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6.046J Design and Analysis of Algorithms (MIT) 6.046J Design and Analysis of Algorithms (MIT)

Description

Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow, computational geometry, number-theoretic algorithms, polynomial and matrix calculations, caching, and parallel computing. Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow, computational geometry, number-theoretic algorithms, polynomial and matrix calculations, caching, and parallel computing.

Subjects

sorting | sorting | search trees | search trees | heaps | heaps | hashing | hashing | divide and conquer | divide and conquer | dynamic programming | dynamic programming | greedy algorithms | greedy algorithms | amortized analysis | amortized analysis | graph algorithms | graph algorithms | shortest paths | shortest paths

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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6.046J Design and Analysis of Algorithms (MIT) 6.046J Design and Analysis of Algorithms (MIT)

Description

Includes audio/video content: AV lectures. This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography. Includes audio/video content: AV lectures. This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography.

Subjects

algorithm | algorithm | sorting | sorting | search trees | search trees | heaps | heaps | hashing | hashing | divide and conquer | divide and conquer | dynamic programming | dynamic programming | greedy algorithms | greedy algorithms | amortized analysis | amortized analysis | graph algorithms | graph algorithms | shortest paths | shortest paths | network flow | network flow | cryptography | cryptography

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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Algorithms

Description

This course focuses on the fundamentals of computer algorithms, emphasizing methods useful in practice. This free course may be completed online at any time. See course site for detailed overview and learning outcomes. (Computer Science 303)

Subjects

computer science | computer | algorithms | programming | analysis | sorting | dynamic | graph theory | graph algorithms | greedy algorithms | np-completeness | Computer science | I100

License

Attribution 2.0 UK: England & Wales Attribution 2.0 UK: England & Wales http://creativecommons.org/licenses/by/2.0/uk/ http://creativecommons.org/licenses/by/2.0/uk/

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6.046J Design and Analysis of Algorithms (MIT)

Description

This is an intermediate algorithms course with an emphasis on teaching techniques for the design and analysis of efficient algorithms, emphasizing methods of application. Topics include divide-and-conquer, randomization, dynamic programming, greedy algorithms, incremental improvement, complexity, and cryptography.

Subjects

algorithm | sorting | search trees | heaps | hashing | divide and conquer | dynamic programming | greedy algorithms | amortized analysis | graph algorithms | shortest paths | network flow | cryptography

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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6.046J Design and Analysis of Algorithms (MIT)

Description

Techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics include sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; greedy algorithms; amortized analysis; graph algorithms; and shortest paths. Advanced topics may include network flow, computational geometry, number-theoretic algorithms, polynomial and matrix calculations, caching, and parallel computing.

Subjects

sorting | search trees | heaps | hashing | divide and conquer | dynamic programming | greedy algorithms | amortized analysis | graph algorithms | shortest paths

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

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