# MATH 677 - Mathematical Foundations for Data Science - Spring 2024

** Credits 3. 3 Lecture Hours. **

Linear systems; least squares problems; eigenvalue decomposition; singular value decomposition; Perron–Frobenius theory; dynamic programming; convex optimization; gradient descent; linear programming; semidefinite programming; compressive sensing. **Prerequisites:** MATH 304, MATH 309, MATH 311, MATH 323, or equivalent; admission to master of science in data science or master of science in quantitative finance.

### Sections

**This course is not taught in Spring 2024.**