Algorithms

3 Credits · Level: Graduate, Undergraduate

This introductory graduate course explores the design and analysis of efficient algorithms. Topics covered include divide-and-conquer, greedy algorithms, and dynamic programming as well as more advanced topics like amortization, randomization, linear programming, memory-efficient algorithms, online algorithms, and approximation algorithms. Specific problem domains are subject to change but may include string algorithms, computational geometry, graph algorithms, combinatorial optimization, number theory, and computational sciences. Although there is some limited overlap of material, this course is not a replacement for an undergraduate algorithms course and hence assumes some basic understanding of algorithm analysis and discrete mathematics.