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This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.
http://ocw.mit.edu/OcwWeb/Electrical-Engineering-a
created by video_lectures on 2008-06-19 23:42:23
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Structure and Interpretation of Computer Programs has been MIT's introductory pre-professional computer science subject since 1981. It emphasizes the role of computer languages as vehicles for expressing knowledge and it presents basic principles of abstraction and modularity, together with essential techniques for designing and implementing computer languages.
http://www.swiss.ai.mit.edu/classes/6.001/abelson-
created by video_lectures on 2008-06-19 23:45:45
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Introduction to the use of Artificial Intelligence tools and techniques in industrial and company settings. Topics include: foundations (search, knowledge representation) and tools such as expert systems, natural language interfaces and machine learning techniques.
http://www.cs.washington.edu/education/courses/cse
created by video_lectures on 2008-06-19 22:34:09
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