Courses

CS 174. Combinatorics and Discrete Probability

Description

Catalog Description: (4 units) Permutations, combinations, principle of inclusion and exclusion, generating functions, Ramsey theory. Expectation and variance, Chebychev's inequality, Chernov bounds. Birthday paradox, coupon collector's problem, Markov chains and entropy computations, universal hashing, random number generation, random graphs and probabilistic existence bounds.

Prerequisites: CS 170.

Course objectives: Provide familiarity with basic tools in discrete probability and their applications to the design and analysis of randomized algorithms and data structures. Learn how probabilistic ideas and techniques can lead to more efficient and conceptually simpler algorithms for many problems. Develop an understanding of randomness as a computational resource.

Topics covered:

General Catalog

Undergraduate Student Learning Goals