Explore advanced subjects in algorithm design and analysis including algorithmic paradigms, data structures, maximum flow, randomized algorithms, NP-completeness, and approximation algorithms. Three lecture hours a week for one semester. Data Science 388G and Computer Science 388G may not both be counted. Prerequisite: Graduate standing and knowledge of algorithmic paradigms and discrete mathematics.