Robert Sedgewick

 

 


 

Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton, where he was the founding chair of the Department of Computer Science.


More info: http://www.cs.princeton.edu/~rs/




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May 29th 2017

Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations.

Average: 4.3 (12 votes)
May 15th 2017

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 basic iterable data types, sorting, and searching algorithms.

Average: 7.6 (16 votes)
Jan 9th 2017

This course teaches a calculus that enables precise quantitative predictions of large combinatorial structures. In addition, this course 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.

Average: 9 (2 votes)
Mar 16th 2016

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.

Average: 6.8 (9 votes)