Analysis of Algorithms

开始时间: 03/04/2016 持续时间: 6 weeks

所在平台: Coursera

课程类别: 数学

大学或机构: Princeton University(普林斯顿大学)

授课老师: Robert Sedgewick

   

课程主页: https://www.coursera.org/course/aofa

Explore 1600+ online courses from top universities. Join Coursera today to learn data science, programming, business strategy, and more.

课程评论: 1 个评论

评论课程        关注课程

课程详情

Analysis of Algorithms aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the scientific analysis of algorithms in computer science and for the study of scientific models in many other disciplines, including probability theory, statistical physics, computational biology and information theory. This course covers recurrence relations, generating functions, asymptotics, and fundamental structures such as trees, permutations, strings, tries, words, and mappings, in the context of applications to the analysis of algorithms.

课程大纲

Lecture  1  Analysis of Algorithms
Lecture  2  Recurrences
Lecture  3  Solving recurrences with GFs
Lecture  4  Asymptotics
Lecture  5  The symbolic method
Lecture  6  Trees
Lecture  7  Permutations
Lecture  8  Strings and Tries
Lecture  9  Words and Mappings

课程评论(1条)

0

都柏林的老菲利普 2014-02-01 12:20 0 票支持; 0 票反对

传统的算法分析方法,可惜现在都没有什么人用了。
书非常好,建议和Concrete Maths一起读

Deep Learning Specialization on Coursera

课程简介

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.

课程标签

算法 算法分析 算法分析入门 算法分析导论 普林斯顿大学 Sedgewick

28人关注该课程

主题相关的课程

Analytic Combinatorics, Part I 关注

Analytic Combinatorics 关注

Analytic Combinatorics, Part II 关注

Computational Methods for Data Analysis 关注

Algorithms, Part I 关注

Algorithms, Part II 关注

Network Analysis in Systems Biology 关注

Passion Driven Statistics 关注

Dynamical Modeling Methods for Systems Biology 关注

Algebra 关注