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Texas A&M University

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.


This course is not taught in Spring 2024.