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This online course (MOOC) explores the basics of Machine Learning.The Stanford course provides a broad introduction to machine learning, datamining, and statistical pattern...

This online course teaches the essential ideas of Computer Science for beginners with no prior experience.

This online video lecture series gives an introduction to Natural Language Understanding as a sub-problem of artificial intelligence.

This course is a continuation of Crypto I and explains the inner workings of public-key systems and cryptographic protocols. Students will learn how to reason about the security...

This online course gives an introduction to algorithms for learners with at least a little programming experience.

This online course covers the basics of R: a free programming language and software environment used for statistical computing and graphics.

This online course explores programming language compilers. It includes aspects such as lexical analysis, parsing, syntax-directed translation, abstract syntax trees, types and...

This course teaches how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their...

This online course discusses the key problems of parameter estimation in both directed and undirected models, as well as the structure learning task for directed models.

This online video lecture series gives an introduction to Computer Science, Internet technology and the basics of computer hardware (CS105 class at Stanford University). The...

This online video lecture series explores various topics of human-computer interaction.

Cryptography is an indispensable tool for protecting information in computer systems. This course explains the inner workings of cryptographic primitives and how to correctly...

This online course explores data structures (heaps, balanced search trees, hash tables, bloom filters), graph primitives (applications of breadth-first and depth-first search,...

This online course explores the theory of automata and languages. It includes finite automata and the languages they can define, deterministic and nondeterministic automata,...

This online course explores greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, optimal...

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

This online course presents both exact and approximate algorithms for different types of inference tasks, and discusses where each could best be applied.

This online video lecture series gives an introduction to Artificial Intelligence (AI).

This online course explores topics such as asymptotic notation, sorting and searching, divide and conquer (master method, integer and matrix multiplication, closest pair), and...