anchor.diff:    -Marginal cost-plus pricing
     -Peak-load pricing
     -Index-based pricing
  ---Evaluate the impact of channel intermediaries and customer lifetime value on pricing",
  +--Evaluate the impact of channel intermediaries and customer lifetime value on pricing"
   Customer Value in Pricing Strategy,uva-darden-pricing-strategy-customer-value,https://coursera.org/learn/uva-darden-pricing-strategy-customer-value,Business,"University of Virginia, BCG","The traditional approach to pricing based on costs works to pay the bills, but it leaves revenue on the table. You can, in fact, price your products in a way that increases sales--if you know what your customers are willing to pay and can leverage psychology to create better deal and discount plans. In this course, we'll show you how to price a product based on how your customers value it and the psychology behind their purchase decisions. Led by Darden faculty and Boston Consulting Group global pricing experts, this course provides an in-depth understanding of value-based pricing and how to use it to capture more revenue.
   
   By the end of this course, you'll be able to...
   -- Apply knowledge of customer value to price products
   -- Leverage core value-based pricing techniques to inform pricing decisions
   -- Measure customer willingness to pay using models (surveys, conjoint analysis, other data)
  --- Use knowledge of consumer psychology to set prices beneficial to both consumers and sellers",
  -Market and Competition in Pricing Strategy,uva-darden-pricing-strategy-market-competition,https://coursera.org/learn/uva-darden-pricing-strategy-market-competition,Business,"University of Virginia, BCG","If you haven’t considered what the competition is charging, you may not be maximizing your revenue. Spend time analyzing the market and you can influence price and improve margins. In this course, we'll show you how to implement competitive pricing and avoid common legal pitfalls of market-based pricing. You will also learn how to predict, influence and respond to competitors’ pricing moves. Led by Darden faculty and Boston Consulting Group global pricing experts, this course provides an in-depth understanding of market-based pricing and how to use it to capture more revenue.",
  +-- Use knowledge of consumer psychology to set prices beneficial to both consumers and sellers"
  +Market and Competition in Pricing Strategy,uva-darden-pricing-strategy-market-competition,https://coursera.org/learn/uva-darden-pricing-strategy-market-competition,Business,"University of Virginia, BCG","If you haven’t considered what the competition is charging, you may not be maximizing your revenue. Spend time analyzing the market and you can influence price and improve margins. In this course, we'll show you how to implement competitive pricing and avoid common legal pitfalls of market-based pricing. You will also learn how to predict, influence and respond to competitors’ pricing moves. Led by Darden faculty and Boston Consulting Group global pricing experts, this course provides an in-depth understanding of market-based pricing and how to use it to capture more revenue."
   Leadership for Managers,leadership,https://coursera.org/learn/leadership,Business,Vanderbilt University,"Personal branding is critical for today’s executive—it distinguishes you as a competent authority, of course, but it also helps you establish your own goals for continuous improvement and develop your strengths as a business leader. If you’re looking to establish yourself more effectively in a leadership role and align your actions and behaviors with how you want to be perceived, this course is for you.
   
   This course is composed of three modules about managing self, managing others, and leading efforts for change. You’ll complete a capstone project on organizational change that tests your skills in a variety of simulated situations, and you’ll receive detailed feedback about your efforts. You’ll leave with a thorough understanding of how your leadership can make an impact on your organization—and a set of sharpened skills to help you accomplish your goals.
  
positive.code: - why Lean is a key driver for sustainable competitive advantage
  - how different companies can leverage Lean to create value both in manufacturing and services
  - what it takes to drive a Lean transformation and build a culture of continuous improvement 
  - how new technologies impact traditional lean practices",
  Cost and Economics in Pricing Strategy,uva-darden-pricing-strategy-cost-economics,https://coursera.org/learn/uva-darden-pricing-strategy-cost-economics,Business,"University of Virginia, BCG","How much should you charge for your products and services? Traditionally, businesses have answered this question based on the cost to produce or provide their goods and services. This course shows you the economic factors behind pricing based on cost and the pros and cons of a cost-based pricing approach. Led by Darden faculty and Boston Consulting Group global pricing experts, the course provides the practical and research-based models and methods you need to set prices that maximize your profits. 
  
  By the end of this course, you’ll be able to:
  
negative.code: •	Create and communicate a vision for workplace change
  •	Build coalitions that work
  
  Most of all, you’ll learn to develop your own unique strengths—and make more meaningful, authentic connections with others."
  Intercultural Management,intercultural,https://coursera.org/learn/intercultural,Business,ESCP Europe,"This MOOC explores different aspects of intercultural management, including teams, leadership, Human Resource Management, marketing and negotiations. When you complete this MOOC, you will have a richer understanding of the concept of culture, and how culture influences the way that individuals behave. 
  
  You will also get a deeper knowledge about how culture shapes management practices in international organizations. We will introduce you to a number of experts in the field of intercultural management who will discuss the challenges and the benefits of dealing with employees on a global level. 
  
  Moreover, we will share with you insights from our own research to illustrate recent developments in the field of intercultural management. During the MOOC we will provide you with a variety of concepts and tools that empower you to successfully interact with people from other cultures to achieve your desired personal and business-related goals.
  "
  Python Data Structures,python-data,https://coursera.org/learn/python-data,Computer Sciences,University of Michigan,"This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Informatics”. This course is equivalent to the second half of the 11-week ""Programming for Everybody (Python)"" course. This course covers Python 2."
  User Experience: Research & Prototyping,user-research,https://coursera.org/learn/user-research,Computer Sciences,"University of California, San Diego","This course will teach you the core process of experience design and how to effectively evaluate your work with the people for whom you are designing. You'll learn fundamental methods of design research that will enable you to effectively understand people, the sequences of their actions, and the context in which they work. Through the assignments, you’ll learn practical techniques for making sense of what you see and transform your observations into meaningful actionable insights and unique opportunity areas for design. You’ll also explore how to generate ideas in response to the opportunities identified and learn methods for making your ideas tangible. By answering specific questions and refining your concepts, you’ll move closer to making your ideas real. We’ll use cases from a variety of industries including health, education, transportation, finance, and beyond to illustrate how these methods work across different domains."
  Code Yourself! An Introduction to Programming,intro-programming,https://coursera.org/learn/intro-programming,Computer Sciences,"The University of Edinburgh, Universidad ORT Uruguay","This course will teach you how to program in Scratch, an easy to use visual programming language. More importantly, it will introduce you to the fundamental principles of computing and it will help you think like a software engineer."
  Advanced Competitive Strategy,advanced-competitive-strategy,https://coursera.org/learn/advanced-competitive-strategy,Computer Sciences,Ludwig-Maximilians-Universität München (LMU),"Advanced Competitive Strategy will introduce new topics and modules with even more real world examples and opportunities for student interaction than in the previous course Competitive Strategy (https://www.coursera.org/learn/competitivestrategy). In Advanced Competitive Strategy, we will look at how companies can build up and maintain their customer base by increasing switching costs and facilitating strategic customer lock-ins. We will find out how firms can increase their profits by pursuing suitable price discrimination and product differentiation strategies."
  "Computational Investing, Part I",computational-investing,https://coursera.org/learn/computational-investing,Computer Sciences,Georgia Institute of Technology,"Why do the prices of some companies’ stocks seem to move up and down together while others move separately? What does portfolio “diversification” really mean and how important is it? What should the price of a stock be? How can we discover and exploit the relationships between equity prices automatically? We’ll examine these questions, and others, from a computational point of view. You will learn many of the principles and algorithms that hedge funds and investment professionals use to maximize return and reduce risk in equity portfolios."
  "Responsive Website Basics: Code with HTML, CSS, and JavaScript ",website-coding,https://coursera.org/learn/website-coding,Computer Sciences,"University of London, Goldsmiths, University of London","In this course you will learn three key website programming and design languages: HTML, CSS and JavaScript. You will create a web page using basic elements to control layout and style. Additionally, your web page will support interactivity."
  Introduction to Software Product Management,introduction-to-software-product-management,https://coursera.org/learn/introduction-to-software-product-management,Computer Sciences,University of Alberta,"This course highlights the importance and role of software product management. It also provides an overview of the specialization, as well as its goals, structure, and expectations. The course explains the value of process, requirements, planning, and monitoring in producing better software."
  Object Oriented Programming in Java,object-oriented-java,https://coursera.org/learn/object-oriented-java,Computer Sciences,"University of California, San Diego",This is an intermediate Java course. We recommend this course to learners who have previous experience in software development or a background in computer science. Our goal is that by the end of this course each and every one of you feels empowered to create a Java program that’s more advanced than any you have created in the past and that is personally interesting to you.
  Introduction to Game Design,game-design,https://coursera.org/learn/game-design,Computer Sciences,California Institute of the Arts,"This course is an introduction to the primary concepts of gaming, and an exploration of how these basic concepts affect the way gamers interact with our games. In this course you will understand what defines a “game” and the mechanics and rules behind different types of games. Through four linked assignments you'll learn ways to create and describe a game concept, and specifically what makes a compelling game."
  "Big Data, Cloud Computing, & CDN Emerging Technologies",big-data-cloud-computing-cdn,https://coursera.org/learn/big-data-cloud-computing-cdn,Computer Sciences,Yonsei University,"You have most likely heard about Clouds and Big Data before, and already know how significantly important they are and will be in the future. Cloud Computing enables us to easily use software as well as processing platforms and computing infrastructure (that are not equipped on our computers and smartphones) from any location through Internet services."
  "HTML, CSS and JavaScript",html-css-javascript,https://coursera.org/learn/html-css-javascript,Computer Sciences,The Hong Kong University of Science and Technology,"This course will teach you the essential elements of web page development, covering HTML, CSS and JavaScript. No previous experience of these technologies is necessary, although it is helpful if you have some prior programming experience. First, HTML together with CSS are discussed and explored."
  Input and Interaction,interaction-techniques,https://coursera.org/learn/interaction-techniques,Computer Sciences,"University of California, San Diego","In this course, you will learn relevant fundamentals of human motor performance, perception, and cognition that inform effective interaction design. You will use these models of how people work to design more effective input and interaction techniques. You’ll apply these to both traditional graphic and gestural interfaces."
  Introduction To Swift Programming,swift-programming,https://coursera.org/learn/swift-programming,Computer Sciences,University of Toronto,"Introduction to Swift Programming is the first course in a four part specialization series that will provide you with the tools and skills necessary to develop an iOS App from scratch. By the end of this first course you will be able to demonstrate intermediate application of programming in Swift, the powerful new programming language for iOS. Guided by best practices you will become proficient with syntax, object oriented principles, memory management, functional concepts and more in programming with Swift."
  Programming and the Web for Beginners,duke-programming-web,https://coursera.org/learn/duke-programming-web,Computer Sciences,Duke University,"Learn foundational programming concepts (e.g., functions, for loops, conditional statements) and how to solve problems like a programmer. In addition, learn basic web development as you build web pages using HTML, CSS, JavaScript. By the end of the course, will create a web page where others can upload their images and apply image filters that you create."
  Ruby on Rails: An Introduction,ruby-on-rails-intro,https://coursera.org/learn/ruby-on-rails-intro,Computer Sciences,Johns Hopkins University,"In this course, we will explore how to build web applications with the Ruby on Rails web application framework, which is geared towards rapid prototyping. Yes, that means building quickly! At the conclusion of this course, you will be able to build a meaningful web application and deploy it to the “cloud” using a Heroku PaaS (Platform as a Service). Best of all, it will almost feel effortless… Really!"
  Securing Digital Democracy,digital-democracy,https://coursera.org/learn/digital-democracy,Computer Sciences,University of Michigan,"In this course, you'll learn what every citizen should know about the security risks--and future potential — of electronic voting and Internet voting. We'll take a look at the past, present, and future of election technologies and explore the various spaces intersected by voting, including computer security, human factors, public policy, and more."
  Foundations of Objective-C App Development,objective-c,https://coursera.org/learn/objective-c,Computer Sciences,"University of California, Irvine",An introduction to the Objective-C programming language. This will prepare you for more extensive iOS app development and build a foundation for advanced iOS development topics. Objective-C programming requires a Mac laptop or desktop computer.
  Introduction to Game Development,game-development,https://coursera.org/learn/game-development,Computer Sciences,Michigan State University,"If you love games and want to learn how to make them, then this course will start you down that path. Making games is a creative and technical art form. In this course you will familiarize yourself with the tools and practices of game development. You will get started developing your own videogames using the industry standard game development tools, including the Unity3D game engine and C#. At the end of the course you will have completed three hands-on projects and will be able to leverage an array of game development techniques to create your own basic games."
  Interactive Computer Graphics,interactive-computer-graphics,https://coursera.org/learn/interactive-computer-graphics,Computer Sciences,The University of Tokyo,"This course will introduce various interactive tools developed in computer graphics research field with their design rationales and algorithms. Examples include enhancements to graphical user interfaces, authoring tools for 2D drawings and 3D animations, and interactive computer-aided design systems. Rich live demonstrations and course assignments will give you insights and skills to design and implement such tools for your own problems."
  Human-Centered Design: an Introduction,human-computer-interaction,https://coursera.org/learn/human-computer-interaction,Computer Sciences,"University of California, San Diego","In this course, you will learn how to design technologies that bring people joy, rather than frustration. You'll learn several techniques for rapidly prototyping and evaluating multiple interface alternatives -- and why rapid prototyping and comparative evaluation are essential to excellent interaction design. You'll learn how to conduct fieldwork with people to help you get design ideas. How to make paper prototypes and low-fidelity mock-ups that are interactive -- and how to use these designs to get feedback from other stakeholders like your teammates, clients, and users. Armed with these design-thinking strategies, you’ll be able to do more creative human-centered design in any domain."
  Design Principles: an Introduction,design-principles,https://coursera.org/learn/design-principles,Computer Sciences,"University of California, San Diego","What makes an interface intuitive? How can I tell whether one design works better than another? This course will teach you fundamental principles of design and how to effectively evaluate your work with users. You'll learn fundamental principles of visual design so that you can effectively organize and present information with your interfaces. You'll learn principles of perception and cognition that inform effective interaction design. And you'll learn how to perform and analyze controlled experiments online. In many cases, we'll use Web design as the anchoring domain. A lot of the examples will come from the Web, and we'll talk just a bit about Web technologies in particular. When we do"
  "Internet History, Technology, and Security",internet-history,https://coursera.org/learn/internet-history,Computer Sciences,University of Michigan,"The impact of technology and networks on our lives, culture, and society continues to increase. The very fact that you can take this course from anywhere in the world requires a technological infrastructure that was designed, engineered, and built over the past sixty years. To function in an information-centric world, we need to understand the workings of network technology. This course will open up the Internet and show you how it was created, who created it and how it works. Along the way we will meet many of the innovators who developed the Internet and Web technologies that we use today."
  Introduction to HTML5,html,https://coursera.org/learn/html,Computer Sciences,University of Michigan,"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."
  Internet Emerging Technologies,internet-technologies,https://coursera.org/learn/internet-technologies,Computer Sciences,Yonsei University,"Every information service is connected through the Internet. If your work is any bit related to information, there is no excuse, you have to know what the Internet is and how it works! The relation of information and the Internet is equivalent to the blood and blood vessels of our body, which we have been using and will be using every day of our lives."
  Programming for Everybody (Getting Started with Python),python,https://coursera.org/learn/python,Computer Sciences,University of Michigan,This course aims to teach everyone the basics of programming computers using Python. We cover the basics of how one constructs a program from a series of simple instructions in Python. The course has no pre-requisites and avoids all but the simplest mathematics. Anyone with moderate computer experience should be able to master the materials in this course.
  CODAPPS: Coding mobile apps for entrepreneurs,codapps,https://coursera.org/learn/codapps,Computer Sciences,emlyon business school,"This course will teach you how to create mobile apps for Android, iOS and Windows Phone. No prerequisite in coding knowledge is required. In progressive steps, we will first learn how to create a simple and useful app: your own curriculum vitae. We will discover how to test the app on phones, and how to distribute it on the Play Store, Apple's App Store and the Windows Store."
  Database Management Essentials,database-management,https://coursera.org/learn/database-management,Computer Sciences,University of Colorado System,"Database Management Essentials provides the foundation you need for a career in database development, data warehousing, or business intelligence, as well as for the entire Data Warehousing for Business Intelligence specialization. In this course, you will create relational databases, write SQL statements to extract information to satisfy business reporting requests, create entity relationship diagrams (ERDs) to design databases, and analyze table designs for excessive redundancy."
  Introduction to the Internet of Things and Embedded Systems,iot,https://coursera.org/learn/iot,Computer Sciences,"University of California, Irvine","The explosive growth of the “Internet of Things” is changing our world and the rapid drop in price for typical IoT components is allowing people to innovate new designs and products at home. In this first class in the specialization you will learn the importance of IoT in society, the current components of typical IoT devices and trends for the future. IoT design considerations, constraints and interfacing between the physical world and your device will also be covered. You will also learn how to make design trade-offs between hardware and software."
  Cybersecurity and Its Ten Domains,cyber-security-domain,https://coursera.org/learn/cyber-security-domain,Computer Sciences,University System of Georgia,"This course is designed to introduce students, working professionals and the community to the exciting field of cybersecurity. Throughout the MOOC, participants will engage in community discourse and online interaction. Participants will gain knowledge and understanding of cybersecurity and its domains."
  Wireless Communication Emerging Technologies,wireless-communication-technologies,https://coursera.org/learn/wireless-communication-technologies,Computer Sciences,Yonsei University,"This course covers the services and specifications of the most popular wireless communication technologies used around the world. The most popular wireless communication technologies are mobile communication, WLAN (Wireless Local Area Network), and WPAN (Wireless Personal Area Network), which are all included in smartphones. Among WLAN types Wi-Fi is most popular, and among WPAN types Bluetooth is most popular. Therefore, the lectures in this course cover Wi-Fi and Bluetooth specifications."
  Principles of Game Design,gamedesign,https://coursera.org/learn/gamedesign,Computer Sciences,Michigan State University,"In this course you will practice moving from game concept through design documentation, prototyping and testing. Numerous elements go into the overall process of game design. These range from topics such as idea generation, story, character, and game world development, game mechanics and level design, and user experience design. You will explore the process for designing meaningful experiences for your players."
  Front-End Web UI Frameworks and Tools,web-frameworks,https://coursera.org/learn/web-frameworks,Computer Sciences,The Hong Kong University of Science and Technology,"This course will give you an overview of client-side web frameworks, in particular Bootstrap. You will learn about grids and responsive design, Bootstrap CSS and JavaScript components. You will learn about CSS preprocessors, Less and Sass. You will also learn the basics of Node.js and NPM and learn about Web tools like Bower."
  Java Programming: Solving Problems with Software,java-programming,https://coursera.org/learn/java-programming,Computer Sciences,Duke University,"Learn to code in Java and improve your programming and problem-solving skills. You will learn to design algorithms as well as develop and debug programs. Using custom open-source classes, you will write programs that access and transform images, websites, and other types of data. At the end of the course you will build a program that determines the popularity of different baby names in the US over time by analyzing comma separated value (CSV) files."
  Introduction to CSS3,introcss,https://coursera.org/learn/introcss,Computer Sciences,University of Michigan,"The web today is almost unrecognizable from the early days of white pages with lists of blue links. Now, sites are designed with complex layouts, unique fonts, and customized color schemes. This course will show you the basics of Cascading Style Sheets (CSS3). The emphasis will be on learning how to write CSS rules, how to test code, and how to establish good programming habits."
  Responsive Web Design,responsive-web-design,https://coursera.org/learn/responsive-web-design,Computer Sciences,"University of London, Goldsmiths, University of London","In this course you will learn how to apply concepts from interaction design and human computer interaction in order to design and build an interactive, professional looking website. You will learn how to make your web page designs adapt to different screen sizes using responsive grid layouts. You will learn how to add navigation and other design elements, and you will learn how to separate data and display using JavaScript objects and templates."
  The Arduino Platform and C Programming,arduino-platform,https://coursera.org/learn/arduino-platform,Computer Sciences,"University of California, Irvine",The Arduino is an open-source computer hardware/software platform for building digital devices and interactive objects that can sense and control the physical world around them. In this class you will learn how the Arduino platform works in terms of the physical board and libraries and the IDE (integrated development environment).
  Story and Narrative Development for Video Games,video-game-story,https://coursera.org/learn/video-game-story,Computer Sciences,California Institute of the Arts,"In this course, you will examine how storytelling acts as a vital mechanism for driving video gameplay forward. Looking at several historical and contemporary games, you will be asked to evaluate and interpret different story styles with the goal of identifying themes and procedures for your own game ideas. We'll examine traditional narrative story processes, such as three-act structure, and how they fit into game story flows and the strategic elements of gameplay."
  Rails with Active Record and Action Pack,rails-with-active-record,https://coursera.org/learn/rails-with-active-record,Computer Sciences,Johns Hopkins University,"You already know how to build a basic web application with the Ruby on Rails framework. Perhaps, you have even taken Course 1, ""Ruby on Rails: An Introduction"" (we highly recommend it) where you relied on external web services to be your “data layer”. But in the back of your mind, you always knew that there would come a time when you would need to roll up your sleeves and learn SQL to be able to interact with your own relational database (RDBMS)."
  Software Processes and Agile Practices,software-processes-and-agile-practices,https://coursera.org/learn/software-processes-and-agile-practices,Computer Sciences,University of Alberta,"This course delves into a variety of processes to structure software development. It also covers the foundations of core Agile practices, such as Extreme Programming and Scrum."
  Data structures: Measuring and Optimizing Performance,data-structures-optimizing-performance,https://coursera.org/learn/data-structures-optimizing-performance,Computer Sciences,"University of California, San Diego","How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? This is an intermediate Java course. We recommend this course to learners who have previous experience in software development or a background in computer science, and in particular, we recommend that you have taken the first course in this specialization (which also requires some previous experience with Java)."
  Using Python to Access Web Data,python-network-data,https://coursera.org/learn/python-network-data,Computer Sciences,University of Michigan,"This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python. This course will cover Chapters 11-13 of the textbook “Python for Informatics”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization."
  Networking and Security in iOS Applications,security,https://coursera.org/learn/security,Computer Sciences,"University of California, Irvine",You will learn to extend your knowledge of making iOS apps so that they can securely interact with web services and receive push notifications. You'll learn how to store data securely on a device using Core Data. You’ll also learn to securely deploy apps to the App Store and beta users over-the-air. The format of the course is through a series of code tutorials. We will walk you through the creation of several apps that you can keep as a personal app toolbox.
  Quantitative Formal Modeling and Worst-Case Performance Analysis,quantitative-formal-modeling-1,https://coursera.org/learn/quantitative-formal-modeling-1,Computer Sciences,EIT Digital,"Welcome to Quantitative Formal Modeling and Worst-Case Performance Analysis. In this course, you will learn about modeling and solving performance problems in a fashion popular in theoretical computer science, and generally train your abstract thinking skills."
  iOS App Development Basics,iosappdevelopmentbasics,https://coursera.org/learn/iosappdevelopmentbasics,Computer Sciences,University of Toronto,"iOS App Development Basics, the second course in the iOS App Development with Swift specialization, expands your programming skills and applies them to authentic app development projects. The topics covered in this course include Xcode basics, Core iOS and Cocoa Touch frameworks, simple user interface creation, MVC Architecture and much more. With a focus on using Apple’s components to access sensors like camera, microphone and GPS, by the end of this course you will be able to create a basic App according to specified parameters and guidelines."
  Gamification,gamification,https://coursera.org/learn/gamification,Computer Sciences,University of Pennsylvania,"Gamification is the application of game elements and digital game design techniques to non-game problems, such as business and social impact challenges. This course will teach you the mechanisms of gamification, why it has such tremendous potential, and how to use it effectively. For additional information on the concepts described in the course, you can purchase Professor Werbach's book For the Win: How Game Thinking Can Revolutionize Your Business in print or ebook format in several languages."
  "Data Warehouse Concepts, Design, and Data Integration",dwdesign,https://coursera.org/learn/dwdesign,Computer Sciences,University of Colorado System,"This is the second course in the Data Warehousing for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will learn exciting concepts and skills for designing data warehouses and creating data integration workflows. These are fundamental skills for data warehouse developers and administrators. You will have hands-on experience for data warehouse design and use open source products for manipulating pivot tables and creating data integration workflows."
  Internet of Things: Communication Technologies,internet-of-things-communication,https://coursera.org/learn/internet-of-things-communication,Computer Sciences,"University of California, San Diego","Have you wondered how “Things” talk to each other and the cloud? Do you understand the alternatives for conveying latency-sensitive real time data versus reliable signaling data? Building on the skills from the Sensing and Actuation course, we will explore protocols to exchange information between processors."
  App Design and Development for iOS,iosappdesigndevelopment,https://coursera.org/learn/iosappdesigndevelopment,Computer Sciences,University of Toronto,"In App Design and Development for iOS, the third course of the iOS App Development with Swift specialization, you will be developing foundational programming skills to support graphical element presentation and data manipulation from basic functions through to advanced processing. You will continue to build your skill set to use and apply core graphics, touch handling and gestures, animations and transitions, alerts and actions as well as advanced algorithms, threading and more. By the end of this course you will be able to develop a more advanced, fully functioning app."
  Build a Modern Computer from First Principles: From NAND to Tetris (Project-Centered Course),build-a-computer,https://coursera.org/learn/build-a-computer,Computer Sciences,Hebrew University of Jerusalem,"In this project-centered course* you will build a modern computer system, from the ground up. We’ll divide this fascinating journey into six hands-on projects that will take you from constructing elementary logic gates all the way through creating a fully functioning general purpose computer. In the process, you will learn - in the most direct and constructive way - how computers work, and how they are designed."
  How To Create a Website in a Weekend! (Project-Centered Course),how-to-create-a-website,https://coursera.org/learn/how-to-create-a-website,Computer Sciences,The State University of New York,"In this project-centered course*, you’ll design, build, and publish a basic website that incorporates text, sound, images, hyperlinks, plug-ins, and social media interactivity. We’ll provide you with step-by-step instructions, exercises, tips, and tools that enable you to set up a domain name, create an attractive layout for your pages, organize your content properly, ensure that your site functions well across different operating systems and on mobile devices, keep your site safe, and finally, let people know your site is online. We’ll even show you how to track your visitors. Throughout the course, you'll engage in collaboration and discussion with other learners through course forums and peer review."
  Advanced Styling with Responsive Design,responsivedesign,https://coursera.org/learn/responsivedesign,Computer Sciences,University of Michigan,"It used to be the case that everyone viewed webpages on about the same size screen. But with the explosion of the use of smartphones to access the Internet, the landscape of design has completely changed. People viewing your site will now expect that it will perform regardless of the platform (smartphone, tablet, laptop, or desktop computer). This ability to respond to any platform is called responsive design."
  Information Design,infodesign,https://coursera.org/learn/infodesign,Computer Sciences,"University of California, San Diego","A blank canvas is full of possibility. If you have an idea for a user experience, how do you turn it into a beautiful and effective user interface? This covers covers principles of visual design so that you can effectively organize and present information with your interfaces. You'll learn concrete strategies to create user interfaces, including key lessons in typography, information architecture, layout, color, and more. You’ll learn particular issues that arise in new device contexts, such as mobile and responsive interfaces."
  Character Design for Video Games,video-game-character,https://coursera.org/learn/video-game-character,Computer Sciences,California Institute of the Arts,"In this course you will explore concepts and approaches involved in creating successful character designs that can be applied to video games. Following a first week delving into some foundational concepts for successful character design, each of the remaining three weeks are structured as a ""master class"" where you will observe three professional character designers at work in the studio: Andy Ristaino (Adventure Time), Jacky Ke Jiang (Journey), and Robertryan Cory (SpongeBob SquarePants). Each designer will take on two different design challenges on the fly and address the various issues in designing characters for games, such as movement, expression, and technical limitations."
  Multiplatform Mobile App Development with Web Technologies,hybrid-mobile-development,https://coursera.org/learn/hybrid-mobile-development,Computer Sciences,The Hong Kong University of Science and Technology,"This course focuses on developing multiplatform mobile applications using the Web skills (HTML5, CSS and Javascript) that you have already acquired so far in the previous courses of this specialization. In particular we make use of the Cordova hybrid application framework to develop and target multiple mobile platforms with a single codebase. We make use of the Ionic framework, one of fastest growing mobile application frameworks, that is built with mobile-optimized HTML5 and CSS based components and AngularJS. You will learn about UI development with Ionic and then using Cordova's modules to access the native mobile platform's capabilities from Javascript."
  "Networks: Friends, Money, and Bytes",friends-money-bytes,https://coursera.org/learn/friends-money-bytes,Computer Sciences,Princeton University,"You pick up your iPhone while waiting in line at a coffee shop. You google a not-so-famous actor, get linked to a Wikipedia entry listing his recent movies and popular YouTube clips of several of them. You check out user reviews on Amazon and pick one, download that movie on BitTorrent or stream that in Netflix. But suddenly the WiFi logo on your phone is gone and you're on 3G. Video quality starts to degrade, but you don't know if it's the server getting crowded or the Internet is congested somewhere. In any case, it costs you $10 per Gigabyte, and you decide to stop watching the movie, and instead multitask between sending tweets and calling your friend on Skype, while songs stream from iCloud to your phone."
  "C++ For C Programmers, Part A",c-plus-plus-a,https://coursera.org/learn/c-plus-plus-a,Computer Sciences,"University of California, Santa Cruz",This course is for experienced C programmers who want to program in C++. The examples and exercises require a basic understanding of algorithms and object-oriented software.
  Server-side Development with NodeJS,server-side-development,https://coursera.org/learn/server-side-development,Computer Sciences,The Hong Kong University of Science and Technology,"This course deals with all things server-side. We base the entire course around the NodeJS platform. We start with a brief overview of the Web protocols: HTTP and HTTPS. We examine NodeJS and NodeJS modules: Express for building web servers. On the database side, we review basic CRUD operations, NoSQL databases, in particular MongoDB and Mongoose for accessing MongoDB from NodeJS. We examine the REST concepts and building a RESTful API. We touch upon authentication and security. Finally we review backend as a service (BaaS) approaches, including mobile BaaS, both open-source and commercial BaaS services."
  Agile Planning for Software Products,agile-planning-for-software-products,https://coursera.org/learn/agile-planning-for-software-products,Computer Sciences,University of Alberta,"This course covers the techniques required to break down and map requirements into plans that will ultimately drive software production. Upon successful completion of this course, you will be able to: - Create effective plans for software development - Map user requirements to developer tasks - Assess and plan for project risks"
  International Cyber Conflicts,cyber-conflicts,https://coursera.org/learn/cyber-conflicts,Computer Sciences,The State University of New York,"By nature, cyber conflicts are an international issue that span across nation-state borders. By the end of the course, you will be able to apply the knowledge gained for analysis and management of international cyber incidents and conflicts including for activities such as development of policy related to cybercrime and cyberwarfare. Management of cyber incidents and conflicts requires an interdisciplinary perspective including an understanding of: 1) characteristics of the cyber threats and conflicts themselves, 2) international efforts to reduce and improve cyber security, and 3) psychological and sociopolitical factors."
  Algorithmic Toolbox,algorithmic-toolbox,https://coursera.org/learn/algorithmic-toolbox,Computer Sciences,"University of California, San Diego, Higher School of Economics","The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. We will learn a lot of theory: how to sort data and how it helps for searching; how to break a large problem into pieces and solve them recursively; when it makes sense to proceed greedily; how dynamic programming is used in genomic studies."
  Best Practices for iOS User Interface Design,ui,https://coursera.org/learn/ui,Computer Sciences,"University of California, Irvine","You will learn to develop sophisticated user interfaces for iOS, with a focus on user interface design best practices, UI animations, and responsive design. You will learn about the key UI widgets, mapping interfaces and view restoration."
  Usable Security,usable-security,https://coursera.org/learn/usable-security,Computer Sciences,"University of Maryland, College Park","This course focuses on how to design and build secure systems with a human-centric focus. We will look at basic principles of human-computer interaction, and apply these insights to the design of secure systems with the goal of developing security measures that respect human performance and their goals within a system."
  Mastering the Software Engineering Interview,cs-tech-interview,https://coursera.org/learn/cs-tech-interview,Computer Sciences,"University of California, San Diego","You’ve hit a major milestone as a computer scientist and are becoming a capable programmer. You now know how to solve problems, write algorithms, and analyze solutions; and you have a wealth of tools (like data structures) at your disposal. You may now be ready for an internship or (possibly) an entry-level software engineering job. But can you land the internship/job? It depends in part on how well you can solve new technical problems and communicate during interviews. How can you get better at this? Practice!"
  Control of Mobile Robots,mobile-robot,https://coursera.org/learn/mobile-robot,Computer Sciences,Georgia Institute of Technology,"Control of Mobile Robots is a course that focuses on the application of modern control theory to the problem of making robots move around in safe and effective ways. The structure of this class is somewhat unusual since it involves many moving parts - to do robotics right, one has to go from basic theory all the way to an actual robot moving around in the real world, which is the challenge we have set out to address through the different pieces in the course"
  Approximation Algorithms Part I,approximation-algorithms-part-1,https://coursera.org/learn/approximation-algorithms-part-1,Computer Sciences,École normale supérieure,"How efficiently can you pack objects into a minimum number of boxes? How well can you cluster nodes so as to cheaply separate a network into components around a few centers? These are examples of NP-hard combinatorial optimization problems. It is most likely impossible to solve such problems efficiently, so our aim is to give an approximate solution that can be computed in polynomial time and that at the same time has provable guarantees on its cost relative to the optimum."
  "HTML, CSS, and Javascript for Web Developers",html-css-javascript-for-web-developers,https://coursera.org/learn/html-css-javascript-for-web-developers,Computer Sciences,Johns Hopkins University,"Do you realize that the only functionality of a web application that the user directly interacts with is through the web page? Implement it poorly and, to the user, the server-side becomes irrelevant! Today’s user expects a lot out of the web page: it has to load fast, expose the desired service, and be comfortable to view on all devices: from a desktop computers to tablets and mobile phones."
  Using Databases with Python,python-databases,https://coursera.org/learn/python-databases,Computer Sciences,University of Michigan,"This course will introduce students to the basics of the Structured Query Language (SQL) as well as basic database design for storing data as part of a multi-step data gathering, analysis, and processing effort. The course will use SQLite3 as its database. We will also build web crawlers and multi-step data gathering and visualization processes. We will use the D3.js library to do basic data visualization. This course will cover Chapters 14-15 of the book “Python for Informatics”."
  Web Application Development with Javascript and MongoDB,web-application-development,https://coursera.org/learn/web-application-development,Computer Sciences,"University of London, Goldsmiths, University of London","In this course, you will develop more advanced web application programming skills. You will learn how to control data read and write access using methods, publish and subscribe. You will learn how to access your database and server shells using command line tools. You will use the SimpleSchema system to validate data and generate input forms automatically. You will see a complete collaborative code editing environment, TextCircle, being built from scratch."
  Front-End JavaScript Frameworks: AngularJS,angularjs,https://coursera.org/learn/angularjs,Computer Sciences,The Hong Kong University of Science and Technology,"This course concentrates mainly on Javascript based front-end frameworks, and in particular, AngularJS, the most popular among them. We will review the model view controller (MVC) design-pattern in the context of AngularJS. You will be introduced to various aspects of AngularJS including two-way data binding and angular directives and filters. You will then be introduced to angular controllers and scopes. UI routing and templates will then be reviewed."
  Interactivity with JavaScript,javascript,https://coursera.org/learn/javascript,Computer Sciences,University of Michigan,"If you want to take your website to the next level, the ability to incorporate interactivity is a must. But adding some of these types of capabilities requires a stronger programming language than HTML5 or CSS3, and JavaScript can provide just what you need. With just a basic understanding of the language, you can create a page that will react to common events such as page loads, mouse clicks &"
  Client Needs and Software Requirements ,client-needs-and-software-requirements,https://coursera.org/learn/client-needs-and-software-requirements,Computer Sciences,University of Alberta,"This course covers practical techniques to elicit and express software requirements from client interactions. Upon successful completion of this course, you will be able to: - Create clear requirements to drive effective software development - Visualize client needs using low-fidelity prototypes - Maximize the effectiveness of client interactions - Adapt to changing product requirements"
  Getting Started: Agile Meets Design Thinking,getting-started-agile,https://coursera.org/learn/getting-started-agile,Computer Sciences,University of Virginia,"Despite everyone's good intentions, hard work and solid ideas, too many projects end up creating unneeded, unusable, and unsellable products. But it doesn't have to be this way. Agile and design thinking offer a different--and effective--approach to product development, one that results in valuable solutions to meaningful problems. In this course, you’ll learn how to determine what's valuable to a user early in the process--to frontload value--by focusing your team on testable narratives about the user and creating a strong shared perspective."
  Cryptography I,crypto,https://coursera.org/learn/crypto,Computer Sciences,Stanford University,Cryptography is an indispensable tool for protecting information in computer systems. In this course you will learn the inner workings of cryptographic systems and how to correctly use them in real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic. We will examine many deployed protocols and analyze mistakes in existing systems. The second half of the course discusses public-key techniques that let two parties generate a shared secret key.
  Game Development for Modern Platforms,gamedev-platforms,https://coursera.org/learn/gamedev-platforms,Computer Sciences,Michigan State University,"The device or ""platform"" that a game is developed for and played on has a massive impact on the game development process. In this hands-on course you will explore how to develop a game for a variety of modern platforms, including Web, Windows, Mac OS X, iOS, and Android. While building a complete game, you will learn intermediate and advanced game development techniques in the Unity game engine. By the end of the course, you will understand how to develop, refine, package, and prepare your game for distribution on a variety of game platforms."
  Reviews & Metrics for Software Improvements,reviews-and-metrics-for-software-improvements,https://coursera.org/learn/reviews-and-metrics-for-software-improvements,Computer Sciences,University of Alberta,"This course covers techniques for monitoring your projects in order to align client needs, project plans, and software production. It focuses on metrics and reviews to track and improve project progress and software quality. Upon successful completion of this course, you will be able to:"
  An Introduction to Interactive Programming in Python (Part 1),interactive-python-1,https://coursera.org/learn/interactive-python-1,Computer Sciences,Rice University,"This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple."
  Ruby on Rails Web Services and Integration with MongoDB,ruby-on-rails-web-services-mongodb,https://coursera.org/learn/ruby-on-rails-web-services-mongodb,Computer Sciences,Johns Hopkins University,"In this course, we will explore MongoDB, a very popular NoSQL database and Web Services concepts and integrate them both with Ruby on Rails. MongoDB is a used to handle documents with a pre-defined schema which will give the developers an ability to store, process and use data using it’s rich API. The modules will go in-depth from installation to CRUD operations, aggregation, indexing, GridFS and various other topics where we continuously integrate MongoDB with RailsRuby."
  Java Programming: Principles of Software Design,java-programming-design-principles,https://coursera.org/learn/java-programming-design-principles,Computer Sciences,Duke University,"Solve real world problems with Java using multiple classes. Learn how to create programming solutions that scale using Java interfaces. Recognize that software engineering is more than writing code - it also involves logical thinking and design. By the end of this course you will have written a program that analyzes and sorts earthquake data, and developed a predictive text generator."
  Approximation Algorithms Part II,approximation-algorithms-part-2,https://coursera.org/learn/approximation-algorithms-part-2,Computer Sciences,École normale supérieure,"This is the continuation of Approximation algorithms, Part 1. Here you will learn linear programming duality applied to the design of some approximation algorithms, and semidefinite programming applied to Maxcut. By taking the two parts of this course, you will be exposed to a range of problems at the foundations of theoretical computer science, and to powerful design and analysis techniques."
  Introduction to Meteor.js Development  ,meteor-development,https://coursera.org/learn/meteor-development,Computer Sciences,"University of London, Goldsmiths, University of London","In this course, you will learn how to create a complete, multi-user web site using the Meteor.js framework and MongoDB. You will implement user authentication, security features, reactive templates and routing using iron router. You will carry out key database operations such as inserting, removing and updating data as well as sorting and filtering. You will see how a complete application can be built, line by line."
  Cryptography,cryptography,https://coursera.org/learn/cryptography,Computer Sciences,"University of Maryland, College Park","This course will introduce you to the foundations of modern cryptography, with an eye toward practical applications."
  The Raspberry Pi Platform and Python Programming for the Raspberry Pi,raspberry-pi-platform,https://coursera.org/learn/raspberry-pi-platform,Computer Sciences,"University of California, Irvine","The Raspberry Pi is a small, affordable single-board computer that you will use to design and develop fun and practical IoT devices while learning programming and computer hardware. In addition, you will learn how to set up up the Raspberry Pi environment, get a Linux operating system running, and write and execute some basic Python code on the Raspberry Pi."
  Build Your First Android App (Project-Centered Course),android-app,https://coursera.org/learn/android-app,Computer Sciences,CentraleSupélec,"In this project-centered course*, you’ll design, build, and distribute your own unique application for the Android mobile platform. We’ll provide you with a set of customizable building blocks that you can assemble to create many different types of apps, and that will help you become familiar with many important specificities of Android development. When you complete the project, in addition to having a personalized app that you can use and share, you’ll have the skills and background you need to move on to more advanced coursework in Android development."
  Advanced Data Structures in Java,advanced-data-structures,https://coursera.org/learn/advanced-data-structures,Computer Sciences,"University of California, San Diego","How does Google Maps plan the best route for getting around town given current traffic conditions? How does an internet router forward packets of network traffic to minimize delay? How does an aid group allocate resources to its affiliated local partners? To solve such problems, we first represent the key pieces of data in a complex data structure. In this course, you’ll learn about data structures, like graphs, that are fundamental for working with structured real world data."
  "Designing, Running, and Analyzing Experiments",designexperiments,https://coursera.org/learn/designexperiments,Computer Sciences,"University of California, San Diego","You may never be sure whether you have an effective user experience until you have tested it with users. In this course, you’ll learn how to design user-centered experiments, how to run such experiments, and how to analyze data from these experiments in order to evaluate and validate user experiences. You will work through real-world examples of experiments from the fields of UX, IxD, and HCI, understanding issues in experiment design and analysis."
  Responsive website tutorial and examples,responsive-website-examples,https://coursera.org/learn/responsive-website-examples,Computer Sciences,"University of London, Goldsmiths, University of London","In this course, we will show you exciting examples of collaborative, interactive web applications that use various types of media including sound, images and big data. We will show you how to build sites that provide precisely this functionality, using Meteor. We will also provide fully working example application code that you can use for your own commercial web projects. The course also provides a range of advice and suggestions about how to develop bespoke web applications which match the requirements of clients, where clients are people who commission the product or people who use the product."
  "Java Programming: Arrays, Lists and Structured Data",java-programming-arrays-lists-data,https://coursera.org/learn/java-programming-arrays-lists-data,Computer Sciences,Duke University,Build on the software engineering skills you learned in “Java Programming: Solving Problems with Software” by learning new data structures. Use these data structures to build more complex programs that use Java’s object-oriented features. At the end of the course you will write an encryption program and a program to break your encryption algorithm.
  Toward the Future of iOS Development with Swift,iosswift,https://coursera.org/learn/iosswift,Computer Sciences,"University of California, Irvine",An introduction to the Swift programming language. This will prepare you for more extensive iOS app development and build a foundation for advanced iOS development topics.
  Beginning Game Programming with C#,game-programming,https://coursera.org/learn/game-programming,Computer Sciences,University of Colorado System,"The Beginning Game Programming with C# course is all about learning how to develop video games using the C# programming language. Why use C# instead of C++, Java, ActionScript, or some other programming language you may have heard of? First, using C# lets us use the open-source MonoGame framework, which help us quickly develop games for Windows, Android, iOS, Mac OS X, and others. Second, the Unity game engine is very popular with indie game developers, and C# is one of the programming languages you can use in the Unity environment."
  Running Valuable Design Sprints,running-design-sprints,https://coursera.org/learn/running-design-sprints,Computer Sciences,University of Virginia,"Typically, clients and managers don't want to pay for design (or strategy) but want to rush toward results. Design sprints allow you to meet clients' desire for solutions--to develop sooner--and still adjust based on feedback. But not all sprints are alike. In this course, you’ll learn how to run situation-appropriate sprints, whether it's testing user motivation, interface usability, or solution fit, to avoid waste and deliver value."
  Programming Mobile Applications for Android Handheld Systems: Part 2,android-programming-2,https://coursera.org/learn/android-programming-2,Computer Sciences,"University of Maryland, College Park","This course introduces you to the design and implementation of Android applications for mobile devices. You will build upon concepts from the prior course, including handling notifications, using multimedia and graphics and incorporating touch and gestures into your apps."
  Programming Mobile Applications for Android Handheld Systems: Part 1,android-programming,https://coursera.org/learn/android-programming,Computer Sciences,"University of Maryland, College Park","This course introduces you to the design and implementation of Android applications for mobile devices. You will develop an app from scratch, assuming a basic knowledge of Java, and learn how to set up Android Studio, work with various Activities and create simple user interfaces to make your apps run smoothly."
  "Games, Sensors and Media",games,https://coursera.org/learn/games,Computer Sciences,"University of California, Irvine","You will learn to make fluid digital interactive experiences that are suitable for gaming and use the advanced sensor hardware built into the iPhone and iPad. This includes drawing 2D graphics, playing sounds and music, integrating with Game Center, the iOS physics engine and detecting device orientation and location."
  Algorithmic Thinking (Part 1),algorithmic-thinking-1,https://coursera.org/learn/algorithmic-thinking-1,Computer Sciences,Rice University,"Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part course builds on the principles that you learned in our Principles of Computing course and is designed to train students in the mathematical concepts and process of ""Algorithmic Thinking"", allowing them to build simpler, more efficient solutions to real-world computational problems."
  An Introduction to Interactive Programming in Python (Part 2),interactive-python-2,https://coursera.org/learn/interactive-python-2,Computer Sciences,Rice University,"This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple."
  Data Structures,data-structures,https://coursera.org/learn/data-structures,Computer Sciences,"University of California, San Diego, Higher School of Economics","A good algorithm usually comes together with a set of good data structures that allow the algorithm to manipulate the data efficiently. In this course, we consider the common data structures that are used in various computational problems. You will learn how these data structures are implemented in different programming languages and will practice implementing them in our programming assignments. This will help you to understand what is going on inside a particular built-in implementation of a data structure and what to expect from it."
  Principles of Computing (Part 1),principles-of-computing-1,https://coursera.org/learn/principles-of-computing-1,Computer Sciences,Rice University,This two-part course builds upon the programming skills that you learned in our Introduction to Interactive Programming in Python course. We will augment those skills with both important programming practices and critical mathematical problem solving skills. These skills underlie larger scale computational problem solving and programming. The main focus of the class will be programming weekly mini-projects in Python that build upon the mathematical and programming principles that are taught in the class.
  Java for Android,java4android,https://coursera.org/learn/java4android,Computer Sciences,Vanderbilt University,"This MOOC teaches you how to program core features and classes from the Java programming language that are used in Android, which is the dominant platform for developing and deploying mobile device apps. In particular, this MOOC covers key Java programming language features that control the flow of execution through an app (such as Java’s various looping constructs and conditional statements), enable access to structured data (such as Java's built-in arrays and common classes in the Java Collections Framework, such as ArrayList and HashMap), group related operations and data into classes and interfaces (such as Java's primitive and user-defined types, fields, methods, generic parameters, and exceptions), customize the behavior of existing classes via inheritance and polymorphism (such as subclassing and overriding virtual methods)."
  Networks Illustrated: Principles without Calculus,networks-illustrated,https://coursera.org/learn/networks-illustrated,Computer Sciences,Princeton University,What makes WiFi faster at home than at a coffee shop? How does Google order its search results from the trillions of webpages on the Internet? Why does Verizon charge $15 for every GB of data we use? Is it really true that we are connected in six social steps or less? These are just a few of the many intriguing questions we can ask about the social and technical networks that form integral parts of our daily lives.
  Development of Real-Time Systems,real-time-systems,https://coursera.org/learn/real-time-systems,Computer Sciences,EIT Digital,"The course centers around the problem of achieving timing correctness in embedded systems, which means to guarantee that the system reacts within the real-time requirements. Examples of such systems include airbags, emergency breaks, avionics, and also multi-media systems like video playback and QoS in web servers."
  Introduction to Programming with MATLAB,matlab,https://coursera.org/learn/matlab,Computer Sciences,Vanderbilt University,"This course teaches computer programming to those with little to no previous experience. It uses the programming system and language called MATLAB to do so because it is easy to learn, versatile and very useful for engineers and other professionals. MATLAB is a special-purpose language that is an excellent choice for writing moderate-size programs that solve problems involving the manipulation of numbers. The design of the language makes it possible to write a powerful program in a few lines."
  Web Application Development: Basic Concepts,webapps1,https://coursera.org/learn/webapps1,Computer Sciences,University of New Mexico,"This is the first course in a Coursera Specialization track involving Web Application Architectures. This course will give you the basic background, terminology and fundamental concepts that you need to understand in order to build modern full stack web applications. A full stack web developer is familiar with each ""layer"" of the software technologies involved in a web application, including data modeling and database technologies, the web server environment and middleware components, network protocols, the user interface and basic visual design and user interaction concepts."
  Algorithmic Thinking (Part 2),algorithmic-thinking-2,https://coursera.org/learn/algorithmic-thinking-2,Computer Sciences,Rice University,"Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of ""Algorithmic Thinking"", allowing them to build simpler, more efficient solutions to computational problems."
  Software Security ,software-security,https://coursera.org/learn/software-security,Computer Sciences,"University of Maryland, College Park","This course we will explore the foundations of software security. We will consider important software vulnerabilities and attacks that exploit them -- such as buffer overflows, SQL injection, and session hijacking -- and we will consider defenses that prevent or mitigate these attacks, including advanced testing and program analysis techniques. Importantly, we take a ""build security in"" mentality, considering techniques at each phase of the development cycle that can be used to strengthen the security of software systems."
  Principles of Computing (Part 2),principles-of-computing-2,https://coursera.org/learn/principles-of-computing-2,Computer Sciences,Rice University,"This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Understanding these principles is crucial to the process of creating efficient and well-structured solutions for computational problems. To get hands-on experience working with these concepts, we will use the Python programming language. The main focus of the class will be weekly mini-projects that build upon the mathematical and programming principles that are taught in the class."
  A developer's guide to the Internet of Things (IoT),developer-iot,https://coursera.org/learn/developer-iot,Computer Sciences,IBM,"This course is an entry level introduction to developing and deploying solutions for the Internet of Things. It will focus on capturing data from a trusted device and sending the data to a cloud platform where it can be exploited by the many services available. You will explore all the steps required to create a basic IoT solution using a popular device, the Raspberry Pi, and a trial version of the cloud-based IBM Watson IoT Platform."
  "Cloud Computing Concepts, Part 1",cloud-computing,https://coursera.org/learn/cloud-computing,Computer Sciences,University of Illinois at Urbana-Champaign,"Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies—all centered around distributed systems. Learn about such fundamental distributed computing ""concepts"" for cloud computing. Some of these concepts include: Clouds, MapReduce, key-value stores, Classical precursors, Widely-used algorithms, Classical algorithms, Scalability, Trending areas, And more!"
  Parallel programming,parprog1,https://coursera.org/learn/parprog1,Computer Sciences,École Polytechnique Fédérale de Lausanne,"With every smartphone and computer now boasting multiple processors, the use of functional ideas to facilitate parallel programming is becoming increasingly widespread. In this course, you'll learn the fundamentals of parallel programming, from task parallelism to data parallelism. In particular, you'll see how many familiar ideas from functional programming map perfectly to to the data parallel paradigm. We'll start the nuts and bolts how to effectively parallelize familiar collections operations, and we'll build up to parallel collections, a production-ready data parallel collections library available in the Scala standard library."
  Functional Programming Principles in Scala,progfun1,https://coursera.org/learn/progfun1,Computer Sciences,École Polytechnique Fédérale de Lausanne,"Functional programming is becoming increasingly widespread in industry. This trend is driven by the adoption of Scala as the main programming language for many applications. Scala fuses functional and object-oriented programming in a practical package. It interoperates seamlessly with both Java and Javascript. Scala is the implementation language of many important frameworks, including Apache Spark, Kafka, and Akka. It provides the core infrastructure for sites such as Twitter, Tumblr and also Coursera."
  Functional Program Design in Scala,progfun2,https://coursera.org/learn/progfun2,Computer Sciences,École Polytechnique Fédérale de Lausanne,"In this course you will learn how to apply the functional programming style in the design of larger applications. You'll get to know important new functional programming concepts, from lazy evaluation to structuring your libraries using monads. We'll work on larger and more involved examples, from state space exploration to random testing to discrete circuit simulators. You’ll also learn some best practices on how to write good Scala code in the real world."
  Running Experiments with Agile,building--agile-culture,https://coursera.org/learn/building--agile-culture,Computer Sciences,University of Virginia,"To deliver agile outcomes, you have to do more than implement an agile process; you have to create a culture of experimentation. It's this commitment to experimenting that's at the heart of today’s most successful implementations of agile. This course shows you how to integrate the practice of experimentation across concept testing, usability testing, functional testing, and continuous deployment."
  Creative Programming for Digital Media & Mobile Apps,digitalmedia,https://coursera.org/learn/digitalmedia,Computer Sciences,"University of London, Goldsmiths, University of London","This course is for anyone who would like to apply their technical skills to creative work ranging from video games to art installations to interactive music, and also for artists who would like to use programming in their artistic practice. This course will teach you how to develop and apply programming skills to creative work. This is an important skill within the development of creative mobile applications, digital music and video games. It will teach the technical skills needed to write software that make use of images, audio and graphics, and will concentrate on the application of these skills to creative projects."
  Algorithms on Graphs and Trees,algorithms-on-graphs-and-trees,https://coursera.org/learn/algorithms-on-graphs-and-trees,Computer Sciences,"University of California, San Diego, Higher School of Economics","If you have ever used a navigation service to find optimal route and estimate time to destination, you've used algorithms on graphs. Graphs arise in various real-world situations as there are road networks, computer networks and, most recently, social networks! If you're looking for the fastest time to get to work, cheapest way to connect set of computers into a network or efficient algorithm to automatically find communities and opinion leaders in Facebook, you're going to work with graphs and algorithms on graphs. In this course, you will first learn what a graph is and what are some of the most important properties."
  Software Architecture for the Internet of Things,iot-software-architecture,https://coursera.org/learn/iot-software-architecture,Computer Sciences,EIT Digital,"This course will teach you how to design futureproof systems that meet the requirements of IoT systems: systems that are secure, interoperable, modifiable and scalable. Moreover, you'll learn to apply best-in-class software architecture methods to help you design complex IoT and other applications. Lastly, you'll come to understand the business impact of the technical decisions that you make as an IoT system architect."
  Introduction to User Experience Design ,user-experience-design,https://coursera.org/learn/user-experience-design,Computer Sciences,Georgia Institute of Technology,The focus of this course is to introduce the learner to User Experience (UX) Design User Experience design is design that is user centered. The goal is to design artifacts that allow the users to meet their needs in the most effective efficient and satisfying manner. The course introduces the novice to a cycle of discovery and evaluation and a set of techniques that meet the user's needs.
  Cloud Computing Concepts: Part 2,cloud-computing-2,https://coursera.org/learn/cloud-computing-2,Computer Sciences,University of Illinois at Urbana-Champaign,"Cloud computing systems today, whether open-source or used inside companies, are built using a common set of core techniques, algorithms, and design philosophies—all centered around distributed systems. Learn about such fundamental distributed computing ""concepts"" for cloud computing. Some of these concepts include: Clouds, MapReduce, key-value stores, Classical precursors, Widely-used algorithms, Classical algorithms, Scalability, Trending areas, And more!"
  Hardware Security,hardware-security,https://coursera.org/learn/hardware-security,Computer Sciences,"University of Maryland, College Park","In this course, we will study security and trust from the hardware perspective. Upon completing the course, students will understand the vulnerabilities in current digital system design flow and the physical attacks to these systems. They will learn that security starts from hardware design and be familiar with the tools and skills to build secure and trusted hardware."
  Introduction to Natural Language Processing,nlpintro,https://coursera.org/learn/nlpintro,Computer Sciences,University of Michigan,"This course provides an introduction to the field of Natural Language Processing. It includes relevant background material in Linguistics, Mathematics, Probabilities, and Computer Science. Some of the topics covered in the class are Text Similarity, Part of Speech Tagging, Parsing, Semantics, Question Answering, Sentiment Analysis, and Text Summarization."
  Cybersecurity and Mobility,cybersecurity-and-mobility,https://coursera.org/learn/cybersecurity-and-mobility,Computer Sciences,University System of Georgia,"This course is for you if you are interested in transitioning toward a managerial role in cybersecurity and mobility. Through interviews with industry experts in this area, you will be able to analyze innovations powering the rapid spread of information technology and how they present new challenges for protecting data."
  Introduction to Architecting Smart IoT Devices,iot-devices,https://coursera.org/learn/iot-devices,Computer Sciences,EIT Digital,"Embedded Systems are so ubiquitous that some of us take them for granted: we find them in smartphones, GPS systems, airplanes and so on. But have you ever wondered how these devices actually work? If so, you're in the right place! In this course, you'll learn about the characteristics of embedded systems: the possibilities, dangers, complications and recipes for success."
  "Programming Languages, Part A",programming-languages,https://coursera.org/learn/programming-languages,Computer Sciences,University of Washington,"This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones."
  Algorithms on Strings,algorithms-on-strings,https://coursera.org/learn/algorithms-on-strings,Computer Sciences,"University of California, San Diego, Higher School of Economics","World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome."
  Cybersecurity and the Internet of Things,cybersecurity-and-the-internet-of-things,https://coursera.org/learn/cybersecurity-and-the-internet-of-things,Computer Sciences,University System of Georgia,"Welcome! You may have heard about the Internet of Things (IoT). But you may also have wondered about what it is. Or for that matter, what does it mean to you or an organization. This course is for you if you are curious about the most recent trends and activities in the internet capabilities and concerns about programmed devices. There are complexities and areas of necessary awareness when the industrial sector becomes connected to your home. Security policies and practices have not yet caught up to the internet capabilities of some of our most common products."
  Modeling Discrete Optimization,modelingoptimization,https://coursera.org/learn/modelingoptimization,Computer Sciences,The University of Melbourne,Learn a new way to approach problem solving by stating the problem and letting powerful constraint solving software do the rest. This class teaches you the art of encoding complex discrete optimization problems in the MiniZinc modeling language and then shows you how to effortlessly solve them by leveraging state-of-the-art open-source constraint solving software.
  System Validation: Automata and behavioural equivalences,automata-system-validation,https://coursera.org/learn/automata-system-validation,Computer Sciences,EIT Digital,"Have you ever experienced software systems failing? Websites crash, calendar not synchronising, or even a power blackout. Of course you have! But did you know that many of these errors are the result of communication errors either within a system or between systems? Depending on the system, the impact of software failures can be huge, even resulting in massive economic damage or loss of lives. Software, and in particular the communication between software-intensive systems, is very complex and very difficult to get right."
  Embedded Hardware and Operating Systems,embedded-operating-system,https://coursera.org/learn/embedded-operating-system,Computer Sciences,EIT Digital,"This course is intended for the Bachelor and Master's students, who like practical programming and making IoTs applications! In this course we will talk about two components of a cyber physical system, namely hardware and operating systems. After completing this course, you will have the knowledge of both hardware components and operating systems. You are able to plan and use embedded operating systems in resource-constraint devices for Internet-of-Things (cyber physical system) applications."
  Architecting Smart IoT Devices,iot-architecture,https://coursera.org/learn/iot-architecture,Computer Sciences,EIT Digital,"This course will teach you how to develop an embedded systems device. In order to reduce the time to market, many pre-made hardware and software components are available today. You'll discover all the available hardware and software components, such as processor families, operating systems, boards and networks. You'll also learn how to actually use and integrate these components."
  "C++ For C Programmers, Part B",c-plus-plus-b,https://coursera.org/learn/c-plus-plus-b,Computer Sciences,"University of California, Santa Cruz",This course is for experienced C programmers who want to program in C++. The examples and exercises require a basic understanding of algorithms and object-oriented software.
  Cybersecurity and the X-Factor,cybersecurity-and-x-factor,https://coursera.org/learn/cybersecurity-and-x-factor,Computer Sciences,University System of Georgia,"What is the X-Factor? In Cybersecurity, the X-Factor related to unknown and unpredictable human behavior within and outside of your organization. “No one really knows why humans do what they do”, (David K. Reynolds), and because of this organizations can be unprepared for malicious, untrained, or even best intentioned behavior that can cause alarm and sometimes irreparable harm."
  Advanced Algorithms and Complexity,advanced-algorithms-and-complexity,https://coursera.org/learn/advanced-algorithms-and-complexity,Computer Sciences,"University of California, San Diego, Higher School of Economics","You've learned the basic algorithms now and 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."
  "Algorithms, Part I",introduction-to-algorithms,https://coursera.org/learn/introduction-to-algorithms,Computer Sciences,Princeton University,"This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms."
  "Programming Languages, Part B",programming-languages-part-b,https://coursera.org/learn/programming-languages-part-b,Computer Sciences,University of Washington,"This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones."
  Single Page Web Applications with AngularJS,single-page-web-apps-with-angularjs,https://coursera.org/learn/single-page-web-apps-with-angularjs,Computer Sciences,Johns Hopkins University,"Do you want to write powerful, maintainable, and testable front end applications faster and with less code? Then consider joining this course to gain skills in one of the most popular Single Page Application (SPA) frameworks today, AngularJS. Developed and backed by Google, AngularJS is a very marketable skill to acquire."
  Python Programming: A Concise Introduction,python-programming-introduction,https://coursera.org/learn/python-programming-introduction,Computer Sciences,Wesleyan University,"The goal of the course is to introduce students to Python Version 3.x programming using hands on instruction. It will show how to install Python and use the Spyder IDE (Integrated Development Environment) for writing and debugging programs. The approach will be to present an example followed by a small exercise where the learner tries something similar to solidify a concept. At the end of each module there will be an exercise where the student is required to write simple programs and submit them for grading. It is intended for students with little or no programming background, although students with such a background should be able to move forward at their preferred pace. The course is four modules long and is designed to be completed in four weeks."
  Introduction to UI Design,ui-design,https://coursera.org/learn/ui-design,Computer Sciences,University of Minnesota,"In this course, you will gain an understanding of the critical importance of user interface design. You will also learn industry-standard methods for how to approach the design of a user interface and key theories and frameworks that underlie the design of most interfaces you use today. Through a series of case studies on commercial systems - many of which you likely use on a regular basis - we will illustrate the benefits of good design. We will also demonstrate how the costs of bad design can often be severe (in user experience, money, and even human lives)."
  Getting started with Augmented Reality,augmented-reality,https://coursera.org/learn/augmented-reality,Computer Sciences,Institut Mines-Télécom,"This course will teach you the basics of developing mobile applications using Mixed and Augmented Reality (MAR) technologies. Through hands-on projects, you’ll learn practical techniques to rapidly and easily prototype three different applications for Android smartphones and tablets – even with no previous coding experience. If you’re a creative entrepreneur, this is your ideal introduction to today’s trends in the products and technologies of the emerging augmented reality market."
  Introduction to Web Development,web-development,https://coursera.org/learn/web-development,Computer Sciences,"University of California, Davis","This course is designed to start you on a path toward future studies in web development and design, no matter how little experience or technical knowledge you currently have. The web is a very big place, and if you are the typical internet user, you probably visit several websites every day, whether for business, entertainment or education. But have you ever wondered how these websites actually work? How are they built? How do browsers, computers, and mobile devices interact with the web?"
  Audio Signal Processing for Music Applications,audio-signal-processing,https://coursera.org/learn/audio-signal-processing,Computer Sciences,"Universitat Pompeu Fabra of Barcelona, Stanford University","In this course you will learn about audio signal processing methodologies that are specific for music and of use in real applications. We focus on the spectral processing techniques of relevance for the description and transformation of sounds, developing the basic theoretical and practical knowledge with which to analyze, synthesize, transform and describe audio signals in the context of music applications. The course is based on open software and content. The demonstrations and programming exercises are done using Python under Ubuntu, and the references and materials for the course come from open online repositories."
  Computational Neuroscience,computational-neurosciencecompneuro,https://coursera.org/learn/computational-neurosciencecompneuro,Computer Sciences,University of Washington,"This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning."
  Learn to Program: The Fundamentals,learn-to-program,https://coursera.org/learn/learn-to-program,Computer Sciences,University of Toronto,": Behind every mouse click and touch-screen tap, there is a computer program that makes things happen. This course introduces the fundamental building blocks of programming and teaches you how to write fun and useful programs using the Python language"
  "Cloud Computing Applications, Part 2",cloud-applications-2,https://coursera.org/learn/cloud-applications-2,Computer Sciences,University of Illinois at Urbana-Champaign,"Welcome to the Cloud Computing Applications course, the second part of a two-course series designed to give you a comprehensive view on the world of Cloud Computing and Big Data! In this second course we continue Cloud Computing Applications by exploring how the Cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Cloud applications and data analytics represent a disruptive change in the ways that society is informed by, and uses information. We start the first week by introducing some major systems for data analysis including Spark and the major frameworks and distributions of analytics applications including Hortonworks, Cloudera, and MapR."
  Android App Components and Data Persistence,androidapps,https://coursera.org/learn/androidapps,Computer Sciences,Vanderbilt University,"This 4 week MOOC builds upon the overview of Java and Android covered in Course 1 by delving deeper into core Android app components, such as intents, activities, and broadcast receivers. You will learn by example how to program these core Android components together with Android concurrency frameworks and basic Java file I/O classes (such as File and InputStream) and Android storage mechanisms (such as Shared Preferences). You'll also learn how to use the Git source code management system. Throughout this MOOC you'll work incrementally on a project involving downloading, storing, and display images from remote websites. Each week you will add additional capabilities to the project, based on material covered in the lecture videos."
  "Programming Languages, Part C",programming-languages-part-c,https://coursera.org/learn/programming-languages-part-c,Computer Sciences,University of Washington,"This course is an introduction to the basic concepts of programming languages, with a strong emphasis on functional programming. The course uses the languages ML, Racket, and Ruby as vehicles for teaching the concepts, but the real intent is to teach enough about how any language “fits together” to make you more effective programming in any language -- and in learning new ones."
  Discrete Optimization,optimization,https://coursera.org/learn/optimization,Computer Sciences,The University of Melbourne,"Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming. Optimization technology is ubiquitous in our society. It schedules planes and their crews, coordinates the production of steel, and organizes the transportation of iron ore from the mines to the ports. Optimization clears the day-ahead and real-time markets to deliver electricity to millions of people."
  "Divide and Conquer, Sorting and Searching, and Randomized Algorithms",algorithms-divide-conquer,https://coursera.org/learn/algorithms-divide-conquer,Computer Sciences,Stanford University,"The primary topics in this part of the specialization are: asymptotic (""Big-oh"") notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and randomized algorithms (QuickSort, contraction algorithm for min cuts)."
  User Research and Design,design-research,https://coursera.org/learn/design-research,Computer Sciences,University of Minnesota,"In this course you will learn and practice techniques of user research and early UI design exploration. First, you will learn and practice several techniques for user research, including in-person research and survey and log-analysis techniques. Then, you will learn to analyze and deliver user research in forms that support UI design, including personas, use cases, tasks, and scenarios. Finally, you will learn and practice ideation techniques that start from user research and broadly generate potential design ideas."
  Web Connectivity and Security in Embedded Systems,iot-connectivity-security,https://coursera.org/learn/iot-connectivity-security,Computer Sciences,EIT Digital,"In this course, we will explore several technologies that bring modern devices together, facilitating a network of connected things and making devices internet enabled. We will discuss rules, protocols, and standards for these devices to communicate with each other in the network. We will also go through security and privacy issues and challenges in cyber physical systems (CPS). We will explore measures and techniques for securing systems from different perspectives. Possible attack models are introduced and solutions to tackle such attacks are discussed. Moreover, some basic concepts related to privacy in cyber physical systems are presented."
  Cloud Networking,cloud-networking,https://coursera.org/learn/cloud-networking,Computer Sciences,University of Illinois at Urbana-Champaign,"This course will allow us to explore in-depth the challenges for cloud networking—how do we build a network infrastructure that provides the agility to deploy virtual networks on a shared infrastructure, that enables both efficient transfer of big data and low latency communication, and that enables applications to be federated across countries and continents? Examining how these objectives are met will set the stage for the rest of the course."
  System Validation (2): Model process behaviour,system-validation-behavior,https://coursera.org/learn/system-validation-behavior,Computer Sciences,EIT Digital,"System Validation is the field that studies the fundamentals of system communication and information processing. It is the next logical step in computer science and improving software development in general. It allows automated analysis based on behavioural models of a system to see if a system works correctly. We want to guarantee that the systems does exactly what it is supposed to do. The techniques put forward in system validation allow to prove the absence of errors. It allows to design embedded system behaviour that is structurally sound and as a side effect enforces you to make the behaviour simple and insightful. This means that the systems are not only behaving correctly, but are also much easier to maintain and adapt. ’Model process behaviour' is the follow up MOOC to 'Automata and behavioural equivalences'. This MOOC shows you how to model process behaviour, in particular protocols and distributed algorithms, dive deeper in the properties of system behaviour, and keep things simple to avoid a state space explosion. Reading material. J.F. Groote and M.R. Mousavi. Modeling and analysis of communicating systems."
  "Graph Search, Shortest Paths, and Data Structures",algorithms-graphs-data-structures,https://coursera.org/learn/algorithms-graphs-data-structures,Computer Sciences,Stanford University,"The primary topics in this part of the specialization are: data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search, connectivity, shortest paths), and their applications (ranging from deduplication to social network analysis)."
  Quantitative Model Checking,quantitative-model-checking,https://coursera.org/learn/quantitative-model-checking,Computer Sciences,EIT Digital,"Model checking focuses on the qualitative evaluation of the model. As formal verification method, model checking analyzes the functionality of the system model. A property that needs to be analyzed has to be specified in a logic with consistent syntax and semantics. For every state of the model, it is then checked whether the property is valid or not. The main focus of this course is on quantitative model checking for Markov chains, for which we will discuss efficient computational algorithms. The learning objectives of this course are as follows: - Express dependability properties for different kinds of transition systems . - Compute the evolution over time for Markov chains. - Check whether single states satisfy a certain formula and compute the satisfaction set for properties."
  Fundamentals of Computer Architecture,computer-architecture-fundamentals,https://coursera.org/learn/computer-architecture-fundamentals,Computer Sciences,EIT Digital,"This course introduces several topics for the learners about the fundamentals of computer architecture. After completing this course, the students will have the basic knowledge of: • Computer Performance and Benchmarks • Summarizing Performance • Amdahl’s law • Introduction to Embedded Systems"
  Bitcoin and Cryptocurrency Technologies,cryptocurrency,https://coursera.org/learn/cryptocurrency,Computer Sciences,Princeton University,"To really understand what is special about Bitcoin, we need to understand how it works at a technical level. We’ll address the important questions about Bitcoin, such as: How does Bitcoin work? What makes Bitcoin different? How secure are your Bitcoins? How anonymous are Bitcoin users? What determines the price of Bitcoins? Can cryptocurrencies be regulated? What might the future hold? After this course, you’ll know everything you need to be able to separate fact from fiction when reading claims about Bitcoin and other cryptocurrencies. You’ll have the conceptual foundations you need to engineer secure software that interacts with the Bitcoin network. And you’ll be able to integrate ideas from Bitcoin in your own projects."
  Data Processing Using Python,python-data-processing,https://coursera.org/learn/python-data-processing,Computer Sciences,Nanjing University,"This course (The English copy of ""用Python玩转数据"" <https://www.coursera.org/learn/hipython/home/welcome>) is mainly for non-computer majors. It starts with the basic syntax of Python, to how to acquire data in Python locally and from network, to how to present data, then to how to conduct basic and advanced statistic analysis and visualization of data, and finally to how to design a simple GUI to present and process data, advancing level by level. This course, as a whole, based on Yahoo Finance data and through establishment of popular cases one after another, enables learners to more vividly feel the simplicity, elegance and robustness of Python. Also, it discusses the fast, convenient and efficient data processing capacity of Python in humanities and social sciences fields like literature, sociology and journalism and science and engineering fields like mathematics and biology, in addition to business fields. Similarly, it may also be flexibly applied into other fields."
  "Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming",algorithms-greedy,https://coursera.org/learn/algorithms-greedy,Computer Sciences,Stanford University,"The primary topics in this part of the specialization are: greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal search trees)."
  Configuration Management on Google Cloud Platform,gcp-configuration-management,https://coursera.org/learn/gcp-configuration-management,Computer Sciences,Google Cloud,"This course introduces configuration management on Google Cloud Platform (GCP). Many of the concepts in this course rely on topics covered in earlier courses in the specialization, so if you haven’t yet worked through that material, you should go back and complete the first and second courses. The labs in this course also rely on work you should have completed in the labs in the previous course. If you haven’t completed the labs in the previous course you should go back and make sure you work through all the labs and have an image of the Guestbook container before moving on to the labs in this course."
  "Computing, Storage and Security with Google Cloud Platform",gcp-security,https://coursera.org/learn/gcp-security,Computer Sciences,Google Cloud,"This course covers the details of Computing, Storage and Security on Google Cloud Platform (GCP). You should be familiar with the fundamentals of working with Google Cloud Platform before working through this course. If you’re new to cloud in general, or Google Cloud Platform in particular, you should first work through our introductory course, Google Cloud Platform Fundamentals. In this course, you learn how to manage both individual and groups of instances or virtual machines and their related resources like disks and IP addresses. You also learn about creating and configuring networks and firewall rules from scratch. You learn about securely managing access to your projects using Identity and Access Management or IAM. Finally, you learn about managing Google Cloud Storage resources in your projects."
  Designing Highly Scalable Web Apps on Google Cloud Platform,gcp-scalable-web-apps,https://coursera.org/learn/gcp-scalable-web-apps,Computer Sciences,Google Cloud,This course covers the details of designing highly available and scalable applications and services on Google Cloud Platform (GCP). In this course you learn how to configure autoscaling with Compute Engine instance groups. You also configure a highly available architecture to serve web content across multiple fault-tolerant instance groups in different zones using a load balancer. This part of the course also includes an introductory lab on Google Cloud Deployment Manager to help you further automate the management and deployment of Google Cloud Platform resources.
  Google Cloud Platform Fundamentals,gcp-fundamentals,https://coursera.org/learn/gcp-fundamentals,Computer Sciences,Google Cloud,"This course covers the fundamentals of Google Cloud Platform. This course introduces you to important concepts and terminology for working with Google Cloud Platform (GCP). You learn about, and compare, many of the computing and storage services available in Google Cloud Platform, including Google App Engine, Google Compute Engine, and Google Container Engine. Notes: • You'll need a Google/Gmail account and a credit card or bank account to sign up for the Google Cloud Platform free trial (Google is currently blocked in China). • There is a known issue with certain EU countries where individuals are not able to sign up, but you may sign up as ""business"" status and intend to see a potential economic benefit from the trial. More details at: https://support.google.com/cloud/answer/6090602"
  "System Validation (4): Modelling Software, Protocols, and other behaviour",system-validation-software-protocols,https://coursera.org/learn/system-validation-software-protocols,Computer Sciences,EIT Digital,"System Validation is the field that studies the fundamentals of system communication and information processing. It allows automated analysis based on behavioural models of a system to see if a system works correctly. We want to guarantee that the systems does exactly what it is supposed to do. The techniques put forward in system validation allow to prove the absence of errors. It allows to design embedded system behaviour that is structurally sound and as a side effect enforces you to make the behaviour simple and insightful. This means that the systems are not only behaving correctly, but are also much easier to maintain and adapt. ’Modeling Software Protocols, and other behaviour' demonstrates the power of formal methods in software modelling, communication protocols, and other examples."
  System Validation (3): Requirements by modal formulas,system-validation-modal-formulas,https://coursera.org/learn/system-validation-modal-formulas,Computer Sciences,EIT Digital,"System Validation is the field that studies the fundamentals of system communication and information processing. It allows automated analysis based on behavioural models of a system to see if a system works correctly. We want to guarantee that the systems does exactly what it is supposed to do. The techniques put forward in system validation allow to prove the absence of errors. It allows to design embedded system behaviour that is structurally sound and as a side effect enforces you to make the behaviour simple and insightful. This means that the systems are not only behaving correctly, but are also much easier to maintain and adapt. ’Requirements by modal formulas' is the third course that shows you how to specify requirements for the automata in order to establish the correct relation between the requirements and the behaviour of the system. Reading material. J.F. Groote and M.R. Mousavi. Modeling and analysis of communicating systems."
  "Shortest Paths Revisited, NP-Complete Problems and What To Do About Them",algorithms-npcomplete,https://coursera.org/learn/algorithms-npcomplete,Computer Sciences,Stanford University,"The primary topics in this part of the specialization are: shortest paths (Bellman-Ford, Floyd-Warshall, Johnson), NP-completeness and what it means for the algorithm designer, and strategies for coping with computationally intractable problems (analysis of heuristics, local search)."
  Building and Deploying Android App Projects,badaap,https://coursera.org/learn/badaap,Computer Sciences,Vanderbilt University,"This 4 week MOOC builds upon the core Android app components and concurrency frameworks covered in Course 2 by focusing on started and bound services, local inter-process communication (IPC), and content providers. Case study apps will be examined from multiple perspectives to learn how to program these app components using Android's material design paradigm. Students will work incrementally on a hands-on project involving a material design-based RSS reader app. Each week you will add additional capabilities to the project, based on material covered in the lecture videos. You'll spend roughly 4 hours per week watching video lectures, taking quizzes, and programming assignments with Java and Android."
  Prototyping and Design,prototyping-design,https://coursera.org/learn/prototyping-design,Computer Sciences,University of Minnesota,"In this course you will learn how to design and prototype user interfaces to address the users and tasks identified in user research. Through a series of lectures and exercises, you will learn and practice paper- and other low-fidelity prototyping techniques; you will learn and apply principles from graphic design, including design patterns; you will learn to write a design rationale; and you will learn how to design for specific populations and situations, including principles and practices of accessible design."
  Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course),nand2tetris2,https://coursera.org/learn/nand2tetris2,Computer Sciences,Hebrew University of Jerusalem,"In this project-centered course you will build a modern software hierarchy, designed to enable the translation and execution of object-based, high-level languages on a bare-bone computer hardware platform. In particular, you will implement a virtual machine and a compiler for a simple, Java-like programming language, and you will develop a basic operating system that closes gaps between the high-level language and the underlying hardware platform. In the process, you will gain a deep, hands-on understanding of numerous topics in applied computer science, e.g. stack processing, parsing, code generation, and classical algorithms and data structures for memory management, vector graphics, input-output handling, and various other topics that lie at the very core of every modern computer system."
  Basic Modeling for Discrete Optimization,basic-modeling,https://coursera.org/learn/basic-modeling,Computer Sciences,"The University of Melbourne, The Chinese University of Hong Kong","Optimization is a common form of decision making, and is ubiquitous in our society. Its applications range from solving Sudoku puzzles to arranging seating in a wedding banquet. The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation of iron ore from the mines to the ports. Good decisions in manpower and material resources management also allow corporations to improve profit by millions of dollars. Similar problems also underpin much of our daily lives and are part of determining daily delivery routes for packages, making school timetables, and delivering power to our homes."
  Information Security: Context and Introduction,information-security-data,https://coursera.org/learn/information-security-data,Computer Sciences,University of London,"In this course you will explore information security through some introductory material and gain an appreciation of the scope and context around the subject. This includes a brief introduction to cryptography, security management and network and computer security that allows you to begin the journey into the study of information security and develop your appreciation of some key information security concepts. The course concludes with a discussion around a simple model of the information security industry and explores skills, knowledge and roles so that you can determine and analyse potential career opportunities in this developing profession and consider how you may need to develop personally to attain your career goals."
  Master of Computer Science - Data Science Applicant Community,mcs-ds-applicant,https://coursera.org/learn/mcs-ds-applicant,Computer Sciences,University of Illinois at Urbana-Champaign,"With a full tuition under $20K, the University of Illinois Master of Computer Science - Data Science (MCS-DS) is the most affordable gateway to one of the most lucrative and fastest growing careers of the new millennium. The MCS-DS builds expertise in four core areas of computer science: data visualization, machine learning, data mining and cloud computing, in addition to building valuable skill sets in statistics and information science with courses taught in collaboration with the University’s Statistics Department and ISchool (ranked #1 among Library and Information Studies Schools.) The purpose of this community is to provide you with resources and support during the application process for the MCS-DS."
  Advanced Modeling for Discrete Optimization,advancedmodeling,https://coursera.org/learn/advancedmodeling,Computer Sciences,"The University of Melbourne, The Chinese University of Hong Kong","Optimization is a common form of decision making, and is ubiquitous in our society. Its applications range from solving Sudoku puzzles to arranging seating in a wedding banquet. The same technology can schedule planes and their crews, coordinate the production of steel, and organize the transportation of iron ore from the mines to the ports. Good decisions in manpower and material resources management also allow corporations to improve profit by millions of dollars. Similar problems also underpin much of our daily lives and are part of determining daily delivery routes for packages, making school timetables, and delivering power to our homes."
  Engineering Maintainable Android Apps,engineeringandroidapps,https://coursera.org/learn/engineeringandroidapps,Computer Sciences,Vanderbilt University,"Engineering Maintainable Android Apps, which is a 4 week MOOC that shows by example various methods for engineering maintainable Android apps, including test-driven development methods and how to develop/run unit tests using JUnit and Robotium (or equivalent automated testing frameworks for Android), as well as how to successfully apply common Java/Android software patterns to improve the extensibility and clarity of Android apps. Students will work on the appropriate automated unit quizzes, based on the material covered in the lecture videos. These lessons will demonstrate the benefits of good software engineering practices that are targeted at creating maintainable code for mobile apps."
  Learn to Program: Crafting Quality Code,program-code,https://coursera.org/learn/program-code,Computer Sciences,University of Toronto,"Not all programs are created equal. In this course, we'll focus on writing quality code that runs correctly and efficiently. We'll design, code and validate our programs and learn how to compare programs that are addressing the same task."
  Introduction to Social Media Analytics,social-media-analytics-introduction,https://coursera.org/learn/social-media-analytics-introduction,Computer Sciences,Emory University,"Social media not only provides marketers with a means of communicating with their customers, but also a way to better understand their customers. Viewing consumers’ social media activity as the “voice of the consumer,” this session exposes learners to the analytic methods that can be used to convert social media data to marketing insights. In Introduction to Social Media Analytics, learners will be exposed to both the benefits and limitations of relying on social media data compared to traditional methods of marketing research. Partnering with a leading social media listening platform, this course provides learners with the foundational skills of social media listening including the creation of monitors and common social media metrics. Moving beyond social media listening, this course shows learners how social media data can be used to provide insights into market structure and consumers’ perceptions of the brand. Learners will have the opportunity to assess data and discern how to ""listen"" to the data by watching video lectures and completing activities, practice quizzes, discussion boards, and peer assessments."
  Big Data Analysis with Scala and Spark,big-data-analysys,https://coursera.org/learn/big-data-analysys,Computer Sciences,École Polytechnique Fédérale de Lausanne,"Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout. We'll cover Spark's programming model in detail, being careful to understand how and when it differs from familiar programming models, like shared-memory parallel collections or sequential Scala collections"
  Evaluating User Interfaces,ui-testing,https://coursera.org/learn/ui-testing,Computer Sciences,University of Minnesota,"In this course you will learn and practice several techniques for user interface evaluation. First we start with techniques that can be applied alone or in a design team, including action analysis, walkthroughs, and heuristic evaluation. Then we move on to user testing, including learning from a series of usability tests carried out in a real usability lab, and techniques to carry out your own tests even"
  Machine Learning,machine-learning,https://coursera.org/learn/machine-learning,Data Science,Stanford University,"Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI"
  Data Management and Visualization,data-visualization,https://coursera.org/learn/data-visualization,Data Science,Wesleyan University,"In this course, you will discover what data is and think about what questions you have that can be answered by the data – even if you’ve never thought about data before. Based on existing data, you will learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly. By the end of the course, you will be able to use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs. Throughout the course, you will share your progress with others to gain valuable feedback, while also learning how your peers use data to answer their own questions."
  Introduction to People Analytics,people-analytics,https://coursera.org/learn/people-analytics,Data Science,Moscow Institute of Physics and Technology,"This course is designed to provide you with an understanding of the role of data and technology in human capital management. Every topic in the course will be covered in the most practical way so that learners get hands-on experience. In the course we use the 4Ts principle: Task, Theory, Technique and Technology so that there is always a connection to organizational performance objectives, an overview of underlying theories and principles, and specific tools which help achieve business objectives."
  Data Manipulation at Scale: Systems and Algorithms,data-manipulation,https://coursera.org/learn/data-manipulation,Data Science,University of Washington,"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."
  Data Science in Real Life,real-life-data-science,https://coursera.org/learn/real-life-data-science,Data Science,Johns Hopkins University,"Have you ever had the perfect data science experience? The data pull went perfectly. There were no merging errors or missing data. Hypotheses were clearly defined prior to analyses. Randomization was performed for the treatment of interest. The analytic plan was outlined prior to analysis and followed exactly. The conclusions were clear and actionable decisions were obvious. Has that every happened to you? Of course not. Data analysis in real life is messy. How does one manage a team facing real data analyses? In this one-week course, we contrast the ideal with what happens in real life."
  Interprofessional Healthcare Informatics ,health-informatics-professional,https://coursera.org/learn/health-informatics-professional,Data Science,University of Minnesota,"Interprofessional Healthcare Informatics is a graduate-level, hands-on interactive exploration of real informatics tools and techniques offered by the University of Minnesota and the University of Minnesota's National Center for Interprofessional Practice and Education. We will be incorporating technology-enabled educational innovations to bring the subject matter to life. Over the 10 modules, we will create a vital online learning community and a working healthcare informatics network."
  Building a Data Science Team,build-data-science-team,https://coursera.org/learn/build-data-science-team,Data Science,Johns Hopkins University,"Data science is a team sport. As a data science executive it is your job to recruit, organize, and manage the team to success. In this one-week course, we will cover how you can find the right people to fill out your data science team, how to organize them to give them the best chance to feel empowered and successful, and how to manage your team as it grows."
  A Crash Course in Data Science,data-science-course,https://coursera.org/learn/data-science-course,Data Science,Johns Hopkins University,"By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials."
  Machine Learning Foundations: A Case Study Approach,ml-foundations,https://coursera.org/learn/ml-foundations,Data Science,University of Washington,Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems?
  Customer Analytics,wharton-customer-analytics,https://coursera.org/learn/wharton-customer-analytics,Data Science,University of Pennsylvania,"Data about our browsing and buying patterns are everywhere. From credit card transactions and online shopping carts, to customer loyalty programs and user-generated ratings/reviews, there is a staggering amount of data that can be used to describe our past buying behaviors, predict future ones, and prescribe new ways to influence future purchasing decisions. In this course, four of Wharton’s top marketing professors will provide an overview of key areas of customer analytics: descriptive analytics, predictive analytics, prescriptive analytics, and their application to real-world business practices including Amazon, Google, and Starbucks to name a few."
  Business Metrics for Data-Driven Companies,analytics-business-metrics,https://coursera.org/learn/analytics-business-metrics,Data Science,Duke University,"In this course, you will learn best practices for how to use data analytics to make any company more competitive and more profitable. You will be able to recognize the most critical business metrics and distinguish them from mere data. You’ll get a clear picture of the vital but different roles business analysts, business data analysts, and data scientists each play in various types of companies. And you’ll know exactly what skills are required to be hired for, and succeed at, these high-demand jobs."
  The Importance of Listening,importance-of-listening,https://coursera.org/learn/importance-of-listening,Data Science,Northwestern University,"In this second MOOC in the Social Marketing Specialization - ""The Importance of Listening"" - you will go deep into the Big Data of social and gain a more complete picture of what can be learned from interactions on social sites. You will be amazed at just how much information can be extracted from a single post, picture, or video. In this MOOC, guest speakers from Social Gist, BroadReader, Lexalytics, Semantria, Radian6, and IBM's Bluemix and Social Media Analytics Tools (SMA) will join Professor Hlavac to take you through the full range of analytics tools and options available to you and how to get the most from them."
  Mastering Data Analysis in Excel,analytics-excel,https://coursera.org/learn/analytics-excel,Data Science,Duke University,"Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality."
  Hadoop Platform and Application Framework,hadoop,https://coursera.org/learn/hadoop,Data Science,"University of California, San Diego","This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment."
  Data Analysis Tools,data-analysis-tools,https://coursera.org/learn/data-analysis-tools,Data Science,Wesleyan University,"In this course, you will develop and test hypotheses about your data. You will learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question. Using your choice of two powerful statistical software packages (SAS or Python), you will explore ANOVA, Chi-Square, and Pearson correlation analysis. This course will guide you through basic statistical principles to give you the tools to answer questions you have developed."
  Practical Predictive Analytics: Models and Methods,datasci2,https://coursera.org/learn/datasci2,Data Science,University of Washington,"Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems."
  Econometrics: Methods and Applications,erasmus-econometrics,https://coursera.org/learn/erasmus-econometrics,Data Science,Erasmus University Rotterdam,"Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making."
  Bioconductor for Genomic Data Science,genbioconductor,https://coursera.org/learn/genbioconductor,Data Science,Johns Hopkins University,Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.
  Regression Models,regression-models,https://coursera.org/learn/regression-models,Data Science,Johns Hopkins University,"Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing."
  Managing Big Data with MySQL,analytics-mysql,https://coursera.org/learn/analytics-mysql,Data Science,Duke University,"This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases."
  Relational Database Support for Data Warehouses,dwrelational,https://coursera.org/learn/dwrelational,Data Science,University of Colorado System,"Relational Database Support for Data Warehouses is the third course in the Data Warehousing for Business Intelligence specialization. In this course, you'll use analytical elements of SQL for answering business intelligence questions. You'll learn features of relational database management systems for managing summary data commonly used in business intelligence reporting. Because of the importance and difficulty of managing implementations of data warehouses, we'll also delve into storage architectures, scalable parallel processing, data governance, and big data impacts."
  Mathematical Biostatistics Boot Camp 2,biostatistics-2,https://coursera.org/learn/biostatistics-2,Data Science,Johns Hopkins University,"Learn fundamental concepts in data analysis and statistical inference, focusing on one and two independent samples."
  Exploratory Data Analysis,exploratory-data-analysis,https://coursera.org/learn/exploratory-data-analysis,Data Science,Johns Hopkins University,This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data.
  Developing Data Products,data-products,https://coursera.org/learn/data-products,Data Science,Johns Hopkins University,"A data product is the production output from a statistical analysis. Data products automate complex analysis tasks or use technology to expand the utility of a data informed model, algorithm or inference. This course covers the basics of creating data products using Shiny, R packages, and interactive graphics. The course will focus on the statistical fundamentals of creating a data product that can be used to tell a story about data to a mass audience."
  Classification,ml-classification,https://coursera.org/learn/ml-classification,Data Science,University of Washington,"In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank. These tasks are an examples of classification, one of the most widely used areas of machine learning, with a broad array of applications, including ad targeting, spam detection, medical diagnosis and image classification."
  Command Line Tools for Genomic Data Science,genomic-tools,https://coursera.org/learn/genomic-tools,Data Science,Johns Hopkins University,"Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University."
  Algorithms for DNA Sequencing,dna-sequencing,https://coursera.org/learn/dna-sequencing,Data Science,Johns Hopkins University,"We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets."
  "Communicating Results: Visualization, Ethics, Reproducibility",datasci3,https://coursera.org/learn/datasci3,Data Science,University of Washington,"Important note: The second assignment in this course covers the topic of Graph Analysis in the Cloud, in which you will use Elastic MapReduce and the Pig language to perform graph analysis over a moderately large dataset, about 600GB. In order to complete this assignment, you will need to make use of Amazon Web Services (AWS). Amazon has generously offered to provide up to $50 in free AWS credit to each learner in this course to allow you to complete the assignment. Further details regarding the process of receiving this credit are available in the welcome message for the course, as well as in the assignment itself."
  Statistical Inference,statistical-inference,https://coursera.org/learn/statistical-inference,Data Science,Johns Hopkins University,"Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance."
  Genomic Data Science with Galaxy,galaxy-project,https://coursera.org/learn/galaxy-project,Data Science,Johns Hopkins University,Learn to use the tools that are available from the Galaxy Project. This is the second course in the Genomic Big Data Science Specialization.
  "Business Intelligence Concepts, Tools, and Applications",dwbizintelligence,https://coursera.org/learn/dwbizintelligence,Data Science,University of Colorado System,"This is the fourth course in the Data Warehouse for Business Intelligence specialization. Ideally, the courses should be taken in sequence. In this course, you will gain the knowledge and skills for using data warehouses for business intelligence purposes and for working as a business intelligence developer. You’ll have the opportunity to work with large data sets in a data warehouse environment and will learn the use of MicroStrategy's Online Analytical Processing (OLAP) and Visualization capabilities to create visualizations and dashboards."
  Regression,ml-regression,https://coursera.org/learn/ml-regression,Data Science,University of Washington,"In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression."
  Practical Machine Learning,practical-machine-learning,https://coursera.org/learn/practical-machine-learning,Data Science,Johns Hopkins University,"One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates."
  R Programming,r-programming,https://coursera.org/learn/r-programming,Data Science,Johns Hopkins University,"In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code."
  Data Visualization and Communication with Tableau,analytics-tableau,https://coursera.org/learn/analytics-tableau,Data Science,Duke University,"One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand."
  Reproducible Research,reproducible-research,https://coursera.org/learn/reproducible-research,Data Science,Johns Hopkins University,"This course focuses on the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducible research is the idea that data analyses, and more generally, scientific claims, are published with their data and software code so that others may verify the findings and build upon them. The need for reproducibility is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available."
  Basic Statistics,basic-statistics,https://coursera.org/learn/basic-statistics,Data Science,University of Amsterdam,"Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics."
  Principles of fMRI 1,functional-mri,https://coursera.org/learn/functional-mri,Data Science,"Johns Hopkins University, University of Colorado Boulder","This course covers the design, acquisition, and analysis of Functional Magnetic Resonance Imaging (fMRI) data. A book related to the class can be found here: https://leanpub.com/principlesoffmri"
  Case studies in business analytics with ACCENTURE,case-studies-business-analytics-accenture,https://coursera.org/learn/case-studies-business-analytics-accenture,Data Science,ESSEC Business School,"This course is RESTRICTED TO LEARNERS ENROLLED IN Strategic Business Analytics SPECIALIZATION as a preparation to the capstone project. During the first two MOOCs, we focused on specific techniques for specific applications. Instead, with this third MOOC, we provide you with different examples to open your mind to different applications from different industries and sectors."
  The Data Scientist’s Toolbox,data-scientists-tools,https://coursera.org/learn/data-scientists-tools,Data Science,Johns Hopkins University,"In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools"
  Statistics for Genomic Data Science,statistical-genomics,https://coursera.org/learn/statistical-genomics,Data Science,Johns Hopkins University,An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.
  Research Data Management and Sharing,data-management,https://coursera.org/learn/data-management,Data Science,"The University of North Carolina at Chapel Hill, The University of Edinburgh","This course will provide learners with an introduction to research data management and sharing. After completing this course, learners will understand the diversity of data and their management needs across the research data lifecycle, be able to identify the components of good data management plans, and be familiar with best practices for working with data including the organization, documentation, and storage and security of data. Learners will also understand the impetus and importance of archiving and sharing data as well as how to assess the trustworthiness of repositories."
  Introduction to Genomic Technologies,introduction-genomics,https://coursera.org/learn/introduction-genomics,Data Science,Johns Hopkins University,"This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed."
  Regression Modeling in Practice,regression-modeling-practice,https://coursera.org/learn/regression-modeling-practice,Data Science,Wesleyan University,"This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results."
  Getting and Cleaning Data,data-cleaning,https://coursera.org/learn/data-cleaning,Data Science,Johns Hopkins University,"Before you can work with data you have to get some. This course will cover the basic ways that data can be obtained. The course will cover obtaining data from the web, from APIs, from databases and from colleagues in various formats. It will also cover the basics of data cleaning and how to make data “tidy”. Tidy data dramatically speed downstream data analysis tasks. The course will also cover the components of a complete data set including raw data, processing instructions, codebooks, and processed data."
  Machine Learning for Data Analysis,machine-learning-data-analysis,https://coursera.org/learn/machine-learning-data-analysis,Data Science,Wesleyan University,"Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to achieve this goal. Make sure to familiarize yourself with course 3 of this specialization before diving into these machine learning concepts. Building on Course 3, which introduces students to integral supervised machine learning concepts, this course will provide an overview of many additional concepts, techniques, and algorithms in machine learning, from basic classification to decision trees and clustering."
  Inferential Statistics,inferential-statistics,https://coursera.org/learn/inferential-statistics,Data Science,University of Amsterdam,"Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population."
  Python for Genomic Data Science,python-genomics,https://coursera.org/learn/python-genomics,Data Science,Johns Hopkins University,This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.
  Framework for Data Collection and Analysis,data-collection-framework,https://coursera.org/learn/data-collection-framework,Data Science,"University of Maryland, College Park","This course will provide you with an overview over existing data products and a good understanding of the data collection landscape. With the help of various examples you will learn how to identify which data sources likely matches your research question, how to turn your research question into measurable pieces, and how to think about an analysis plan. Furthermore this course will provide you with a general framework that allows you to not only understand each step required for a successful data collection and analysis, but also help you to identify errors associated with different data sources."
  Data Visualization,datavisualization,https://coursera.org/learn/datavisualization,Data Science,University of Illinois at Urbana-Champaign,"Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns."
  Introduction to Probability and Data,probability-intro,https://coursera.org/learn/probability-intro,Data Science,Duke University,"This course introduces you to sampling and exploring data, as well as basic probability theory and Bayes' rule. You will examine various types of sampling methods, and discuss how such methods can impact the scope of inference. A variety of exploratory data analysis techniques will be covered, including numeric summary statistics and basic data visualization. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project."
  Process Mining: Data science in Action,process-mining,https://coursera.org/learn/process-mining,Data Science,Eindhoven University of Technology,"Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are unable to use (big) data in a smart way will not survive."
  Principles of fMRI 2,functional-mri-2,https://coursera.org/learn/functional-mri-2,Data Science,"Johns Hopkins University, University of Colorado Boulder","This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data. It is a continuation of the course “Principles of fMRI, Part 1”"
  Inferential Statistics,inferential-statistics-intro,https://coursera.org/learn/inferential-statistics-intro,Data Science,Duke University,"This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project."
  Advanced Linear Models for Data Science 1 : Linear Models,advanced-linear-models-data-science,https://coursera.org/learn/advanced-linear-models-data-science,Data Science,Johns Hopkins University,"University of Maryland, College Park"
  Text Retrieval and Search Engines,text-retrieval,https://coursera.org/learn/text-retrieval,Data Science,University of Illinois at Urbana-Champaign,"Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text. This course will cover search engine technologies, which play an important role in any data mining applications involving text data for two reasons."
  Linear Regression and Modeling ,linear-regression-model,https://coursera.org/learn/linear-regression-model,Data Science,Duke University,"This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio."
  "Statistical Reasoning for Public Health 1: Estimation, Inference, & Interpretation",statistical-reasoning-1,https://coursera.org/learn/statistical-reasoning-1,Data Science,Johns Hopkins University,A conceptual and interpretive public health approach to some of the most commonly used methods from basic statistics.
  (2016) Graph Analytics for Big Data,graph-analytics-clone,https://coursera.org/learn/graph-analytics-clone,Data Science,"University of California, San Diego","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."
  (2016) Introduction to Big Data,intro-to-big-data-clone,https://coursera.org/learn/intro-to-big-data-clone,Data Science,"University of California, San Diego","Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world!"
  (2016) Machine Learning With Big Data,machinelearningwithbigdata-clone,https://coursera.org/learn/machinelearningwithbigdata-clone,Data Science,"University of California, San Diego","Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems"
  Big Data Modeling and Management Systems,big-data-management,https://coursera.org/learn/big-data-management,Data Science,"University of California, San Diego","Once you’ve identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions? In this course, you will experience various data genres and management tools appropriate for each. You will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples."
  Introduction to Neurohacking In R,neurohacking,https://coursera.org/learn/neurohacking,Data Science,Johns Hopkins University,"Neurohacking describes how to use the R programming language (https://cran.r-project.org/) and its associated package to perform manipulation, processing, and analysis of neuroimaging data. We focus on publicly-available structural magnetic resonance imaging (MRI). We discuss concepts such as inhomogeneity correction, image registration, and image visualization."
  Math behind Moneyball,mathematics-sport,https://coursera.org/learn/mathematics-sport,Data Science,University of Houston System,"Learn how probability, math, and statistics can be used to help baseball, football and basketball teams improve, player and lineup selection as well as in game strategy."
  Clustering & Retrieval,ml-clustering-and-retrieval,https://coursera.org/learn/ml-clustering-and-retrieval,Data Science,University of Washington,"A reader is interested in a specific news article and you want to find similar articles to recommend. What is the right notion of similarity? Moreover, what if there are millions of other documents? Each time you want to a retrieve a new document, do you need to search through all other documents? How do you group similar documents together? How do you discover new, emerging topics that the documents cover? In this third case study, finding similar documents, you will examine similarity-based algorithms for retrieval. In this course, you will also examine structured representations for describing the documents in the corpus, including clustering and mixed membership models, such as latent Dirichlet allocation (LDA)."
  Bayesian Statistics: From Concept to Data Analysis,bayesian-statistics,https://coursera.org/learn/bayesian-statistics,Data Science,"University of California, Santa Cruz","This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach to the more commonly-taught Frequentist approach, and see some of the benefits of the Bayesian approach. In particular, the Bayesian approach allows for better accounting of uncertainty, results that have more intuitive and interpretable meaning, and more explicit statements of assumptions. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience."
  Bayesian Statistics,bayesian,https://coursera.org/learn/bayesian,Data Science,Duke University,"This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. The course will apply Bayesian methods to several practical problems, to show end-to-end Bayesian analyses that move from framing the question to building models to eliciting prior probabilities to implementing in R (free statistical software) the final posterior distribution."
  Text Mining and Analytics,text-mining,https://coursera.org/learn/text-mining,Data Science,University of Illinois at Urbana-Champaign,"This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort."
  Statistical Reasoning for Public Health 2: Regression Methods,statistical-reasoning-2,https://coursera.org/learn/statistical-reasoning-2,Data Science,Johns Hopkins University,"A practical and example filled tour of simple and multiple regression techniques (linear, logistic, and Cox PH) for estimation, adjustment and prediction."
  Data-driven Decision Making,decision-making,https://coursera.org/learn/decision-making,Data Science,PwC,"Welcome to Data-driven Decision Making. In this course you'll get an introduction to Data Analytics and its role in business decisions. You'll learn why data is important and how it has evolved. You'll be introduced to “Big Data” and how it is used. You'll also be introduced to a framework for conducting Data Analysis and what tools and techniques are commonly used. Finally, you'll have a chance to put your knowledge to work in a simulated business setting."
  Dealing With Missing Data,missing-data,https://coursera.org/learn/missing-data,Data Science,"University of Maryland, College Park","This course will cover the steps used in weighting sample surveys, including methods for adjusting for nonresponse and using data external to the survey for calibration. Among the techniques discussed are adjustments using estimated response propensities, poststratification, raking, and general regression estimation. Alternative techniques for imputing values for missing items will be discussed. For both weighting and imputation, the capabilities of different statistical software packages will be covered, including R®, Stata®, and SAS®."
  Fundamentals of Visualization with Tableau,dataviz,https://coursera.org/learn/dataviz,Data Science,"University of California, Davis","In this first course of the specialization, you will discover just what data visualization is, and how we can use it to better see and understand data. Using Tableau, we’ll examine the fundamental concepts of data visualization and explore the Tableau interface, identifying and applying the various tools Tableau has to offer. By the end of the course you will be able to prepare and import data into Tableau and explain the relationship between data analytics and data visualization. This course is designed for the learner who has never used Tableau before, or who may need a refresher or want to explore Tableau in more depth"
  Big Data Integration and Processing,big-data-integration-processing,https://coursera.org/learn/big-data-integration-processing,Data Science,"University of California, San Diego","At the end of the course, you will be able to: *Retrieve data from example database and big data management systems *Describe the connections between data management operations and the big data processing patterns needed to utilize them in large-scale analytical applications"
  Pattern Discovery in Data Mining,data-patterns,https://coursera.org/learn/data-patterns,Data Science,University of Illinois at Urbana-Champaign,"Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns."
  Maps and the Geospatial Revolution,geospatial,https://coursera.org/learn/geospatial,Data Science,The Pennsylvania State University,"Learn how advances in geospatial technology and analytical methods have changed how we do everything, and discover how to make maps and analyze geographic patterns using the latest tools. The past decade has seen an explosion of new mechanisms for understanding and using location information in widely-accessible technologies. This Geospatial Revolution has resulted in the development of consumer GPS tools, interactive web maps, and location-aware mobile devices."
  Introduction to Data Analytics for Business,data-analytics-business,https://coursera.org/learn/data-analytics-business,Data Science,University of Colorado Boulder,"This course will expose you to the data analytics practices executed in the business. We will explore such key areas of data analytics as the analytical process, how data is created, stored, and accessed, and how the organization works with data and creates the environment in which analytics can flourish. What you learn in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success within your organization."
  Introduction to Recommender Systems:  Non-Personalized and Content-Based,recommender-systems-introduction,https://coursera.org/learn/recommender-systems-introduction,Data Science,University of Minnesota,"This course, which is designed to serve as the first course in the Recommender Systems specialization, introduces the concept of recommender systems, reviews several examples in detail, and leads you through non-personalized recommendation using summary statistics and product associations, basic stereotype-based or demographic recommendations, and content-based filtering recommendations."
  The R Programming Environment,r-programming-environment,https://coursera.org/learn/r-programming-environment,Data Science,Johns Hopkins University,"This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related ""tidyverse"" tools, processing and manipulation of complex and large datasets, handling textual data, and basic data science tasks."
  Social Media Data Analytics,social-media-data-analytics,https://coursera.org/learn/social-media-data-analytics,Data Science,Rutgers the State University of New Jersey,"Learner Outcomes: After taking this course, you will be able to: - Utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr. - Process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data. - Analyze unstructured data - primarily textual comments - for sentiments expressed in them. - Use different tools for collecting, analyzing, and exploring social media data for research and development purposes."
  Introduction to Data Analysis Using Excel,excel-data-analysis,https://coursera.org/learn/excel-data-analysis,Data Science,Rice University,The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This course is designed to give you a working knowledge of Excel with the aim of getting to use it for more advance topics in Business Statistics. The course is designed keeping in mind two kinds of learners - those who have very little functional knowledge of Excel and those who use Excel regularly and wish to enhance their skills.
  Probabilistic Graphical Models,probabilistic-graphical-models,https://coursera.org/learn/probabilistic-graphical-models,Data Science,Stanford University,"Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems."
  Julia Scientific Programming,julia-programming,https://coursera.org/learn/julia-programming,Data Science,University of Cape Town,"This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more. As open source software, you will always have it available throughout your working life. It can also be used from the command line, program files or a new type of interface known as a Jupyter notebook (which is freely available as a service from JuliaBox.com)."
  Hands-on Text Mining and Analytics,text-mining-analytics,https://coursera.org/learn/text-mining-analytics,Data Science,Yonsei University,"This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help learners be trained to be a competent data scientists."
  Cluster Analysis in Data Mining,cluster-analysis,https://coursera.org/learn/cluster-analysis,Data Science,University of Illinois at Urbana-Champaign,"Discover the basic concepts of cluster analysis, and then study a set of typical clustering methodologies, algorithms, and applications. This includes partitioning methods such as k-means, hierarchical methods such as BIRCH, and density-based methods such as DBSCAN/OPTICS. Moreover, learn methods for clustering validation and evaluation of clustering quality. Finally, see examples of cluster analysis in applications."
  Neural Networks for Machine Learning,neural-networks,https://coursera.org/learn/neural-networks,Data Science,University of Toronto,"Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well. This course contains the same content presented on Coursera beginning in 2013. It is not a continuation or update of the original course. It has been adapted for the new platform."
  Improving your statistical inferences,statistical-inferences,https://coursera.org/learn/statistical-inferences,Data Science,Eindhoven University of Technology,"This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power. Subsequently, you will learn how to interpret evidence in the scientific literature given widespread publication bias, for example by learning about p-curve analysis."
  Deception Detox - How solid science can help you save the world ,deceptiondetox,https://coursera.org/learn/deceptiondetox,Data Science,Erasmus University Rotterdam,"This course will help you become scientifically literate so that you can make better choices for yourself and the world. Unlike other courses on statistics and scientific methods, we explore global challenges - such as poverty or climate change - and then discuss how key approaches of statistics and scientific methods can help tackle these challenges. We present these approaches in a non-mathematical and easily accessible way. You will leave the course being able to recognize which efforts to do good in this world actually work, and you will have used your science literacy to make some personal changes in your life."
  Predictive Modeling and Analytics ,predictive-modeling-analytics,https://coursera.org/learn/predictive-modeling-analytics,Data Science,University of Colorado Boulder,"This course will expose you to the data analytics practices executed in the business. We will explore such key areas of data analytics as the analytical process, how data is created, stored, and accessed, and how the organization works with data and creates the environment in which analytics can flourish. What you learn in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success within your organization. You’ll develop skills and a perspective that will make you more productive faster and allow you to become a valuable asset to your organization."
  Advanced R Programming,advanced-r,https://coursera.org/learn/advanced-r,Data Science,Johns Hopkins University,"This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. Upon completing this course you will be able to identify and abstract common data analysis tasks and to encapsulate them in user-facing functions. Because every data science environment encounters unique data challenges, there is always a need to develop custom software specific to your organization’s mission."
  Nearest Neighbor Collaborative Filtering,collaborative-filtering,https://coursera.org/learn/collaborative-filtering,Data Science,University of Minnesota,"In this course, you will learn the fundamental techniques for making personalized recommendations through nearest-neighbor techniques. First you will learn user-user collaborative filtering, an algorithm that identifies other people with similar tastes to a target user and combines their ratings to make recommendations for that user. You will explore and implement variations of the user-user algorithm, and will explore the benefits and drawbacks of the general approach."
  Problem Solving with Excel ,excel-analysis,https://coursera.org/learn/excel-analysis,Data Science,PwC,"This course explores Excel as a tool for solving business problems. In this course you will learn the basic functions of excel through guided demonstration. Each week you will build on your excel skills and be provided an opportunity to practice what you’ve learned. Finally, you will have a chance to put your knowledge to work in a final project. Please note, the content in this course was developed using a Windows version of Excel 2013. This course was created by PricewaterhouseCoopers LLP with an address at 300 Madison Avenue, New York, New York, 10017."
  Introduction to Data Science in Python,python-data-analysis,https://coursera.org/learn/python-data-analysis,Data Science,University of Michigan,"This course will introduce the learner to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions. The course will also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis. The course will end with a statistics primer, showing how various statistical measures can be applied to pandas DataFrames. By the end of the course, students will be able to take tabular data, clean it, manipulate it, and run basic inferential statistical analyses."
  "Basic Data Descriptors, Statistical Distributions, and Application to Business Decisions",descriptive-statistics-statistical-distributions-business-application,https://coursera.org/learn/descriptive-statistics-statistical-distributions-business-application,Data Science,Rice University,"The ability to understand and apply Business Statistics is becoming increasingly important in the industry. A good understanding of Business Statistics is a requirement to make correct and relevant interpretations of data. Lack of knowledge could lead to erroneous decisions which could potentially have negative consequences for a firm. This course is designed to introduce you to Business Statistics. We begin with the notion of descriptive statistics, which is summarizing data using a few numbers. Different categories of descriptive measures are introduced and discussed along with the Excel functions to calculate them. The notion of probability or uncertainty is introduced along with the concept of a sample and population data using relevant business examples. This leads us to various statistical distributions along with their Excel functions which are then used to model or approximate business processes. You get to apply these descriptive measures of data and various statistical distributions using easy-to-follow Excel based examples which are demonstrated throughout the course."
  Essential Design Principals for Tableau,dataviz-design,https://coursera.org/learn/dataviz-design,Data Science,"University of California, Davis","In this course, you will analyze and apply essential design principles to your Tableau visualizations. This course assumes you understand the tools within Tableau and have some knowledge of the fundamental concepts of data visualization. You will define and examine the similarities and differences of exploratory and explanatory analysis as well as begin to ask the right questions about what’s needed in a visualization. You will assess how data and design work together, including how to choose the appropriate visual representation for your data, and the difference between effective and ineffective visuals. You will apply effective best practice design principles to your data visualizations and be able to illustrate examples of strategic use of contrast to highlight important elements."
  Business Analytics for Decision Making,business-analytics-decision-making,https://coursera.org/learn/business-analytics-decision-making,Data Science,University of Colorado Boulder,"In this course you will learn how to create models for decision making. We will start with cluster analysis, a technique for data reduction that is very useful in market segmentation. You will then learn the basics of Monte Carlo simulation that will help you model the uncertainty that is prevalent in many business decisions. A key element of decision making is to identify the best course of action. Since businesses problems often have too many alternative solutions, you will learn how optimization can help you identify the best option. What is really exciting about this course is that you won’t need to know a computer language or advanced statistics to learn about these predictive and prescriptive analytic models. The Analytic Solver Platform and basic knowledge of Excel is all you’ll need. Learners participating in assignments will be able to get free access to the Analytic Solver Platform."
  Advanced Linear Models for Data Science 2: Statistical Linear Models,linear-models-2,https://coursera.org/learn/linear-models-2,Data Science,Johns Hopkins University,Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language.
  Building R Packages,r-packages,https://coursera.org/learn/r-packages,Data Science,Johns Hopkins University,"Writing good code for data science is only part of the job. In order to maximizing the usefulness and reusability of data science software, code must be organized and distributed in a manner that adheres to community-based standards and provides a good user experience. This course covers the primary means by which R software is organized and distributed to others. We cover R package development, writing good documentation and vignettes, writing robust software, cross-platform development, continuous integration tools, and distributing packages via CRAN and GitHub. Learners will produce R packages that satisfy the criteria for submission to CRAN."
  Probabilistic Graphical Models 2: Inference,probabilistic-graphical-models-2-inference,https://coursera.org/learn/probabilistic-graphical-models-2-inference,Data Science,stanford University,"This course is the second in a sequence of three. Following the first course, which focused on representation, this course addresses the question of probabilistic inference: how a PGM can be used to answer questions. Even though a PGM generally describes a very high dimensional distribution, its structure is designed so as to allow questions to be answered efficiently. The course presents both exact and approximate algorithms for different types of inference tasks, and discusses where each could best be applied. The (highly recommended) honors track contains two hands-on programming assignments, in which key routines of the most commonly used exact and approximate algorithms are implemented and applied to a real-world problem."
  Communicating Business Analytics Results,communicating-business-analytics-results,https://coursera.org/learn/communicating-business-analytics-results,Data Science,University of Colorado Boulder,"The analytical process does not end with models than can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations. This depends on the ability to communicate results to those who make decisions. Presenting findings to decision makers who are not familiar with the language of analytics presents a challenge. In this course you will learn how to communicate analytics results to stakeholders who do not understand the details of analytics but want evidence of analysis and data. You will be able to choose the right vehicles to present quantitative information, including those based on principles of data visualization. You will also learn how to develop and deliver data-analytics stories that provide context, insight, and interpretation."
  Building Data Visualization Tools,r-data-visualization,https://coursera.org/learn/r-data-visualization,Data Science,Johns Hopkins University,"The data science revolution has produced reams of new data from a wide variety of new sources. These new datasets are being used to answer new questions in way never before conceived. Visualization remains one of the most powerful ways draw conclusions from data, but the influx of new data types requires the development of new visualization techniques and building blocks. This course provides you with the skills for creating those new visualization building blocks. We focus on the ggplot2 framework and describe how to use and extend the system to suit the specific needs of your organization or team. Upon completing this course, learners will be able to build the tools needed to visualize a wide variety of data types and will have the fundamentals needed to address new data types as they come about."
  Explaining Your Data Using Tableau,dataviz-explain,https://coursera.org/learn/dataviz-explain,Data Science,"University of California, Davis","In this third course of the specialization, we’ll drill deeper into the tools Tableau offers in the areas of charting, dates, table calculations and mapping. We’ll explore the best choices for charts, based on the type of data you are using. We’ll look at specific types of charts including scatter plots, Gantt charts, histograms, bullet charts and several others, and we’ll address charting guidelines. We’ll define discrete and continuous dates, and examine when to use each one to explain your data. You’ll learn how to create custom and quick table calculations and how to create parameters. We’ll also introduce mapping and explore how Tableau can use different types of geographic data, how to connect to multiple data sources and how to create custom maps."
  A developer's guide to Exploring and Visualizing IoT Data,exploring-visualizing-iot-data,https://coursera.org/learn/exploring-visualizing-iot-data,Data Science,IBM,"The value of IoT can be found within the analysis of data gathered from the system under observation, where insights gained can have direct impact on business and operational transformation. Through analysis data correlation, patterns, trends, and other insight are discovered. Insight leads to better communication between stakeholders, or actionable insights, which can be used to raise alerts or send commands, back to IoT devices. With a focus on the topic of Exploratory Data Analysis, the course provides an in-depth look at mathematical foundations of basic statistical measures, and how they can be used in conjunction with advanced charting libraries to make use of the world’s best pattern recognition system – the human brain. Learn how to work with the data, and depict it in ways that support visual inspections, and derive to inferences about the data. Identify interesting characteristics, patterns, trends, deviations or inconsistencies, and potential outliers."
  Business Applications of Hypothesis Testing and Confidence Interval Estimation ,hypothesis-testing-confidence-intervals,https://coursera.org/learn/hypothesis-testing-confidence-intervals,Data Science,Rice University,"Confidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox. A mastery over these topics will help enhance your business decision making and allow you to understand and measure the extent of ‘risk’ or ‘uncertainty’ in various business processes. This is the third course in the specialization ""Business Statistics and Analysis"" and the course advances your knowledge about Business Statistics by introducing you to Confidence Intervals and Hypothesis Testing. We first conceptually understand these tools and their business application. We then introduce various calculations to constructing confidence intervals and to conduct different kinds of Hypothesis Tests. These are done by easy to understand applications. To successfully complete course assignments, students must have access to a Windows version of Microsoft Excel 2010 or later. Please note that earlier versions of Microsoft Excel (2007 and earlier) will not be compatible to some Excel functions covered in this course."
  Probabilistic Graphical Models 3: Learning,probabilistic-graphical-models-3-learning,https://coursera.org/learn/probabilistic-graphical-models-3-learning,Data Science,Stanford University,"This course is the third in a sequence of three. Following the first course, which focused on representation, and the second, which focused on inference, this course addresses the question of learning: how a PGM can be learned from a data set of examples. The course discusses the key problems of parameter estimation in both directed and undirected models, as well as the structure learning task for directed models. The (highly recommended) honors track contains two hands-on programming assignments, in which key routines of two commonly used learning algorithms are implemented and applied to a real-world problem."
  An Intuitive Introduction to Probability,introductiontoprobability,https://coursera.org/learn/introductiontoprobability,Data Science,University of Zurich,"This course will provide you with an intuitive and practical introduction into Probability Theory. You will be able to learn how to apply Probability Theory in different scenarios and you will earn a ""toolbox"" of methods to deal with uncertainty in your daily life. The course is split in 5 modules. In each module you will first have an easy introduction into the topic, which will serve as a basis to further develop your knowledge about the topic and acquire the ""tools"" to deal with uncertainty. Additionally, you will have the opportunity to complete 5 exercise sessions to reflect about the content learned in each module and start applying your earned knowledge right away."
  Introduction to Formal Concept Analysis,formal-concept-analysis,https://coursera.org/learn/formal-concept-analysis,Data Science,Higher School of Economics,"This course is an introduction into formal concept analysis (FCA), a mathematical theory oriented at applications in knowledge representation, knowledge acquisition, data analysis and visualization. It provides tools for understanding the data by representing it as a hierarchy of concepts or, more exactly, a concept lattice. FCA can help in processing a wide class of data types providing a framework in which various data analysis and knowledge acquisition techniques can be formulated. In this course, we focus on some of these techniques, as well as cover the theoretical foundations and algorithmic issues of FCA."
  Data Visualization with Advanced Excel,advanced-excel,https://coursera.org/learn/advanced-excel,Data Science,PwC,"In this course, you will get hands-on instruction of advanced Excel 2013 functions. You’ll learn to use PowerPivot to build databases and data models. We’ll show you how to perform different types of scenario and simulation analysis and you’ll have an opportunity to practice these skills by leveraging some of Excel's built in tools including, solver, data tables, scenario manager and goal seek. In the second half of the course, will cover how to visualize data, tell a story and explore data by reviewing core principles of data visualization and dashboarding. You’ll use Excel to build complex graphs and Power View reports and then start to combine them into dynamic dashboards."
  Data Analytics for Lean Six Sigma,data-analytics-for-lean-six-sigma,https://coursera.org/learn/data-analytics-for-lean-six-sigma,Data Science,University of Amsterdam,In this course you will learn data analytics techniques that are typically useful within Lean Six Sigma improvement projects. At the end of this course you are able to analyse and interpret data gathered within such a project. You will be able to use Minitab to analyse the data. I will also briefly explain what Lean Six Sigma is. I will emphasize on use of data analytics tools and the interpretation of the outcome. I will use many different examples from actual Lean Six Sigma projects to illustrate all tools. I will not discuss any mathematical background.
  Business Analytics and Digital Media,business-analytics,https://coursera.org/learn/business-analytics,Data Science,Indian School of Business,"The explosion in digital media - web, social and now mobile - represents a departure from how things were like in the last century. This proliferation of digital media is both a threat and an opportunity for many businesses. Business Analytics can be leveraged to process data, sentiment, buzz, contacts, context and other aspects of business interest in real time, for business performance and impact. The course picks and uses use-cases from a variety of industries and geographies, to showcase the potential and impact that business analytics done properly (or not) can have on business performance."
  Recommender Systems:  Evaluation and Metrics,recommender-metrics,https://coursera.org/learn/recommender-metrics,Data Science,University of Minnesota,"In this course you will learn how to evaluate recommender systems. You will gain familiarity with several families of metrics, including ones to measure prediction accuracy, rank accuracy, decision-support, and other factors such as diversity, product coverage, and serendipity. You will learn how different metrics relate to different user goals and business goals. You will also learn how to rigorously conduct offline evaluations (i.e., how to prepare and sample data, and how to aggregate results). And you will learn about online (experimental) evaluation. At the completion of this course you will have the tools you need to compare different recommender system alternatives for a wide variety of uses"
  Linear Regression for Business Statistics,linear-regression-business-statistics,https://coursera.org/learn/linear-regression-business-statistics,Data Science,Rice University,"Regression Analysis is perhaps the single most important Business Statistics tool used in the industry. Regression is the engine behind a multitude of data analytics applications used for many forms of forecasting and prediction. This is the fourth course in the specialization, ""Business Statistics and Analysis"". The course introduces you to the very important tool known as Linear Regression. You will learn to apply various procedures such as dummy variable regressions, transforming variables, and interaction effects. All these are introduced and explained using easy to understand examples in Microsoft Excel. The focus of the course is on understanding and application, rather than detailed mathematical derivations."
  "Understanding China, 1700-2000: A Data Analytic Approach, Part 2",understanding-china-history-part-2,https://coursera.org/learn/understanding-china-history-part-2,Data Science,The Hong Kong University of Science and Technology,"The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history. Current understandings of human history and social theory are based largely on Western experience or on non-Western experience seen through a Western lens."
  "Understanding China, 1700-2000: A Data Analytic Approach, Part 1",understanding-china-history-part-1,https://coursera.org/learn/understanding-china-history-part-1,Data Science,The Hong Kong University of Science and Technology,"The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history."
  "Applied Plotting, Charting & Data Representation in Python",python-plotting,https://coursera.org/learn/python-plotting,Data Science,University of Michigan,"This course will introduce the learner to information visualization basics, with a focus on reporting and charting using the matplotlib library. The course will start with a design and information literacy perspective, touching on what makes a good and bad visualization, and what statistical measures translate into in terms of visualizations. The second week will focus on the technology used to make visualizations in python, matplotlib, and introduce users to best practices when creating basic charts and how to realize design decisions in the framework."
  Google Cloud Platform Big Data and Machine Learning Fundamentals,gcp-big-data-ml-fundamentals,https://coursera.org/learn/gcp-big-data-ml-fundamentals,Data Science,Google Cloud,"This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities. At the end of this course, participants will be able to: • Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform • Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform"
  Creating Dashboards and Storytelling with Tableau,dataviz-dashboards,https://coursera.org/learn/dataviz-dashboards,Data Science,"University of California, Davis","Leveraging the visualizations you created in the previous course, Visual Analytics with Tableau, you will create dashboards that help you identify the story within your data, and you will discover how to use Storypoints to create a powerful story to leave a lasting impression with your audience. You will balance the goals of your stakeholders with the needs of your end-users, and be able to structure and organize your story for maximum impact. Throughout the course you will apply more advanced functions within Tableau, such as hierarchies, actions and parameters to guide user interactions. For your final project, you will create a compelling narrative to be delivered in a meeting, as a static report, or in an interactive display online."
  Functional Programming in Scala Capstone,scala-capstone,https://coursera.org/learn/scala-capstone,Data Science,École Polytechnique Fédérale de Lausanne,"In the final capstone project you will apply the skills you learned by building a large data-intensive application using real-world data. You will implement a complete application processing several gigabytes of data. This application will show interactive visualizations of the evolution of temperatures over time all over the world. The development of such an application will involve: — transforming data provided by weather stations into meaningful information like, for instance, the average temperature of each point of the globe over the last ten years ; — then, making images from this information by using spatial and linear interpolation techniques ; — finally, implementing how the user interface will react to users’ actions."
  Data Analytics for Business Capstone,data-analytics-business-capstone,https://coursera.org/learn/data-analytics-business-capstone,Data Science,University of Colorado Boulder,"The analytics process is a collection of interrelated activities that lead to better decisions and to a higher business performance. The capstone of this specialization is designed with the goal of allowing you to experience this process. The capstone project will take you from data to analysis and models, and ultimately to presentation of insights. 
  
  In this capstone project, you will analyze the data on financial loans to help with the investment decisions of an investment company. You will go through all typical steps of a data analytics project, including data understanding and cleanup, data analysis, and presentation of analytical results. 
  