Explore a background on convex sets and functions, linear programming, convex programming, and iterative first-order and second-order methods. The equivalent of three lecture hours a week for one semester. Data Science 388J and 395T (Topic: Optimization) may not both be counted. Offered on the letter-grade basis only. Prerequisite: Graduate standing and Data Science 388G.