes with foliage, blending materials, and placing meshes effectively. 30 videos1 reading8 assignments1 discussion prompt This module equips you with fundamental skills in lighting and audio for Unreal Engine 5 projects. Explore various lighting techniques, from basic light setup to next-gen technology systems like Lumen, ensuring visually stunning environments. Additionally, the module covers essential audio features, including audio asset management, sound design, and tools for creating immersive soundscapes. 17 videos3 assignments This module covers the essentials of collaboration and sharing in Unreal Engine 5, with a focus on version control using Perforce's Helix system and techniques for efficient asset management across projects. Gain practical skills in setting up version control, managing file revisions, and resolving conflicts. Learn how to streamlining workflows through asset migration and share your project with simple packaging. 9 videos1 reading2 assignments1 discussion prompt In this final project, you will apply everything you’ve learned in the course to create a compelling and immersive 3D environment in Unreal Engine 5, referred to as your "Unreal Paradise." This task will involve landscape creation, asset integration, lighting, and audio implementation to bring your scene to life. The use of source control is highly encouraged but is optional and will not be used as a marking or grading criteria for successful completion of this final project. 5 videos2 readings1 peer review1 discussion prompt

5 modules

Beginner level

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

https://www.coursera.org/learn/unreal-engine-fundamentals

Advanced Algorithms and Complexity

83,476

4.6

Neil Rhodes

University of California San Diego

['Python Programming', 'Linear Programming (LP)', 'Np-Completeness', 'Dynamic Programming']

In previous courses of our online specialization you've learned the basic algorithms, and now you are ready to step into the area of more complex problems and algorithms to solve them. Advanced algorithms build upon basic ones and use new ideas. We will start with networks flows which are used in more typical applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision. We then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements and many others. Next we discuss inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them in practice. We finish with a soft introduction to streaming algorithms that are heavily used in Big Data processing. Such algorithms are usually designed to be able to process huge datasets without being able even to store a dataset. Network flows show up in many real world situations in which a good needs to be transported across a network with limited capacity. You can see it when shipping goods across highways and routing packets across the internet. In this unit, we will discuss the mathematical underpinnings of network flows and some important flow algorithms. We will also give some surprising examples on seemingly unrelated problems that can be solved with our knowledge of network flows. 9 videos5 readings1 assignment1 programming assignment1 plugin Linear programming is a very powerful algorithmic tool. Essentially, a linear programming problem asks you to optimize a linear function of real variables constrained by some system of linear inequalities. This is an extremely versatile framework that immediately generalizes flow problems, but can also be used to discuss a wide variety of other problems from optimizing production procedures to finding the cheapest way to attain a healthy diet. Surprisingly, this very general framework admits efficient algorithms. In this unit, we will discuss some of the importance of linear programming problems along with some of the tools used to solve them. 10 videos1 reading1 assignment1 programming assignment Although many of the algorithms you've learned so far are applied in practice a lot, it turns out that the world is dominated by real-world problems without a known provably efficient algorithm. Many of these problems can be reduced to one of the classical problems called NP-complete problems which either cannot be solved by a polynomial algorithm or solving any one of them would win you a million dollars (see Millenium Prize Problems) and eternal worldwide fame for solving the main problem of computer science called P vs NP. It's good to know this before trying to solve a problem before the tomorrow's deadline :) Although these problems are very unlikely to be solvable efficiently in the nearest future, people always come up with various workarounds. In this module you will study the classical NP-complete problems and the reductions between them. You will also practice solving large instances of some of these problems despite their hardness using very efficient specialized software based on tons of research in the area of NP-complete problems. 16 videos2 readings1 assignment1 programming assignment1 plugin After the previous module you might be sad: you've just went through 5 courses in Algorithms only to learn that they are not suitable for most real-world problems. However, don't give up yet! People are creative, and they need to solve these problems anyway, so in practice there are often ways to cope with an NP-complete problem at hand. We first show that some special cases on NP-complete problems can, in fact, be solved in polynomial time. We then consider exact algorithms that find a solution much faster than the brute force algorithm. We conclude with approximation algorithms that work in polynomial time and find a solution that is close to being optimal. 11 videos1 reading1 assignment1 programming assignment In most previous lectures we were interested in designing algorithms with fast (e.g. small polynomial) runtime, and assumed that the algorithm has random access to its input, which is loaded into memory. In many modern applications in big data analysis, however, the input is so large that it cannot be stored in memory. Instead, the input is presented as a stream of updates, which the algorithm scans while maintaining a small summary of the stream seen so far. This is precisely the setting of the streaming model of computation, which we study in this lecture. The streaming model is well-suited for designing and reasoning about small space algorithms. It has received a lot of attention in the literature, and several powerful algorithmic primitives for computing basic stream statistics in this model have been designed, several of them impacting the practice of big data analysis. In this lecture we will see one such algorithm (CountSketch), a small space algorithm for finding the top k most frequent items in a data stream. 10 videos1 assignment1 programming assignment

5 modules

Advanced level

https://www.coursera.org/learn/advanced-algorithms-and-complexity

86%

Introduction to HTML5

572,401

4.7

Colleen van Lent, Ph.D.

University of Michigan

['Web Design', 'Web Accessibility', 'HTML', 'Html5']

Thanks to a growing number of software programs, it seems as if anyone can make a webpage. But what if you actually want to understand how the page was created? There are great textbooks and online resources for learning web design, but most of those resources require some background knowledge. This course is designed to help the novice who wants to gain confidence and knowledge. We will explore the theory (what actually happens when you click on a link on a webpage?), the practical (what do I need to know to make my own page?), and the overlooked (I have the code, but how do I put it on the web to share with others?). Throughout the course there will be a strong emphasis on adhering to syntactic standards for validation and semantic standards to promote wide accessibility for users with disabilities. This course will appeal to a wide variety of people, but specifically those who would like a step-by-step description of the basics. There are no prerequisites for this course and it is assumed that students have no prior programming skills or IT experience. The course will culminate in a small final project that will require the completion of a very simple page with links and images. The focus of this course is on the basics, not appearance. You can see a sample final HTML page at https://example-site-1--wd4ehtml.repl.co/ . This is the first course in the Web Design For Everybody specialization. Subsequent courses focus on the marketable skills of styling the page with CSS3, adding interactivity with JavaScript and enhancing the styling with responsive design. This week we will uncover the "mystery" behind the Internet. What happens when you type a URL into your browser so that a webpage magically appears? What is HTML5 and what happened to HTML 1 - 4? We will also cover some practical concepts that you need to master before you begin coding your own pages. 7 videos9 readings1 assignment1 discussion prompt This week you will need to take a deep breath and jump into coding. I will cover a large number of HTML tags, but it is important that you do more than just listen to these video and read the text book material. You need to practice (and fail!) in order to learn. Believe it or not, once you master the basic idea of using tags and attributes you will know everything you need to use any HTML5 tag. The page may not look the way you want it to look yet, but you will be able to use text, links, images, tables, and even music and videos! If you want to refer to a textbook this week for reinforcement of concepts, we will be using the Shay Howe online textbook as a reference. I will include links after the lectures, but some students prefer to read before the videos. (My preferred approach is to read/watch/read again.) 9 videos11 readings1 assignment Okay, you created a file...what now? This week we will begin by covering the important but often overlooked concepts of validation and accessibility. Did you follow the DOM structure when you created your page? Did you use semantic tags to make sure that page viewers can access all of the information, even if they have physical or cognitive disabilities? This is knowledge you can use if you would like to pursue a career as a web accessibility specialist. Finally I will briefly cover the steps needed to post your site to the web if you decide to use something other than Replit. There are many free and paid services that you can use to get your work off your computer and on to the Internet. 8 videos8 readings1 assignment1 peer review1 app item

3 modules

Beginner level

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

97%

Entrepreneurship: Launching an Innovative Business Specialization

44,515

4.7

Dr. James V. Green

University of Maryland, College Park

['Venture Capital', 'Finance', 'Value Proposition', 'Entrepreneurship']

The Entrepreneurship Specialization examines the entrepreneurial mindset and skill sets, indicators of innovation opportunities, critical steps to bring innovations to the marketplace, and innovation strategies to establish and maintain a competitive advantage. Fundamentals of new venture financing are explored with attention to capital structures for new ventures, term sheets and how to negotiate them, and the differences between early-stage versus later-stage financing. You will develop an understanding of how to develop winning investor pitches, who and when to pitch, how to avoid common mistakes, and how to ‘get to the close’. In the final Capstone Project, you will apply the tools and concepts from the specialization courses by crafting a comprehensive, customer-validated business model, and creating a business plan and investor pitch. This course assists aspiring and active entrepreneurs in developing great ideas into great companies. With strong economies presenting rich opportunities for new venture creation, and challenging economic times presenting the necessity for many to make their own job, the need to develop the skills to develop and act on innovative business opportunities is increasingly vital. Using proven content, methods, and models for new venture opportunity assessment and analysis, you will learn how to: * Identify and analyze entrepreneurial opportunities; * Enhance your entrepreneurial mindset; * Improve your strategic decision-making; and * Build innovative business models. Our goal is to demystify the startup process, and to help you build the skills to identify and act on innovative opportunities now, and in the future. With this course, students experience a sampling of the ideas and techniques explored in the University of Maryland's master's degree in technology entrepreneurship, an innovative, 100% online program. Learn more at http://mte.umd.edu/landing. Develop insights on navigating the innovation process from idea generation to commercialization. Build knowledge on how to create strategies to bring innovations to market. Develop an innovation portfolio and business model canvas for your venture. We establish a framework for examining the innovation process, and quickly transition into exploring how to successfully bring innovations to market. Key questions answered within the course include: * What are the key indicators of innovation opportunities? * What steps are critical for entrepreneurs to bring innovations to the marketplace? * What innovation strategies are valuable for new ventures to establish and maintain a competitive advantage? With this course, students experience a sampling of the ideas and techniques explored in the University of Maryland's master's degree in technology entrepreneurship, an innovative, 100% online program. Learn more at http://mte.umd.edu/landing. This course is for aspiring or active entrepreneurs who wants to understand how to secure funding for their company. This course will demystify key financing concepts to give entrepreneurs and aspiring entrepreneurs a guide to secure funding. Examine the many financing options available to get your new venture funded. Learn the basics of finance, valuations, dilution and non-dilutive funding sources. Understand capital structure for new ventures, term sheets and how to negotiate them, and the differences between early-stage versus later-stage financing. Develop an understanding of how to develop winning investor pitches, who and when to pitch, how to avoid common mistakes that limit the effectiveness of the pitch, and how to ‘get to the close’. Key questions answered within the course include: * When to raise outside capital? * What kind of investors invest by stage and where to find them? * What are your fundraising options? * What are the key components of the term sheet? * How to perform company valuations? * How to pitch to investors? * What techniques help the entrepreneur ‘get to the close’? With this course, students experience a sampling of the ideas and techniques explored in the University of Maryland's master's degree in technology entrepreneurship, an innovative 100% online program. Learn more at http://mte.umd.edu/landing. Integrate the tools and concepts from the specialization courses to develop a comprehensive business plan. Choose to enhance new venture concepts previously explored in specialization courses, or develop a new concept for this capstone project. Develop a comprehensive, customer-validated business model and create an investor pitch for the concept. With this course, students experience a sampling of the ideas and techniques explored in the University of Maryland's master's degree in technology entrepreneurship, an innovative 100% online program. Learn more at http://mte.umd.edu.

4 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/business-entrepreneurship

Make Apps with ChatGPT and Generative AI

Enrollment number not found

Rating not found

Packt - Course Instructors

Packt

['ChatGPT', 'Power Automate', 'business applications', 'airtable', 'Airtable', 'Business Applications', 'OpenAI API']

ChatGPT is a language generation model developed by OpenAI, with its latest version, Davinci, powering the ChatGPT program. This course aims to teach how to build applications and solutions using ChatGPT by understanding OpenAI and ChatGPT APIs. Students will learn to create serverless functions that handle ChatGPT prompts and responses, integrating these into various platforms. The course covers connecting to the OpenAI API, creating Azure functions, and developing applications such as CoverLetterCreator, StockPhotoPPT, PolitelySayNo, and TravelPlan. By the end, learners will be able to increase productivity and build real-life applications using ChatGPT and other OpenAI models like DALL-E. They will integrate the API into platforms like Outlook, Power Apps, Power Automate, Airtable, and Bubble. The course is ideal for managers, employees, and individuals looking to improve team efficiency or monetize applications using ChatGPT. Learners will integrate ChatGPT into business tools, create no-code apps, plan itineraries, generate cover letters, and produce stock photos for presentations. In this module, we will establish the groundwork for the course by exploring essential app development concepts and the roadmap for building ChatGPT applications. We will look at examples of successful ChatGPT solutions, understand the technical requirements, meet the course instructor, and learn the keys to successful ChatGPT app development. 6 videos1 reading In this module, we will delve into the fundamentals of OpenAI and ChatGPT, focusing on how ChatGPT can be employed for solving problems. We will explore the different GPT-3 models, including their strengths and weaknesses, and detail the capabilities of GPT-3 Davinci. Additionally, we will cover key techniques for optimizing prompts, the concept of tokenization, and the importance of temperature control in generating diverse responses. 7 videos In this module, we will lay the essential groundwork for our development environment by guiding you through the setup of necessary accounts and tools. You will sign up for OpenAI API and Azure accounts, create an Azure Function resource, and install Python. Additionally, we will install and configure Visual Studio Code, learn to use the terminal for running Python and Pip, and set up a Microsoft 365 E5 account to access further resources. 8 videos1 assignment In this module, we will focus on building a serverless ChatGPT API. You will learn how to access the OpenAI API using Python and manage ChatGPT responses. We will guide you through creating and deploying Azure Functions, testing them with Postman, and integrating them with OpenAI ChatGPT. Additionally, we will cover local testing and the final deployment of OpenAI ChatGPT to Azure Functions. 8 videos In this module, we will explore the integration of ChatGPT with Microsoft Power Automate to create automated workflows. You will learn how to connect OpenAI ChatGPT to Power Automate using HTTP requests and develop a functional Teams chatbot. Finally, we will guide you through the process of testing and publishing your Teams ChatGPT chatbot for effective communication and automation. 4 videos In this module, we will cover the creation and enhancement of applications using Power Apps. You will learn how to build basic Power Apps and integrate them with OpenAI ChatGPT. Additionally, we will guide you through the implementation of a Q&A bot within Power Apps, enabling interactive and intelligent user experiences. 3 videos1 assignment In this module, we will integrate ChatGPT with Microsoft Outlook by developing an Office Add-In. You will learn to set up the development environment, create and launch an Outlook Add-In, and execute ChatGPT API calls from within Outlook. Additionally, we will address common issues like CORS and security errors, facilitate the transfer of email content to ChatGPT, and automate pasting ChatGPT responses back into Outlook, enhancing email functionalities. 7 videos In this module, we will explore building and enhancing applications on the Bubble platform. You will learn how to create applications in Bubble and establish a connection with the ChatGPT API. Additionally, we will cover techniques for dynamic prompt modification, enabling more interactive and customized responses within your Bubble applications. 3 videos In this module, we will integrate ChatGPT with Airtable to enhance its functionality. You will learn to set up the context in Airtable, write scripts for calling the ChatGPT API, and dynamically modify prompts based on Airtable variables. Finally, we will guide you through testing a ChatGPT-powered marketing email generator, demonstrating practical applications of this integration. 4 videos1 assignment In this module, we will guide you through the development of a ChatGPT-powered itinerary app. You will learn how to set up the front-end and create additional pages, develop ChatGPT workflows, and link these pages together for seamless functionality. We will also cover the integration of ImageAI and OpenAI for photo features and ensure robust testing of both text and photo capabilities within the app. 6 videos In this module, we will develop the EmailResponder app using ChatGPT to automate email responses. You will learn to set up the Outlook environment, make necessary front-end changes, and create ChatGPT-powered back-end functions. Additionally, we will guide you through modifying email bodies, adding a reply box for user inputs, and expanding the app with ChatGPT mood options to tailor responses based on different emotional tones. 6 videos1 assignment In this module, we will build the JobApplicationCreator app to streamline the job application process using ChatGPT. You will learn to create a screen for generating personalized cover letters, link the ChatGPT API, and develop the necessary workflows. Additionally, we will test the app with various job descriptions to ensure it produces effective and tailored cover letters for different roles. 3 videos In this module, we will develop the SplashImages app to generate stock photos using the DALL-E image API. You will learn how to use the DALL-E API, create an intuitive front-end interface, and integrate ChatGPT with Power Automate for seamless operations. Finally, we will test the stock photo generator to ensure it produces high-quality images suitable for various needs. 4 videos1 assignment In this module, we will conclude the course by summarizing the key concepts and skills you have acquired. We will reflect on the practical applications of ChatGPT and generative AI, and provide you with encouragement and guidance for your continued journey in AI development. Congratulations on completing the course! 1 video1 assignment

14 modules

Intermediate level

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

https://www.coursera.org/learn/packt-make-apps-with-chatgpt-and-generative-ai-nsygy

Applied Data Science with R Specialization

4,360

4.5

Rav Ahuja

IBM

['Shiny Dashboards', 'SQL & RDBMS', 'Data Analysis and Modelling', 'Data Visualization', 'R Programmin Language', 'Shiny Dashboards', 'SQL & RDBMS', 'Data Analysis and Modelling', 'Data Visualization', 'R Programmin Language']

This Specialization is intended for anyone with a passion for learning who is seeking to develop the job-ready skills, tools, and portfolio to have a competitive edge in the job market as an entry-level data scientist. Through these five online courses, you will develop the skills you need to bring together often disparate and disconnected data sources and use the R programming language to transform data into insights that help you and your stakeholders make more informed decisions. By the end of this Specialization, you will be able to perform basic R programming tasks to complete the data analysis process, including data preparation, statistical analysis, and predictive modeling. You will also be able to create relational databases and query the data using SQL and R and communicate your data findings using data visualization techniques. Applied Learning Project Throughout this Specialization, you will complete hands-on labs to help you gain practical experience with various data sources, datasets, SQL, relational databases, and the R programing language. You will work with tools like R Studio, Jupyter Notebooks, and related R libraries for data science, including dplyr, Tidyverse, Tidymodels, R Shiny, ggplot2, Leaflet, and rvest. In the final course in this Specialization, you will complete a capstone project that applies what you have learned to a challenge that requires data collection, analysis, basic hypothesis testing, visualization, and modelling to be performed on real-world datasets. Manipulate primitive data types in the R programming language using RStudio or Jupyter Notebooks. Control program flow with conditions and loops, write functions, perform character string operations, write regular expressions, handle errors. Construct and manipulate R data structures, including vectors, factors, lists, and data frames. Read, write, and save data files and scrape web pages using R. Create and access a database instance on the cloud Compose and execute basic SQL statements - SELECT, INSERT, UPDATE, DELETE, CREATE, DROP Construct SQL statements to filter, sort, group results, use built-in functions, compose nested queries, access multiple tables Analyze data from Jupyter using R and SQL by combining SQL and R skills to query real-world datasets Prepare data for analysis by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values. Compare and contrast predictive models using simple linear, multiple linear, and polynomial regression methods. Examine data using descriptive statistics, data grouping, analysis of variance (ANOVA), and correlation statistics. Evaluate a model for overfitting and underfitting conditions and tune its performance using regularization and grid search. Create bar charts, histograms, pie charts, scatter plots, line graphs, box plots, and maps using R and related packages. Design customized charts and plots using annotations, axis titles, text labels, themes, and faceting. Create maps using the Leaflet package for R. Create interactive dashboards using the Shiny package for R. Write a web scraping program to extract data from an HTML file using HTTP requests and convert the data to a data frame. Prepare data for modelling by handling missing values, formatting and normalizing data, binning, and turning categorical values into numeric values. Interpret datawithexploratory data analysis techniques by calculating descriptive statistics, graphing data, and generating correlation statistics. Build a Shiny app containing a Leaflet map and an interactive dashboard then create a presentation on the project to share with your peers.

5 course series

Beginner level

2 months (at 10 hours a week)

https://www.coursera.org/specializations/applied-data-science-r

Python 3 Programming Specialization

243,225

4.8

Steve Oney

University of Michigan

['Json', 'Computer Programming', 'Python Programming', 'Sorting']

This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance. You will have lots of opportunities to practice. You will also learn ways to reason about program execution, so that it is no longer mysterious and you are able to debug programs when they don’t work. By the end of the specialization, you’ll be writing programs that query Internet APIs for data and extract useful information from them. And you’ll be able to learn to use new modules and APIs on your own by reading the documentation. That will give you a great launch toward being an independent Python programmer. This specialization is a good next step for you if you have completedPython for EverybodyOpens in a new tabbut want a more in-depth treatment of Python fundamentals and more practice, so that you can proceed with confidence to specializations likeApplied Data Science with PythonOpens in a new tab. But it is also appropriate as a first set of courses in Python if you are already familiar with some other programming language, or if you are up for the challenge of diving in head-first. Applied Learning Project By the end of the second course, you will create a simple sentiment analyzer that counts the number of positive and negative words in tweets. In the third course, you will mash up two APIs to create a movie recommender. The final course,Python Project: pillow, tesseract, and opencv(Course 5), is an extended project in which you'll perform optical character recognition (OCR) and object detection in images. Learn Python 3 basics, including conditional statements, loops, and data structures like strings and lists. Develop practical programming skills by creating drawings and building your debugging abilities. Explore the dictionary data structure and user-defined functions in Python. Understand concepts like local and global variables, parameter-passing techniques, named functions, and lambda expressions. Apply Python's sorted function and control sorting order with custom functions. Create a final project involving social media data analysis and CSV file manipulation. Fetch and process data from Internet services effectively. Master Python list comprehensions for data extraction and processing. Utilize the Python requests module to interact with REST APIs and navigate API documentation. Explore classes, instances, and inheritance to represent data efficiently. Gain insights into class design and cultivate the practice of writing automated tests for your code. Learn to override built-in methods and create inherited classes that reuse functionality. How to inspect and understand APIs and third party libraries to be used with Python 3 How to apply the Python imaging library (pillow) to open, view, and manipulate images, including cropping, resizing, recoloring, and overlaying text How to apply the python tesseract (pytesseract) library with Python 3 in order to detect text in images through optical character recognition (OCR)

5 course series

Beginner level

3 months (at 10 hours a week)

https://www.coursera.org/specializations/python-3-programming

Introduction to Forensic Science

160,213

4.8

Roderick Bates

Nanyang Technological University, Singapore

[]

We have all seen forensic scientists in TV shows, but how do they really work? What is the science behind their work? The course aims to explain the scientific principles and techniques behind the work of forensic scientists and will be illustrated with numerous case studies from Singapore and around the world. Some questions which we will attempt to address include: How did forensics come about? What is the role of forensics in police work? Can these methods be used in non-criminal areas? Blood. What is it? How can traces of blood be found and used in evidence? Is DNA chemistry really so powerful? What happens (biologically and chemically) if someone tries to poison me? What happens if I try to poison myself? How can we tell how long someone has been dead? What if they have been dead for a really long time? Can a little piece of a carpet fluff, or a single hair, convict someone? Was Emperor Napoleon murdered by the perfidious British, or killed by his wallpaper? *For Nanyang Technological University (NTU) students, please be noted that this course will no longer be eligible for credit transfer. 7 readings 10 videos1 reading 11 videos1 reading 11 videos1 reading1 assignment 11 videos1 reading1 peer review 11 videos1 reading1 assignment 6 videos1 reading1 peer review 12 videos1 reading1 assignment 7 videos1 reading

9 modules

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

https://www.coursera.org/learn/forensic-science

98%

Cloud Computing Law Specialization

3,220

4.9

Dimitra Kamarinou

Queen Mary University of London

['General Data Protection Regulation (GDPR)', 'Cybersecurity', 'Cloud Computing', 'Contract Law', 'Cloud Services']

This Specialization is intended for anyone interested in understanding the legal rights and obligations of providers and customers of cloud services. Our three Courses cover the key legal and regulatory issues for cloud services, including cloud contracts, data protection law, law enforcement access, and much more! You will learn to describe cloud providers’ and customers’ legal rights, to identify and assess legal risks, and to suggest possible legal and technological solutions. Applied Learning Project In this Specialization, learners analyse case studies based on real-world issues. They apply their understanding of cloud computing law to help fictional cloud providers and customers solve legal problems, by answering a series of multiple-choice questions. Have you ever wondered what’s in the small print of cloud contracts? Or who owns the information you upload to the cloud? And who can access and control it? If so, then this course is for you! You’ll learn to identify the legal risks involved in cloud computing transactions - and to suggest possible solutions. To understand how cloud computing works, we’ll first describe different kinds of cloud services and explain how they differ from in-house IT in terms of control, access, and cybersecurity. To understand how the law applies to cloud computing transactions, we’ll focus on the contracts between cloud providers and their customers. You’ll learn to identify and interpret key contract terms and to assess whether customers might negotiate better terms with providers. Finally, we’ll explain how English law protects trade secrets and copyright works stored in the cloud. If you’re a lawyer, this course will be your guide to cloud infrastructure and supply chains. If you have a technical or commercial background, this course will introduce you to key legal issues in contracts and intellectual property. In short, if you’re interested in how the law applies to cloud computing, this course is for you. Vast amounts of personal information are processed in the cloud. But who is legally responsible for such ‘personal data’ in cloud environments? What duties do cloud providers like Amazon, Microsoft, and Google have? And what rights can you, as an individual, exercise under data protection law? If you’d like to find out, then this course is for you! First, we’ll look at how the European Union’s ‘General Data Protection Regulation’ (‘GDPR’) regulates the processing of personal data in cloud services. You’ll learn to identify controllers and processors, describe their roles and responsibilities, and understand how cloud customers and providers can comply in practice. Second, we’ll look at international transfers of personal data. We’ll explain how the GDPR can apply to cloud providers and their customers anywhere in the world, as well as how restrictions on international transfers apply to cloud services. Third, we’ll look at how the Network and Information Security (‘NIS’) Directive regulates the cybersecurity of critical infrastructure. You’ll learn to identify cloud providers’ duties to notify security breaches and to keep their services secure, and how to apply those duties to concrete case studies. In short, this course covers how the GDPR and NIS Directive apply to cloud services and what cloud providers and their customers should do to comply. Have you ever wondered how a police officer in Europe can obtain evidence from a cloud provider in the USA? Or whether a major cloud provider might abuse its market power? Or in which countries cloud providers pay taxes? If so, then this course is for you! First, we’ll look at how law enforcement agents can request access to cloud data, including data stored outside their borders. You’ll learn to advise cloud providers on responding to access requests and on dealing with potential conflicts with European Union (‘EU’) data protection law. Second, we’ll cover EU competition law, including how to define the relevant market for cloud services and to assess market power. You’ll learn to identify when cloud providers might be found to have entered into anti-competitive agreements, or to have abused a dominant position in a market. Third, we’ll look at how the income from cloud services is taxed. We’ll cover how such income is classified and which countries have the right to tax cloud providers. You’ll learn how tax principles apply to cloud services today, and how this might change in future. In short, we’ll cover how the rules of law enforcement access, competition law, and tax law apply to cloud services – and you’ll discover the practical steps that cloud providers can take to comply with their obligations.

3 course series

Beginner level

1 month (at 10 hours a week)

https://www.coursera.org/specializations/cloud-computing-law

AI-Powered Software and System Design

3,107

4.6

Laurence Moroney

DeepLearning.AI

['Designing software applications with AI guidance', 'Data serialization and configuration-driven development', 'Optimizing database queries with AI assistance']

This final course in the skill certificate focuses on applying AI to high-level software engineering tasks. You'll work with LLMs to design and implement sophisticated software systems, optimize code using established design patterns, and create efficient databases from scratch. By the end of this course, you will be able to: - Use AI to suggest and implement software architectures based on natural language requirements - Build a configurable application that interacts with external APIs like DALL-E - Design and implement a complete database system for an e-commerce platform - Optimize database queries and analyze code for security risks with AI assistance - Refactor existing applications using Gang of Four design patterns, guided by AI insights These advanced skills will enable you to tackle complex software engineering projects with greater efficiency and creativity. You'll learn to harness the power of AI to make informed design decisions, implement robust systems, and optimize code at scale. This course will prepare you to lead innovative software projects and adapt to the evolving landscape of AI-augmented software development. 8 videos4 readings2 assignments2 ungraded labs 9 videos1 reading2 assignments1 programming assignment3 ungraded labs 9 videos2 readings2 assignments1 ungraded lab

3 modules

Beginner level

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

https://www.coursera.org/learn/ai-powered-software-and-system-design

Data Manipulation at Scale: Systems and Algorithms

61,333

4.3

Bill Howe

University of Washington

['Relational Algebra', 'Python Programming', 'SQL', 'Mapreduce']

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales. In this course, you will learn the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against your requirements. You will learn how practical systems were derived from the frontier of research in computer science and what systems are coming on the horizon. Cloud computing, SQL and NoSQL databases, MapReduce and the ecosystem it spawned, Spark and its contemporaries, and specialized systems for graphs and arrays will be covered. You will also learn the history and context of data science, the skills, challenges, and methodologies the term implies, and how to structure a data science project. At the end of this course, you will be able to: Learning Goals: 1. Describe common patterns, challenges, and approaches associated with data science projects, and what makes them different from projects in related fields. 2. Identify and use the programming models associated with scalable data manipulation, including relational algebra, mapreduce, and other data flow models. 3. Use database technology adapted for large-scale analytics, including the concepts driving parallel databases, parallel query processing, and in-database analytics 4. Evaluate key-value stores and NoSQL systems, describe their tradeoffs with comparable systems, the details of important examples in the space, and future trends. 5. “Think” in MapReduce to effectively write algorithms for systems including Hadoop and Spark. You will understand their limitations, design details, their relationship to databases, and their associated ecosystem of algorithms, extensions, and languages. write programs in Spark 6. Describe the landscape of specialized Big Data systems for graphs, arrays, and streams Understand the terminology and recurring principles associated with data science, and understand the structure of data science projects and emerging methodologies to approach them. Why does this emerging field exist? How does it relate to other fields? How does this course distinguish itself? What do data science projects look like, and how should they be approached? What are some examples of data science projects? 22 videos4 readings1 programming assignment Relational Databases are the workhouse of large-scale data management. Although originally motivated by problems in enterprise operations, they have proven remarkably capable for analytics as well. But most importantly, the principles underlying relational databases are universal in managing, manipulating, and analyzing data at scale. Even as the landscape of large-scale data systems has expanded dramatically in the last decade, relational models and languages have remained a unifying concept. For working with large-scale data, there is no more important programming model to learn. 24 videos1 programming assignment The MapReduce programming model (as distinct from its implementations) was proposed as a simplifying abstraction for parallel manipulation of massive datasets, and remains an important concept to know when using and evaluating modern big data platforms. 26 videos1 programming assignment NoSQL systems are purely about scale rather than analytics, and are arguably less relevant for the practicing data scientist. However, they occupy an important place in many practical big data platform architectures, and data scientists need to understand their limitations and strengths to use them effectively. 36 videos Graph-structured data are increasingly common in data science contexts due to their ubiquity in modeling the communication between entities: people (social networks), computers (Internet communication), cities and countries (transportation networks), or corporations (financial transactions). Learn the common algorithms for extracting information from graph data and how to scale them up. 21 videos

5 modules

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

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

89%

Artificial Intelligence Algorithms Models and Limitations

16,039

4.7

Brent Summers

LearnQuest

['Understanding of algorithms', 'Familiarity with predictive models', 'Overview of ethics considersations']

We live in an age increasingly dominated by algorithms. As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations in the real world. Whether it's making loan decisions or re-routing traffic, machine learning models need to accurately reflect our shared values. In this course, we will explore the rise of algorithms, from the most basic to the fully-autonomous, and discuss how to make them more ethically sound. Welcome to the course! We're going to get started with an overview of the course structure as well as an introductory look at the world of algorithms 5 videos2 readings3 assignments2 discussion prompts This week, we are going to dive into predictive modeling the core differences in theory and practice 3 videos2 readings3 assignments1 discussion prompt This week we are going to focus on machine learning accuracy and training guidelines in the quest for more accurate and ethical models 3 videos2 readings3 assignments1 discussion prompt In our final week, we're going to ask some big questions about where all this predictive intelligence leads. We will discuss the trajectory of artificial intelligence and the broader implications for society as well 4 videos2 readings3 assignments1 discussion prompt

4 modules

Beginner level

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

https://www.coursera.org/learn/ai-algorithm-limitations

Introduction to Nonprofit Law

Enrollment number not found

Rating not found

John M. Bradley

University of Pennsylvania

[]

The nonprofit sector in America is made up of over 1.9 million tax exempt organizations and accounts for nearly 6% of the nation's gross domestic product. This course will introduce the major legal rules that govern nonprofit organizations, beginning with the historical context that has shaped the modern nonprofit sector. We will explore the different forms of nonprofit organizations and their associated legal obligations, and we will examine the rules that govern nonprofit activities such as fundraising. We will also look at the constraints nonprofit organizations face regarding both political activity and internal employment considerations. Finally, we will examine the various oversight mechanisms designed to keep nonprofit organizations in line with their mission as well as look to the future and explore how the nonprofit sector may continue to evolve. Welcome to this introductory course on the laws that shape and govern the nonprofit sector in America! In this first module, we will look at the history and development of the nonprofit sector in the United States. We'll see the influence of early theories of charitable work as well as the evolving relationship between nonprofit organizations and the government. 8 videos3 readings1 assignment1 discussion prompt This module will introduce the different entity choices available to the nonprofit sector and the various considerations that go into choosing a corporate form. In particular, we examine how the primary purpose and fundraising strategy can influence the particular form chosen. Finally, we look at the different obligations to state and federal governments that nonprofit entities must fulfill to maintain their exempt status. 7 videos4 readings1 assignment This module examines the operational challenges that are particular to the nonprofit form. What legal obligations must a nonprofit fulfill when bringing in revenue? Under what circumstances may exempt organizations participate in lobbying or political activity? Finally, we will study the seemingly simple issue of distinguishing between employees and volunteers in the nonprofit setting. 11 videos8 readings1 assignment In this final module, we address accountability - who is charged with ensuring that organizations that have been formed as nonprofit, tax-exempt organizations abide by their expected and legal purposes and activities? 9 videos6 readings1 assignment

4 modules

Intermediate level

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

https://www.coursera.org/learn/introduction-to-nonprofit-law

Introduction to Finance: The Basics

59,048

4.7

Xi Yang

University of Illinois Urbana-Champaign

['Financial Management', 'Finance', 'Future Value', 'Leadership And Management']

In the Introduction to Finance I: The Basics course, you will be introduced to the basic concepts needed to understand the financial manager’s decision-making process. To achieve that, you will learn about the basic forms a business can take and the goal of the financial manager. You will also learn the fundamentals of financial statements and how to measure a company’s financial health using financial ratios. In addition, you will explore how to allocate capital across time to create value. After learning the course, you should be familiar with major topics in modern finance and communicate with others within and outside of the business world. With a deep understanding of the financial side of the business, you will be in a better position to make informed decisions and plan for the financial future. 3 videos7 readings1 quiz1 discussion prompt In this module, you will be introduced to three basic forms to organize a business based on the nature of the business and its financing needs. Examining the goal of financial business helps us to develop a concrete framework to evaluate a corporate manager’s financial decisions. The corporation organization form is widespread because it can solve problems facing big business, but it also incurs the agency cost. You will also learn about some strategies companies are using to mitigate the agency problem. 10 videos2 readings6 assignments In this module, you will learn the basics of financial statements. The balance sheet captures the assets, liabilities, and stockholders’ equity of a company. The income statement is used to show profit and loss. You will explore the link between these two financial statements. You will also learn how to derive cash flows from financial statements, and the sources and uses of cash flow. 8 videos2 readings7 assignments This module is the application of financial statements. You will be introduced to the concept of standardized statements. You will learn how to conduct ratio analysis to evaluate the financial health of a company. In addition, you will use financial ratios to measure the liquidity of the company, the leverage of the company, the profitability of the company, and the asset management of the company. 10 videos2 readings5 quizzes1 peer review In this module, you will be introduced to the basic concepts about the time value of money: the present value, the future value, and the net present value. You will also examine the difference between the quoted interest rate and effective annual rate. Two explicit patterns of cash flow will be studied in detail: annuity and perpetuity. There are widespread applications of time value of money in our daily life and business valuation. Some examples include mortgage plan selection, pension plan choice, and investment decisions. 7 videos4 readings5 quizzes1 assignment1 peer review

5 modules

Beginner level

https://www.coursera.org/learn/introduction-to-finance-the-basics

96%

Differential Equations Part I Basic Theory

50,725

4.7

Kwon, Kil Hyun

Korea Advanced Institute of Science and Technology(KAIST)

[]

This introductory courses on (Ordinary) Differential Equations are mainly for the people, who need differential equations mostly for the practical use in their own fields. So we try to provide basic terminologies, concepts, and methods of solving various types of differential equations as well as a rudimentary but indispensable knowledge of the underlying theory and some related applications. The prerequisites of the courses is one- or two- semester calculus course and some exposure to the elementary theory of matrices like determinants, Cramer’s Rule for solving linear systems of equations, eigenvalues and eigenvectors. 9 videos1 assignment 9 videos1 assignment 12 videos1 assignment 5 videos1 assignment 5 videos1 assignment 9 videos1 assignment 5 videos1 assignment 4 videos1 assignment 5 videos1 assignment

9 modules

Beginner level

https://www.coursera.org/learn/ordinary-differential-equations

95%

Engineering Project Management: Risk, Quality, Teams, and Procurement

41,512

4.8

Tom Phalen

Rice University

['Project Management', 'Procurement', 'Risk Management Plan', 'Project Risk Management']

Many Project Managers focus only on the scope, schedule and budget. However, a successful project requires that you manage risk, control the quality of the deliverables, engage and manage people and procure goods and services. This course will focus on these key support functions that make the difference between a highly successful project and an average one. During the course, you will prepare a Qualitative Risk Analysis and Evaluate the Cost of Quality for a provided Case Study. By the end of this course you will be able to: • Identify positive and negative risks • Develop risk strategies • Perform a qualitative risk analysis • Identify cost contingencies and reserves • Develop a quality plan • Identify quality standards • Utilize cause and effect tools • Create a prioritization matrix • Develop a team management plan that includes team development, identifying team members and clarifies roles and responsibilities • Develop a procurement plan that includes contracts and incentives All of this will position you to understand the more intangible aspects of project management to drive better overall performance. Rice Center for Engineering Leadership is a Registered Education Provider through the Project Management Institute (PMI)®. Learners who complete this course on the Certificate track will be awarded 12 hours of Profession Development Units. These are recognized by PMI for continuing education or can be applied toward the 35 hours of education required for the Project Management Professional (PMP)® certification. *PMI and PMP are registered marks of the Project Management Institute, Inc. 2 videos8 readings 9 videos2 readings4 assignments1 peer review2 discussion prompts 8 videos2 readings4 assignments1 peer review1 discussion prompt 9 videos1 reading4 assignments1 discussion prompt 6 videos1 reading4 assignments1 discussion prompt 1 video2 readings1 assignment

6 modules

Beginner level

https://www.coursera.org/learn/project-risk-quality-management

97%

Exam Prep AZ-500:Microsoft Azure Security Engineer Associate Specialization

Enrollment number not found

4.2

Whizlabs Instructor

Whizlabs

['Database Security', 'Storage Security', 'Virtual Machine', 'Network Security', 'Azure Monitoring', 'Azure Storage Accounts', 'Virtual Networks', 'Kubernetes', 'Containers', 'Microsoft Permissions Management', 'Database Security', 'Storage Security', 'Virtual Machine', 'Network Security', 'Azure Monitoring', 'Azure Storage Accounts', 'Virtual Networks', 'Kubernetes', 'Containers', 'Microsoft Permissions Management']

Exam AZ-500: Microsoft Aure Security Engineer is an intermediate-level certification for Security Engineers and Analysts. It is an important and fundamental exam for Security Engineers. This AZ-500 exam validates your skills such as implementing, managing, and monitoring security for resources in Azure,multi-cloud, and hybrid environments as part of an end-to-end infrastructure. Also, recommend security components and configurations to protect identity & access, data, applications, and networks. The Exam Prep AZ-500: Microsoft Azure Security Engineer Associate Specializationis divided into a set of 4 Courses. These courses cover Domain requirements for appearing in ExamAZ-500: Microsoft Azure Security Technologies The detail of the Courses is provided below Course 1. Azure: Identity and Access Management Course 2. Azure: Network Security Course 3. Azure: Compute, Storage, and Database Security Course 4. Azure: Security Operations Management All these courses are further divided into Modules, Lessons, and Video Items. All the courses have a set of Practice Quiz and Graded Quiz available that test the candidate's ability to understand the concept and grasp the topics discussed in the courses. Applied Learning Project Whizlabs is a renowned provider of Hands-on learning opportunities in a diverse range of technologies including Cloud Computing (AWS, Azure, GCP), DevOps, Java, Big Data, Snowflake, CompTIA, Cybersecurity, and Blockchain. Since its inception in 2000, Whizlabs has assisted more than 10 million professionals and learners worldwide to accomplish their career objectives by offering an extensive selection of courses, hands-on labs, practice tests, and a Cloud Sandbox. Explore the concepts of Azure Active Directory (Azure AD) Demonstrate the concepts of Azure AD Protection Services Analyze the concepts of Manage identities in Azure AD Demonstrate the concepts of Authentication and Authorization in Azure AD Explore the concepts of Application access in Azure AD Explore the concepts of Azure Virtual Networks(VNets). Configure and implement Security for Virtual Networks(VNets). Configure Public & Private Security Access to Azure Resources. Demonstrate the concepts of Azure Firewall Manager and Application Gateway. Explore the concepts of Azure VMs, Storage Accounts, Container, and SQL DB services Analyze Advanced Security for Compute Resources Configure and Implement Security for Storage Services Demonstration of Kubernetes, Containers, SAS, and SQL DB services Demonstrate the concepts of Microsoft Defender for Cloud - Security Posture & Threat Protection Configure Security Governance in Azure Implement Security Monitoring and Automation Solutions Demonstrate the concepts of Microsoft Sentinel

4 course series

Intermediate level

6 months (at 2 hours a week)

https://www.coursera.org/specializations/exam-prep-az-500-microsoft-azure-security-engineer-associate

Cybersecurity Identity and Access Solutions with Azure AD

Enrollment number not found

Rating not found

Microsoft

Microsoft

['Information Security (INFOSEC)', 'Authentication Methods', 'Access Management', 'Enterprise Security', 'Enterprise security', 'Identity governance', 'Identity Governance']

In this course, you’ll explore the world of authorization and authentication, and understand the concepts of two-step authentication and single sign-on policies. You’ll also become familiar with the features and capabilities of Azure Active Directory (Azure AD), particularly those relating to the benefits of using Azure AD to manage an enterprise’s security requirements including access management, identity governance, and management. This course will take you one step closer to the Microsoft Cybersecurity Analyst Professional Certificate, which requires no degree or prior experience. Examine Azure Active Directory identity services. Learn about the various subscription packages, managing users and groups, Azure Active Directory identity types, and how Azure Active Directory facilitates SaaS. 10 videos21 readings5 assignments1 discussion prompt Learn about the different authentication methods and features available in Azure Active Directory to help improve and secure sign-in events. Learn how to use authentication to verify and control access and permissions to various resources to better security overall. 12 videos12 readings6 assignments Explore Azure Active Directory as a tool for identity and access management in Microsoft Cloud. Learn about Azure AD services and identity principals, secure authentication, access management capabilities, as well as identity protection and governance. 10 videos15 readings6 assignments Put your skills into practice by configuring identity and access policies for the end-of-course project and reinforce your understanding of the key concepts you’ve learned. 2 videos5 readings2 assignments1 discussion prompt

4 modules

Beginner level

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

https://www.coursera.org/learn/cybersecurity-identity-access-solutions-azure-ad

TOEFL Speaking and Writing Sections Skills Mastery

17,336

4.4

Shiva Sutherland

University of California, Irvine

[]

This course prepares non-native speakers of English to take the speaking and writing sections of the TOEFL iBT exam. This course explains the difference between the integrated tasks and independent tasks in the speaking and writing sections of the iBT and provides effective strategies for tackling each task. For each type of prompt, you will learn how to best plan your responses, which is a key step to providing well-formed and organized answers. This course also teaches how to best practice and prepare for test day as well as how to manage your time and perform optimally during the exam. With plenty of practice, you will know exactly what to expect when you take the actual test, reducing anxiety and boosting your confidence. Join this course and give yourself the best chance to reach your target scores on the speaking and writing sections of the TOEFL iBT. In this first week, you will become familiar with a question type that you will encounter on the real iBT speaking portion of the TOEFL test, specifically the independent speaking task." You will also practice answering some speaking sample questions with suggested templates. This will help you know what to expect when you answer speaking questions and be prepared to plan your responses. 3 videos3 readings1 assignment1 discussion prompt In this second week, you will become familiar with a question type that you will encounter on the real iBT speaking portion of the test, specifically the integrated speaking tasks. You will also practice answering some speaking sample questions with suggested templates. This will help you know what to expect when you answer to speaking questions and be prepared to plan your responses. 3 videos1 reading1 assignment1 discussion prompt In this third week, you will become familiar with a question type that you will encounter in the real iBT writing portion of the test, specifically the Independent writing task. You will also practice answering some sample questions with suggested templates. This will help you know what to expect when you complete the writing section of the test and be prepared to plan your answers. 2 videos1 reading1 assignment1 discussion prompt In this fourth week, you will become familiar with a question type that you will encounter on the real iBT writing portion of the test, specifically the Integrated writing task. You will also practice answering some sample questions with suggested templates. This will help you know what to expect when you complete the writing section of the test and be prepared to plan your answers. 2 videos1 reading1 assignment1 discussion prompt

4 modules

Beginner level

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

https://www.coursera.org/learn/toefl-speaking-writing-sections-skills-mastery

Social Determinants of Health: Vulnerable Populations

Enrollment number not found

Rating not found

Daniel J. Pesut, Ph.D., RN, FAAN

University of Minnesota

['Health Informatics', 'Data Analysis', 'Health Equity', 'Data Visualization']

This second of five courses focuses on how social determinants of health affects vulnerable populations. Focusing on four groups of vulnerable populations, students will examine how social determinants of health contribute to the poor health outcomes experienced by these populations. The topics of this course include: 1. Poverty 2. Women’s Health 3. Gender and LGBTQI+ Health 4. Family Health 5. Data Applications: t-test Analysis and Box Plot Visualization In this module, we will discuss how poverty relates to health as we examine the interrelationships between poverty and other social determinants of health. In lesson one, we will define poverty, as we explore how poverty both causes and is caused by poor health. We will also look at some policy perspectives aimed at eradicating poverty. In lesson two, we will continue our discussion from lesson one, as we evaluate different approaches, perspectives and solutions to ending poverty. We will also consider how success is measured when evaluating the effectiveness of these proposed interventions. 3 videos7 readings2 assignments1 discussion prompt5 plugins In this module, we will consider the gender-specific impact of social determinants of health on women. In lesson one, we will review what defines a health inequity for women and examine how gender acts as an axis of health disparity. Lesson two focuses on reproductive health and the need for contraception. We will look at how the SDOH shape resources and accessibility for women at global and national levels, and how reproductive rights are tied to human rights for girls and women. Lesson three continues to build on the content from previous lessons, with a more in-depth look at maternal health. We will investigate how the SDOH impacts aspects of maternal health with a focus on pregnancy related mortality and its prevalence on global and national levels. We will also examine how structural racism drives health disparities and specifically, maternal outcomes. In lesson four, we will summarize the factors that shape gender-based health disparities and the impact on women, while investigating policy-based strategies and resources to improve health outcomes for women while addressing SDOHs. 4 videos13 readings2 assignments1 discussion prompt In this module, we focus on the social determinants of health in LGBTQI+ populations. In lesson one, we will define important terminology related to LGBTQI+ health needs as we look at LGBTQI+ vulnerabilities to the social determinants of health. In lesson two, we will examine how heteronormativity and cisnormativity can act as negative social determinants of LGBTQI+ health and wellbeing as we consider how media and language can perpetuate these inequalities. In lesson three, we consider how microaggressions, discrimination, and implicit bias can contribute to a healthcare system bias that negatively impacts the accessibility and quality of care received by LGBTQI+ patients. In lesson four, we will review key dates in LGBTQI+ history in the United States, as we investigate social and structural level changes that can improve LGBTQI+ health outcomes. 4 videos7 readings2 assignments1 discussion prompt2 plugins In this module, we will examine the social determinants of health for families with young children and discuss policy-based strategies for improving health outcomes. In lesson one, we’ll explore the Rainbow Model as a way to understand how social determinants affect the health of young children. We will also review the different pathways through which socioeconomic circumstances influence health and contribute to child health inequalities. Applying what we learned in the previous lesson, in lesson two, we will look at a case study in order to investigate how social determinants influence a family’s ability to promote child health. Finally in lesson three, we will analyze some strategies for improving health outcomes for families with young children through policies that address social determinants of health. 3 videos2 readings2 assignments1 discussion prompt This module will focus on analyzing, displaying and interpreting social determinants of health data, with a particular focus on comparing social determinants by group. Lesson one will provide an overview of t-test analysis and box plot visualization. In lesson two, we will learn how to conduct t-test analyses and create boxplots in R. Using the NHANES dataset, we will compare general health and Hgb a1c by gender. Using the Omaha System dataset, we will compare total signs & symptoms, social determinant of health signs & symptoms, and income signs & symptoms by gender. Finally, we will discuss how to interpret the results of our analysis as we visualize our findings using boxplots. 2 videos3 readings1 peer review1 discussion prompt1 ungraded lab3 plugins

5 modules

Beginner level

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

https://www.coursera.org/learn/sdoh-vulnerable-populations

Wharton Business and Financial Modeling Capstone

10,824

4.6

Richard Lambert

University of Pennsylvania

['Summary Statistics', 'Financial Modeling', 'Diversification (Finance)', 'Investment']

In this Capstone you will recommend a business strategy based on a data model you’ve constructed. Using a data set designed by Wharton Research Data Services (WRDS), you will implement quantitative models in spreadsheets to identify the best opportunities for success and minimizing risk. Using your newly acquired decision-making skills, you will structure a decision and present this course of action in a professional quality PowerPoint presentation which includes both data and data analysis from your quantitative models. Wharton Research Data Services (WRDS) is the leading data research platform and business intelligence tool for over 30,000 corporate, academic, government and nonprofit clients in 33 countries. WRDS provides the user with one location to access over 200 terabytes of data across multiple disciplines including Accounting, Banking, Economics, ESG, Finance, Insurance, Marketing, and Statistics. Welcome! This opening module was designed to give you an overview of the Business and Financial Modeling Capstone, in which you will be working with historical financial data to calculate individual returns and summary statistics on those returns. The project has multiple steps, which are outlined below in the "Project Prompt", and culminates in a recommendation for portfolio allocation that you will prepare a presentation on. You will draw on elements from all courses to complete this project, and you can use your final presentation as a work sample to improve your current job or even find a new one. Before moving on, complete the "Project Scope Quiz." The work you do this week enables you to understand the steps needed to successfully complete your final project. 3 readings1 assignment2 discussion prompts In this module, which correlates to Steps 1 and 2 in the Project Prompt, you'll be working with a historical data set to calculate performance data and to provide summary statistics on that data. These calculations will allow you to practice using Spreadsheets for financial calculations, and provides the foundational skills and numbers for the next steps of the project. First, you'll use the set to calculate daily returns on a set of securities. You'll then use your Spreadsheet skills to calculate summary statistics. You'll be given the opportunity to test your knowledge with a sample return to see if your calculations are correct. And you may want to refresh your recollection of the content from the Specialization with the lectures included here. The work you complete this week allows you to form the basis for comparing stock performance, which you will use in creating the investment portfolio for your final project as well as the comparison to the performance of a single stock. 6 videos4 readings2 assignments1 discussion prompt In this module, you'll go beyond calculating simple returns to tackle the more advanced task of finding the minimum variance and "optimal risk portfolio" weights for a portfolio of selected securities (note, the "optimal risky portfolio" is also known as an "optimal portfolio" or "tangent portfolio"). You'll follow the tasks in Step 3 in the Project Prompt and use the resources below to calculate the portfolio weights for two securities that results in the portfolio with the minimum variance; then, you'll calculate the "optimal risky portfolio" on the efficient frontier for these same two securities, then for all 10 stocks in the pool. You'll be quizzed on your calculations and other insights that emerge from this exercise. The work you complete this week gives you practice in creating an optimal risky portfolio, which is a key component of your final project. Note: There are a number of resources available on the internet providing step-by-step instructions on how to use Excel to create an "optimal risky portfolio" on the efficient frontier given a certain set of available assets. We encourage you to attempt to use the skills you gained during the Specialization to work through these steps independently; you are, however, permitted to utilize third-party resources if you find it necessary. We've included some lectures from the underlying Specialization courses concerning Solver, optimization, and other relevant topics. 7 videos5 readings1 assignment2 discussion prompts The Capital Asset Pricing Model, or CAPM, is another tool used by investors to weigh the risks and rewards of potential investments. In this optional module covering Step 4 in the Project Prompt, you can use CAPM as a vehicle to further strengthen your financial modeling skills, including using regression concepts. You may revisit the Specialization lectures below touching on regression. To test whether you've grasped the concepts in the CAPM model, this module includes a short quiz. This assessment is formative, meaning your score will not count towards your final grade. The work you do this week may inform how you build the mixed asset portfolio of your final project, but it is not necessary to complete the final project. 3 videos3 readings1 assignment1 discussion prompt In this final module you are asked to move beyond a stock-only portfolio to one utilizing more diversified assets and to prepare a short presentation summarizing your findings. As explained in Step 5 of the Project Prompt, you have $5 million to invest in the Vanguard Total Bond Market Index Fund (ticker: VBTLX) and Vanguard 500 Index (ticker: VFIAX) investment vehicles. There are two assessments in this module. First, you'll complete a short quiz on the characteristics of your optimal risky portfolio. Then, in the peer review component of this Capstone, you are tasked with preparing a short presentation that (i) explores how your portfolio of mixed asset class of funds compares to a single security (AAPL) and (ii) uses that comparison to discuss the importance of portfolio diversification. 1 reading1 assignment1 peer review3 discussion prompts

5 modules

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

https://www.coursera.org/learn/wharton-business-financial-modeling-capstone

80%

Introduction to Applied Machine Learning

25,129

4.7

Anna Koop

Alberta Machine Intelligence Institute

[]

This course is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this course will introduce you to problem definition and data preparation in a machine learning project. By the end of the course, you will be able to clearly define a machine learning problem using two approaches. You will learn to survey available data resources and identify potential ML applications. You will learn to take a business need and turn it into a machine learning application. You will prepare data for effective machine learning applications. This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute. This week, you will learn about what machine learning (ML) actually is, contrast different problem scenarios, and explore some common misconceptions about ML. You will apply this knowledge by identifying different components essential to a machine learning business solution. 12 videos6 readings2 assignments3 discussion prompts This week, you will learn how to translate a business need into a machine learning problem. We'll walk through some applied examples so you can get a feel for what makes a well-defined question for your QuAM. Narrowing down your question and making sure you have the data necessary to learn is critical to ML success! 8 videos4 readings1 assignment2 discussion prompts This week is all about data. You will learn about data acquisition and understand the various sources of training data. We'll talk about how much data you need and what pitfalls might arise, including ethical issues. 9 videos2 readings1 assignment2 discussion prompts This week you will learn about the Machine Learning Process Lifecycle (MLPL). After understanding the definitions and components of the MLPL you will analyze the application of the MLPL on a case study. 7 videos2 readings1 assignment2 discussion prompts

4 modules

Intermediate level

https://www.coursera.org/learn/machine-learning-applied

99%

Cyber Threats and Attack Vectors

30,594

4.7

Greg Williams

University of Colorado System

[]

Data breaches occur nearly every day. From very large retailers, down to your fantasy football website, and anywhere in between, they have been compromised in some way. How did the attackers get in? What did they do with the data they compromised? What should I be concerned with in my own business or my systems? This course is the second course in the Practical Computer Security. It will discuss types of threats and attack vectors commonly seen in today’s environment. I hate to be the bearer of bad news, but threats are all over the place! This course isn’t designed to insight fear that there is no hope for keeping systems and business secure, but rather educate you on how attacks are carried out so that you have a better sense of what to look out for in your business or with your systems. Welcome! This week we'll explore users and user based attacks. User based attacks are common because it may be easier to compromise a human rather than a computer. 5 videos4 readings2 assignments1 discussion prompt Threats against networks and systems are the most common type of attack method. This week will explore these concepts. 3 videos4 readings2 assignments1 discussion prompt You use the cloud every day; you may not even realize it! This week will focus on the cloud and security surrounding cloud and cloud services. 4 videos3 readings2 assignments1 discussion prompt The week will focus on common vulnerabilities that systems face and how they work. 4 videos3 readings2 assignments1 discussion prompt Data breaches occur daily. Sometimes they are announced right away, other times they are found out months after the compromise. This week will focus on the course project. 1 video1 peer review

5 modules

Beginner level

https://www.coursera.org/learn/cyber-threats-attack-vectors

97%

Putting the Personal in Personalized Nutrition

Enrollment number not found

Rating not found

Sharon M. Donovan

University of Illinois Urbana-Champaign

['Epigenetics', 'Registered Dietitian (RD/RDN)', 'Human Nutrition', 'Dietary Analysis']

A “one size fits all” approach to nutrition may not work for everyone. We each have unique variations in our genome, epigenome and microbiome, which interact with our external environment to affect how our bodies respond to dietary intake. Learners will exam the basic principles of nutrition, explore the foundational aspects of personalized nutrition, and analyze the research about the roles of genetics and microbiomes in our personalized nutrition journey. This course is part of the College of ACES suite of online programs, including the graduate-level certificate, "Food Regulations, Nutrition Policy, and Personalized Nutrition" that can be stacked toward an online master's degree. To learn more about online programs from the College of ACES and explore ways to apply your Coursera work toward a degree program at the University of Illinois, visit ACES Online at acesonline.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. In the second part of this module, you will explore the basics of nutrition and describe nutrient components. You will differentiate between macro and micronutrients and understand the concept of essential nutrients. Lastly, this module will explore dietary variety and recognize the importance of consuming a diverse range of foods to meet nutrient needs as well as navigating the dietary guidelines. 15 videos11 readings2 assignments1 discussion prompt At the conclusion of this module, you will understand the intricacies of tailoring dietary recommendations to individual needs. Throughout this module, we'll define personalized nutrition, contextualize it within the broader spectrum of dietary guidance, and delve into the factors influencing individuals' responses to food. Prepare to uncover the science behind personalized nutrition and its practical applications. 8 videos3 readings1 assignment At the conclusion of this module, you will uncover the fascinating intersection of genetics and personalized nutrition. We’ll unravel how single nucleotide polymorphisms influence our genetic makeup and impact our health. You will recognize the essential relationship between DNA, mRNA, and proteins—the molecular players that shape our nutritional responses. 12 videos1 reading1 assignment At the conclusion of this module, you will be ready to complete the final assessment for the course and earn your Coursera certificate! You will delve into the intricate world of microbiota and microbiome—the tiny ecosystems within our bodies that play a pivotal role in our well-being. We’ll explore the fascinating link between personalized nutrition and the gut microbiota. 8 videos6 readings2 assignments

4 modules

Intermediate level

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

https://www.coursera.org/learn/putting-the-personal-in-personalized-nutrition

Market Research and Consumer Behavior

135,535

4.4

Shameek Sinha

IE Business School

['Market Research', 'Consumer Behaviour', 'Data Analysis']

Your marketing quest begins here! The first course in this specialization lays the neccessary groundwork for an overall successful marketing strategy. It is separated into two sections: Market Research and Consumer Behavior. Gain the tools and techniques to translate a decision problem into a research question in the Market Research module. Learn how to design a research plan, analyze the data gathered and accurately interpret and communicate survey reports, translating the results into practical recommendations. You will then focus in on the consumer decision-making process, highlighting the key moments from identifying a need to buying and consuming a product. Adopt a true “consumer focus” in your managerial decisions by analyzing how consumers make decisions, what happens (in their hearts and minds) at different stages of the decision making process, and the variables that influence those decisions. This course will equip you with the knowledge required to understand the state of your product before approaching the market strategy. There’s no better place to build the foundations of your marketing journey! This Course consists of two blocks: Marketing Research and Consumer Behavior. First, learners will see the tools and methods to be able to effectively conduct (or hire) and interpret marketing research. Second, they will learn the foundations of consumer behavior and the consumer decision-making process and how to use this knowledge in the formulation of effective marketing strategies and tactic. In this first module, you will head-dive into your consumer's thought-processes to really get to know what makes them tick, and, more specifically, what makes them make their purchase decisions. Getting into the mind of your customer is the first step in developing a marketing strategy that is effective. 8 videos1 reading1 assignment Module 2 will guide you through the consumer decision-making process. Here you will explore how a potential-buyer researches a product, how they make their purchase decision, and their post-purchase evaluation. You will also understand the difference between consumer markets and business markets. 7 videos1 reading1 assignment In the second half of this course, you will explore the world of marketing research. In Module 3, Professor Sinha will share with you the importance of market research and how to acquire data. Later, you will delve into the different types of experimental research and design. 8 videos1 assignment In the last Module of this course, you will learn with more detail the various types of data acquired during the marketing research process and how to evaluate and assess it. Discovering the importance of, and how to create an effective survey, will also be covered.In the second half of this course, you will explore the world of marketing research. 6 videos1 reading1 assignment

4 modules

Beginner level

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

91%

Workday Basics Series

24,927

4.7

Workday Education

Workday

['Workday Reporting', 'Workday (Software)', 'Workday Terminology', 'Business Process', 'Configurable Security Frameworks']

The Workday Basics Series is an introduction to the Workday platform, priming you for a career with Workday technology. You’ll learn about the core functionalities of Workday and the foundational frameworks that allow Workday to support some of the largest organizations in the world. You will start out with Workday Basics, where you will learn about Workday terminology, navigation, the business process framework, configurable security, and object-oriented reporting. Then you will move on to Workday Beyond Basics, where you will learn about the Workday update process, tenant branding, advanced security controls, data analytics functionality, and how Workday helps business users improve operational efficiency. The Workday Basics Series is designed to be your first-step towards learning the Workday platform and determining if a career with Workday technology is right for you. No prior Workday training is required or expected. If you commit to earning a certificate, you will be eligible for a Workday Basics badge and can join the Learn with Workday Talent Directory to signal your interest in joining the Workday ecosystem. Workday Basics is your entry point to a rewarding career using Workday technology. In this course, you will learn why companies choose Workday. You will also gain an understanding of the foundational frameworks that allow Workday to uniquely support organizations and their goals. 38 videos14 readings12 assignments Welcome to Workday Beyond Basics! Workday Basics served as your entry point to Workday. Beyond Basics is the next step in your journey. In this course, you will dive deeper into the Workday framework, review additional Workday products and features, and explore real world business cases that showcase Workday in action. 24 videos29 readings8 assignments

2 modules

Beginner level

https://www.coursera.org/learn/workday-basics-series

91%

Power System Modelling and Fault Analysis

Enrollment number not found

Rating not found

Subject Matter Expert

L&T EduTech

['Short Circuits Analysis', 'Grid Layout', 'Simulations', 'Power System Modelling']

This course is designed to provide a detailed description of modeling of power system components and analyze of various types of symmetrical and unsymmetrical faults occurring in a power system network. By the end of this course, you will be able to: • Develop a comprehensive understanding of the structure and nature of an electrical grid system, issues faced in grid operations and types of grid interconnections. (BL2) • Draw the single line diagram representation of a three-phase power system using standard symbols. (BL3) • Develop the per unit impedance and reactance diagram from a given single line diagram of a power system network. (BL3) • Model the various power system components namely generator, transformers, and transmission lines for equivalent circuit representation for further analysis and investigation. (BL4) • Perform the analysis of power system when subjected to symmetrical or unsymmetrical faults based on Thevenin’s circuit representation and as a outcome design as suitable protection scheme by sizing the Circuit Breaker and Fuse. (BL4) • Elucidate the concept of symmetrical component transformation in unsymmetrical fault analysis. (BL3) This course provides a specialized focus on power system modeling and fault analysis supported with realistic industry test cases. The course stands out for its hands-on ETAP demonstrations, which is an industrial software used in power grid sectors, providing learners with practical skills in the field of power system design and analysis. Additionally, it touches upon the various details involved in the modeling of power system components and short circuit studies, catering to real time scenarios and case studies. To be successful in this course, you should have a background in basic electrical engineering principles, including knowledge of circuit analysis, electromagnetism, mathematical modelling and transmission and distribution of electrical power. Familiarity with any simulation packages such as MATLAB, POWER WORLD will be beneficial for hands-on exercises. By enrolling in this course, participants will not only gain theoretical knowledge but also practical skills that are directly applicable in the field of power system analysis and design Whether you're a student aspiring to enter the industry or a professional seeking to deepen your expertise, this course offers a unique blend of theoretical insights and hands-on applications, equipping you with the tools to excel in this dynamic field. Let’s begin this course by understanding the basic structure of electrical grid system, merits, demerits and challenges involved, grid interconnections, various studies carried out in a power system and the need for power system analysis. 16 videos2 readings1 assignment1 discussion prompt This module imparts knowledge on per unit system calculations, modelling of the various power system components in the form of equivalent circuits and their representation in impedance / reactance diagram. 13 videos1 assignment1 discussion prompt This module aims to explore the various types of faults occurring in a power system, the concept of symmetrical components and analysis of symmetrical faults 18 videos1 assignment1 discussion prompt This module helps to understand the various types of unsymmetrical faults and details the analysis of unsymmetrical faults with interconnection of sequence networks. 14 videos1 assignment1 discussion prompt

4 modules

Intermediate level

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

https://www.coursera.org/learn/industrial-power-system-analysis-and-stability

Calculus through Data & Modelling: Integration Applications

1,561

4.7

Joseph W. Cutrone, PhD

Johns Hopkins University

[]

This course continues your study of calculus by focusing on the applications of integration. The applications in this section have many common features. First, each is an example of a quantity that is computed by evaluating a definite integral. Second, the formula for that application is derived from Riemann sums. Rather than measure rates of change as we did with differential calculus, the definite integral allows us to measure the accumulation of a quantity over some interval of input values. This notion of accumulation can be applied to different quantities, including money, populations, weight, area, volume, and air pollutants. The concepts in this course apply to many other disciplines outside of traditional mathematics. We will expand the notion of the average value of a data set to allow for infinite values, develop the formula for arclength and curvature, and derive formulas for velocity, acceleration, and areas between curves. Through examples and projects, we will apply the tools of this course to analyze and model real world data. In this module, we generalize the notion of the average value of a (finite) set of points. Did you ever wonder how we compute the average temperature during the day if infinitely many temperature readings are possible? Or how the average rainfall is calculated? The notions in this module will allow us to expand the idea of an average value to compute averages with (infinite) values over a continuous interval. 1 video1 reading1 assignment What do we mean by the arc length of a curve? We might think of fitting a piece of string to the curve and then measuring the string against a ruler. But this is difficult to do when working with a complicated curve. In this module we develop the precise notion of the length and curvature of an arc of a curve in both the xy plane and in space. 3 videos1 reading1 assignment In this module, we show how the ideas of tangent and normal vectors can be used in physics to study the motion of an object, including its velocity and acceleration, but now we focus on curves in three dimensional space. The techniques developed here then allow us to study the rates of change for more advanced functions. 1 video2 readings1 assignment Finding the area between two curves is not just an interesting application of definite integrals from a geometric view, but when working with the appropriate functions, has applications in economics, business, and even medicine. 3 videos1 reading2 assignments

4 modules

Intermediate level

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

https://www.coursera.org/learn/calculus-through-data-and-modelling-integration-applications

Supply Chain Management: A Learning Perspective

92,281

4.7

Bowon Kim

Korea Advanced Institute of Science and Technology(KAIST)

['Supply Chain Risk Management', 'Supply Chain', 'Inventory']

As a human being, we all consume products and/or services all the time. This morning you got up and ate your breakfast, e.g., eggs, milk, bread, fresh fruits, and the like. After the breakfast, you drove your car to work or school. At your office, you used your computer, perhaps equipped with 27” LCD monitor. During your break, you drank a cup of coffee and played with your iPhone. So on and so forth. You probably take it for granted that you can enjoy all of these products. But if you take a closer look at how each of these products can be made and eventually delivered to you, you will realize that each one of these is no short of miracle. For example, which fruit do you like? Consider fresh strawberries. In order for the strawberries to be on your breakfast table, there must be numerous functions, activities, transactions, and people involved in planting, cultivating, delivering, and consuming strawberries. Moreover, all of these functions, activities, transactions, and people are connected as an integral chain, through which physical products like strawberries themselves and virtual elements such as information and communication flow back and forth constantly. By grouping related functions or activities, we have a supply chain, comprised of four primary functions such as supplier, manufacturer, distributor, and finally consumer. A supply chain is essentially a value chain. For the society or economy as a whole, the goal is to maximize value, i.e., to create satisfactory value without spending too much. In order to create the maximum value for the strawberry supply chain, every participant in the chain must carry out its function efficiently. In addition, all of the members must coordinate with each other effectively in order to ensure value maximization. We have to face the same issues for almost all the products and services we take for granted in our everyday life, e.g., cars, hamburgers, haircuts, surgeries, movies, banks, restaurants, and you name it! In this course, we want to understand fundamental principles of value creation for the consumers or the market. We try to answer questions like how the product or service is made, how the value-creating activities or functions are coordinated, who should play what leadership roles in realizing all these, and so on. As our course title hints, we approach all of these issues from a learning perspective, which is dynamic in nature and emphasizes long-term capability building rather than short-term symptomatic problem solving. In this chapter, Professor Bowon Kim briefly introduces students to this course. It is about philosophical and moral foundation of a supply chain management. 5 videos In this chapter, we will learn what a supply chain is, what supply chain management is all about, and why it is important to grasp the fundamentals of supply chain management in creating real value for the customers. 6 videos1 reading1 assignment Effective SCM requires the firm to have strong operations capabilities. One can group various operations capabilities into three representative capabilities: Controllability, flexibility, and integrating capability. In order to be competitive in the market, the firm must retain high levels of these capabilities. In this chapter, we will discuss what the management capabilities are and the relationship among these capabilities. 9 videos1 assignment Learning is an essential part of any creative activity. In this chapter, we will learn what the learning capability is and its dynamics in supply chain management. We will also look into the learning propensity model and how the learning processes influence the performance of a supply chain system. 9 videos1 assignment Quality is one of the most important factors that determine the utility. That is, the higher the quality, the larger the utility experienced by the customer. But, quality is not a one-dimensional concept. In fact, it is a highly complex, multi-layered one. In this chapter, we will explore this complex concept, 'Quality'. We will learn dimensions of quality, total quality management (TQM), quality dynamics and statistical process control (SPC) in detail. 9 videos1 assignment New product innovation is the key to firm's success. In order to sustain successful business, the firm must design and manage its new product process effectively and efficiently. In this chapter, we will learn new product innovation and new product development process. Especially, we will look into and compare two approaches, traditional approach and cross-functional approach. 6 videos1 assignment In order to optimize the supply chain performance, the firm must design its supply chain effectively. In this chapter, we will talk about how to design the effective supply chain and look into the designing factors of supply chain management in detail. 7 videos1 assignment Coordination is the key dimension of infrastructure in supply chain management. In this chapter, we will talk about what supply chain coordination is and why it is important. And we will learn vendor-managed inventory (VMI) and postponement in detail. 4 videos1 assignment Why is the effective SCM important for the firm to gain competitive advantage in the global market? In this chapter, we will consider crucial issues related to the question and deal with global supply chain management and value chain sustainability. 5 videos1 assignment The final exam is based on the concepts and theories we have learned in this course. It includes 30 multiple choice questions. 1 assignment

10 modules

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

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

98%

Advancing Proficiency in U.S. Payroll Fundamentals

Enrollment number not found

5.0

ADP Learning Academy

Automatic Data Processing, Inc. (ADP)

['Tax Compliance', 'Employee Data Management and Recordkeeping', 'Payroll Fundamentals', 'Worker Classifications', 'Payroll Tax Management']

Welcome to Advancing Proficiency in U.S. Payroll Fundamentals, the fourth course in ADP's Entry-level Payroll Specialist Professional Certificate program. Module 1 focuses on the responsibilities of an employer as it relates to net pay, tax deposits, and filings. Module 2 will explore the taxes employers are responsible for withholding from their employees' paychecks. Module 3 explores the regular deposits and filings required by most employers in the U.S. This is an entry-level course intended for beginner learners interested in learning the fundamentals of payroll, those pursing an entry-level Payroll Specialist role, and more experienced professionals looking to shift their career to purposefully focus on the area of a Payroll Specialist. This module will provide you with the knowledge to understand all the variables that contribute to the transformation of gross pay into net pay. 10 videos5 readings5 assignments1 discussion prompt This module will explore the employer's responsibilities when it comes to federal and state payroll taxes and the proper withholding of them. You will also learn the best practices surrounding federal and state unemployment taxes. 5 videos7 readings6 assignments1 discussion prompt This module will describe the responsibilities of an employer in regards to regular federal deposits and filings. You will the typical timeline and forms needed to properly manage tax filings. 7 videos6 readings5 assignments1 discussion prompt

3 modules

Beginner level

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

https://www.coursera.org/learn/adp-advancing-proficiency-in-us-payroll-fundamentals

Learn English: Intermediate Grammar Specialization

131,450

4.8

Tamy Chapman

University of California, Irvine

['English Grammar', 'Perfect Tenses', 'English Language', 'Adjective']

This specialization covers common topics in intermediate grammar, such as perfect verb tenses and adjective clauses. It will also cover "tricky English" grammar topics that learners of English often find frustrating. The capstone will give you a chance to review all of the knowledge you've learned in the courses and create a multi-media "scrapbook" of grammar to keep with you after the specialization ends. This is the first course in the Learn English: Intermediate Grammar specialization. In this course, you will learn about important intermediate verb tenses, including present perfect, present perfect progressive, past perfect, and past perfect progressive. You will also learn about common modal verbs used in English. This course is designed for learners who have a basic understanding of English grammar but who want to learn more and improve their skills for everyday speaking or writing, as well as for academics. It will be a fun class with lots of entertaining and informative video lectures. Being able to adeptly use adjective clauses in speaking and writing is useful for upper level English learners. Adjectives and adjective clauses are very common in English, so students need to be able to understand them when they see them or hear them. Students often struggle to bring complexity to their speaking and writing and adjective clauses can be a great way to do this. Please note that all of the lectures and practice activities are available for free, but taking the quizzes and getting feedback on assignments are only available in the paid version 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. If you have taken the three courses in this specialization, you have learned a lot of grammar in the last few months. This will be a big help to your studies or your career. This capstone project will help you process what you've learned and help you remember it forever. You will create a grammar scrapbook of the difficult or interesting English grammatical structures that you studied in the specialization. You will choose a multi-media tool of your choice, such as video or e-book, to showcase proper use of the grammar. You will also give authentic examples of the grammar found in articles, movies, or songs to make the scrapbook interesting. This will be a scrapbook that you can keep with you long after this specialization ends.

4 course series

Intermediate level

3 months (at 10 hours a week)

https://www.coursera.org/specializations/intermediate-grammar

AI in Healthcare Capstone

12,341

4.7

Matthew Lungren

Stanford University

[]

This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a primary care provider. We will follow the patient's journey from the lens of the data that are created at each encounter, which will bring us to a unique de-identified dataset created specially for this specialization. The data set spans EHR as well as image data and using this dataset, we will build models that enable risk-stratification decisions for our patient. We will review how the different choices you make -- such as those around feature construction, the data types to use, how the model evaluation is set up and how you handle the patient timeline -- affect the care that would be recommended by the model. During this exploration, we will also discuss the regulatory as well as ethical issues that come up as we attempt to use AI to help us make better care decisions for our patient. This course will be a hands-on experience in the day of a medical data miner. In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding 1) Date of the original release and expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content. 2 readings2 assignments2 peer reviews 1 reading2 assignments2 peer reviews 1 reading2 assignments2 peer reviews 1 reading2 assignments2 peer reviews 3 readings1 assignment1 peer review

5 modules

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

https://www.coursera.org/learn/ai-in-healthcare-capstone

Pre-formulation

Enrollment number not found

4.7

Erland Stevens, PhD

Novartis

[]

In this course we will focus on how active compounds are developed into a formulation suitable for dosing in animal studies and early human clinical trials.  Factors such as the route of administration, enhancing the solubility of the drug substance, the crystalline form of the drug substance, drug substance vs. drug product, storage requirements, and how special requirements of the patient population play a role in the design of an ideal formulation will be covered.  Finally, some of the differences encountered when formulating a biologic vs. a small molecule will be discussed. Target audience: This course is suitable for life scientists, clinicians, and individuals from fields that support drug discovery (e.g., patents, finance, licensing, etc.) interested in learning more about the pharmaceutical/biotechnology sector. Advanced undergraduate coursework or practical familiarity/working knowledge in biological sciences and organic chemistry is recommended. Welcome, by the end of the course students will be able to: Define the concepts of formulation, drug substance, and drug product. Describe the role of pre-formulation in drug discovery and its impact on route of administration selection. List and explain the importance of physicochemical properties in drug discovery and development. Compare and contrast the pre-formulation considerations for small molecule drugs and biologics. 4 videos1 reading3 assignments 5 videos6 assignments 5 videos5 assignments

3 modules

Intermediate level

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

https://www.coursera.org/learn/pre-formulation

Responsible AI Practices

Enrollment number not found

Rating not found

AWS Instructor

Amazon Web Services

[]

In this course, you will learn about responsible artificial intelligence (AI) practices. In the first section of this course, you will be introduced to what responsible AI is. You will learn how to define responsible AI, understand the challenges that responsible AI attempts to overcome, and explore the core dimensions of responsible AI. Then in the next section of the course, you will dive into some topics for developing responsible AI systems. In this section of the course, you will learn about some of the services and tools that AWS offers to help you with responsible AI. You will also learn about responsible AI considerations for selecting a model and preparing data for your AI systems. Finally, in the last section of the course, you learn what it means for a model to be transparent and explainable. You will also learn about tradeoffs to consider between safety and transparency for an AI model and the principles of human-centered design for explainable AI. 1 reading1 assignment

1 module

Beginner level

1 hour to complete

https://www.coursera.org/learn/responsible-artificial-intelligence-practices

Build Website with HTML, JavaScript, AngularJS, and React Specialization

2,789

4.3

Board Infinity

Board Infinity

['Jquery', 'HTML', 'React (Web Framework)', 'JavaScript', 'Angularjs', 'Cascading Style Sheets (CSS)', 'Jquery', 'HTML', 'React (Web Framework)', 'JavaScript', 'Angularjs', 'Cascading Style Sheets (CSS)']

Dive deep into the world of modern web development with this comprehensive specialization. Comprising three distinct courses, this curriculum empowers learners to create cutting-edge, dynamic websites by combining essential front-end technologies: 1. Building Webpages with HTML and CSS: Introduction to the backbone of web development: HTML and CSS. Constructing web pages from scratch, diving into HTML elements like headlines, paragraphs, lists, and links. Advanced styling techniques using CSS properties and selectors. Embrace responsive design with Bootstrap, ensuring your websites look impeccable on all devices. 2.JavaScript for Web Development: Start with the foundation: learn basic JavaScript concepts like data types, variables, and functions. Elevate your websites' interactivity by mastering the Document Object Model (DOM) and JavaScript event handling. Dive deeper with advanced JavaScript techniques and explore the power of jQuery for streamlined DOM manipulation. 3. Frontend Libraries and Frameworks: Dive into powerful frontend libraries and frameworks. Discover React's potential for building reusable UI components. Unlock AngularJS's capabilities for dynamic single-page applications. Integrate jQuery for simpler, more elegant JavaScript solutions. Embark on this transformative journey and redefine your skills as a front-end developer. Construct dynamic, interactive websites with HTML, CSS, JavaScript, AngularJS, and React. Applied Learning Project Our program is highly focused on practical, hands-on learning. We understand that developers learn best by doing, so our courses and modules are designed to help learners apply what they learn in real-world scenarios. Our instructors are experienced developers who have worked on numerous Frontend projects and are well-equipped to guide learners through the practical aspects of Frontend Development. Grasp fundamentals of HTML, mastering the structure and usage of tags, attributes, and elements to define web content and layout. Understand and apply CSS basics, learning to control layout, typography, and color schemes while comprehending the concept of cascading. Delve into Bootstrap's framework, leveraging its pre-built components to create professional, mobile-friendly web designs. Acquire foundational web design principles, emphasizing responsive design and ensuring web pages are visually appealing across devices. Gain deep knowledge of JavaScript fundamentals: variables, data types, operators, and functions for effective web application development. Acquire the ability to dynamically modify web pages using DOM manipulation and craft responsive user interfaces through event handling techniques. Achieve expertise in advanced JavaScript practices and harness the power of jQuery to enhance web page interactivity and simplify tasks. Culminate learning with a hands-on project, demonstrating real-world application of JavaScript and jQuery skills to create dynamic web experiences. Master the intricacies of React, learning components, state management, and JSX, to craft interactive user interfaces with ease. Delve deep into Angular's architecture, from components and directives to services, optimizing web applications for scalability and robustness. Construct simple web pages with responsive layouts, interactive features, and dynamic content to enrich user experience. Acquire hands-on experience in end-to-end front-end project development, equipping you with a promising career as a front-end developer.

3 course series

Beginner level

3 months (at 5 hours a week)

https://www.coursera.org/specializations/build-dynamic-website

Graph Analytics for Big Data

53,054

4.3

Amarnath Gupta

University of California San Diego

['Graph Theory', 'Neo4j', 'Analytics', 'Graph Database']

Want to understand your data network structure and how it changes under different conditions? Curious to know how to identify closely interacting clusters within a graph? Have you heard of the fast-growing area of graph analytics and want to learn more? This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects. Meet your instructor, Amarnath Gupta and learn about the course objectives. 1 video1 reading Welcome! This week we will get a first exposure to graphs and their use in everyday life. By the end of the module you will be able to create a graph applying core mathematical properties of graphs, and identify the kinds of analysis questions one might be able to ask of such a graph. We hope the you will be inspired as to how graphical representations might enable you to answer new Big Data problems! 8 videos2 readings1 assignment1 peer review2 discussion prompts 17 videos3 readings2 assignments2 discussion prompts Welcome to the 4th module in the Graph Analytics course. Last week, we got a glimpse of a number of graph properties and why they are important. This week we will use those properties for analyzing graphs using a free and powerful graph analytics tool called Neo4j. We will demonstrate how to use Cypher, the query language of Neo4j, to perform a wide range of analyses on a variety of graph networks. 7 videos9 readings2 assignments In the last two modules we have learned about graph analytics and graph data management. This week we will study how they come together. There are programming models and software frameworks created specifically for graph analytics. In this module we'll give an introductory tour of these models and frameworks. We will learn to implement what you learned in Week 2 and build on it using GraphX and Giraph. 11 videos6 readings1 assignment

5 modules

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

https://www.coursera.org/learn/big-data-graph-analytics

89%

Optimizing Diversity on Teams

8,804

4.4

Dr. Aviva Legatt

University of Pennsylvania

[]

By drawing on social science perspectives, this course enables you to learn what diversity is, and how to use it to maximize team performance, innovation and creativity. You also learn how to draw out the collective wisdom of diverse teams, handle conflict and establish common ground rules through real-world cases and peer-to-peer discussions. In addition, you discover how to overcome common biases faced in diverse teams. Systems of power, reward and rhetoric are discussed to help you create prosperous teams where differences flourish. This module is all about the hidden barriers that can prevent you from promoting and leveraging the benefits of diversity on your team. We will learn specific strategies to get buy-in for diversity initiatives. We will learn about the biases that can harm these efforts, and discuss effective means of identifying and reducing these biases. Towards the end of the module, you will hear from two diversity experts. The first is Arjun Shankar, Co-Director of the Center for Curiosity at the University of Pennsylvania. In this role, he has studied cultural barriers to inclusion in organizations and offers insights based on his research. The second expert is Stanford Thompson, Executive Director of the music education non-profit, Play On, Philly! Stanford advises symphony orchestras nationally on how to improve their diversity, and will offer practical advice on making any team more inclusive. By the end of the module, you will be better positioned to develop diversity initiatives that go beyond compliance and make inclusion a core strength of your team. 8 videos2 readings1 assignment1 peer review1 discussion prompt In the first module, you will learn the essentials of why diversity matters for teams, and why it can be difficult to build diverse teams. We will overview basic concepts of difference, bias, and conflict that will serve as a foundation for later modules. 14 videos4 readings1 assignment1 peer review1 discussion prompt In this module, we will move from promoting diversity to looking at the conflicts that can arise in diverse work environments. You will learn about why conflicts occur and how you can develop norms to address them. By the end of the module, you will be able to have better conversations related to diversity issues in the workplace. 8 videos2 readings1 assignment1 peer review1 discussion prompt In this module, you will get a practical perspective on managing diversity in teams by looking at real life cases of companies creating a more inclusive workplace. Looking at the experience of Google, Nike and UnitedHealthcare, you will see how major businesses are applying specific strategies and techniques for overcoming barriers to inclusion. 9 videos3 readings1 assignment1 peer review1 discussion prompt

4 modules

Beginner level

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

https://www.coursera.org/learn/diverse-teams