Online courses directory (684)

This is an introduction to quantum computation, a cutting edge field that tries to exploit the exponential power of computers based on quantum mechanics. The course does not assume any prior background in quantum mechanics, and can be viewed as a very simple and conceptual introduction to that field.

Introduction to programming and computer science. Introduction to Programs Data Types and Variables. Binary Numbers. Python Lists. For Loops in Python. While Loops in Python. Fun with Strings. Writing a Simple Factorial Program. (Python 2). Stepping Through the Factorial Program. Flowchart for the Factorial Program. Python 3 Not Backwards Compatible with Python 2. Defining a Factorial Function. Diagramming What Happens with a Function Call. Recursive Factorial Function. Comparing Iterative and Recursive Factorial Functions. Exercise - Write a Fibonacci Function. Iterative Fibonacci Function Example. Stepping Through Iterative Fibonacci Function. Recursive Fibonacci Example. Stepping Through Recursive Fibonacci Function. Exercise - Write a Sorting Function. Insertion Sort Algorithm. Insertion Sort in Python. Stepping Through Insertion Sort Function. Simpler Insertion Sort Function. Introduction to Programs Data Types and Variables. Binary Numbers. Python Lists. For Loops in Python. While Loops in Python. Fun with Strings. Writing a Simple Factorial Program. (Python 2). Stepping Through the Factorial Program. Flowchart for the Factorial Program. Python 3 Not Backwards Compatible with Python 2. Defining a Factorial Function. Diagramming What Happens with a Function Call. Recursive Factorial Function. Comparing Iterative and Recursive Factorial Functions. Exercise - Write a Fibonacci Function. Iterative Fibonacci Function Example. Stepping Through Iterative Fibonacci Function. Recursive Fibonacci Example. Stepping Through Recursive Fibonacci Function. Exercise - Write a Sorting Function. Insertion Sort Algorithm. Insertion Sort in Python. Stepping Through Insertion Sort Function. Simpler Insertion Sort Function.

In this course, you will learn how to formalize information and reason systematically to produce logical conclusions. We will also examine logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.

Examines key computational abstraction levels below modern high-level languages. From Java/C to assembly programming, to basic processor and system organization.

In this class you will learn how to debug programs systematically, how to automate the debugging process and build several automated debugging tools in Python.

In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.

GMAT: Data Sufficiency 1. GMAT: Data Sufficiency 2. GMAT: Data Sufficiency 3. GMAT: Data Sufficiency 4. GMAT: Data Sufficiency 5. GMAT: Data Sufficiency 6. GMAT: Data Sufficiency 7. GMAT: Data Sufficiency 8. GMAT: Data Sufficiency 9. GMAT: Data Sufficiency 10. GMAT: Data Sufficiency 11. GMAT: Data Sufficiency 12. GMAT: Data Sufficiency 13. GMAT: Data Sufficiency 14. GMAT: Data Sufficiency 15. GMAT: Data Sufficiency 16. GMAT: Data Sufficiency 17. GMAT: Data Sufficiency 18. GMAT: Data Sufficiency 19. GMAT: Data Sufficiency 20. GMAT: Data Sufficiency 21. GMAT Data Sufficiency 21 (correction). GMAT: Data Sufficiency 22. GMAT: Data Sufficiency 23. GMAT: Data Sufficiency 24. GMAT: Data Sufficiency 25. GMAT: Data Sufficiency 26. GMAT: Data Sufficiency 27. GMAT: Data Sufficiency 28. GMAT: Data Sufficiency 29. GMAT: Data Sufficiency 30. GMAT: Data Sufficiency 31. GMAT: Data Sufficiency 32. GMAT: Data Sufficiency 33. GMAT: Data Sufficiency 34. GMAT: Data Sufficiency 35. GMAT: Data Sufficiency 36. GMAT: Data Sufficiency 37. GMAT: Data Sufficiency 38. GMAT: Data Sufficiency 39. GMAT Data Sufficiency 40. GMAT Data Sufficiency 41.

Ever played the Kevin Bacon game? This class will show you how it works by giving you an introduction to the design and analysis of algorithms, enabling you to discover how individuals are connected.

Learn about General Game Playing (GGP) and develop GGP programs capable of competing against humans and other programs in GGP competitions .

This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. Part I covers generating functions and real asymptotics and then introduces the symbolic method in the context of applications in the analysis of algorithms and basic structures such as permutations, trees, strings, words, and mappings.

Try to picture yourself sitting down with your computer, ready to start developing a fully functional web application for the first time, available online for millions to use. “Where should I even begin? How long is this going to take me? Am I making any mistakes along the way?” The questions may leave you with an uneasy feeling that you will learn many lessons the hard way. In this intermediate course, Steve Huffman will teach you everything he wished he knew when he started building Reddit and, more recently, Hipmunk, as a lead engineer. Starting from the basics of how the web works, this course will walk you through core web development concepts such as how internet and browsers fit together, form validations, databases, APIs, integrating with other websites, scaling issues, and more; all of which form part of the knowledge it takes to build a web application of your own.

This course is about learning the fundamental computing skills necessary for effective data analysis. You will learn to program in R and to use R for reading data, writing functions, making informative graphs, and applying modern statistical methods.

This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.

In this course, we will study the concepts and algorithms behind some of the remarkable successes of computer vision - capabilities such as face detection, handwritten digit recognition, reconstructing three-dimensional models of cities and more.

Learn critical concepts and practical methods to support research data planning, collection, storage and dissemination.

In this course, you will learn the fundamental computer science principles that power today’s apps. You will also create your own Android app using Java and standard software development tools.

In this course, you will learn about software defined networking and how it is changing the way communications networks are managed, maintained, and secured.

Learn the fundamentals of parallel computing with the GPU and the CUDA programming environment! In this class, you'll learn about parallel programming by coding a series of image processing algorithms, such as you might find in Photoshop or Instagram. You'll be able to program and run your assignments on high-end GPUs, even if you don't own one yourself. **Why It’s Important to Think Parallel** [Third Pillar of Science][1] Learn how scientific discovery can be accelerated by combining theory and experimentation with computing to fight cancer, prevent heart attacks, and spur new advances in robotic surgery. [1]: http://www.youtube.com/watch?v=3DbAB2ChDBw

The Internet is a computer network that millions of people use every day. Understand the design strategies used to solve computer networking problems while you learn how the Internet works.

The course aims to provide a foundation in artificial intelligence techniques for planning, with an overview of the wide spectrum of different problems and approaches, including their underlying theory and their applications.