MATH 424: Probability and Computing

Course Description

Credits 3.
3 Lecture Hours.Applications of modern probability in data science, with an emphasis on randomization and the role of probabilistic techniques in computing; discrete random variables and expectation; deviation inequalities and applications to randomized algorithms; probabilistic methods and satisfiability; Monte Carlo method; sample complexity; combinatorial dimension.Prerequisites:MATH 304,MATH 309,MATH 311, orMATH 323;MATH 411orSTAT 414.Cross Listing:STAT 424/MATH 424.