MATH 316
Math.Foundations of Data Science
Students are introduced to the mathematics behind data sciences. Topics include numerical linear algebra, image compression, regression, least-squares problems, large-scale numerical optimization, among others. Along with the theory, students gain experience by working on examples.
Topics
- numerical linear algebra
- image compression
- regression
- least-squares problems
- large-scale numerical optimization
- among others
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027