MATH 677

Mathematical Foundations for Data Science

Texas A&M University · UGRD · Fall 2026

1 section

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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; enrolled in MS in Data Science, MS in Quantitative Finance, or MS in Mathematics.

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Class #texas_am-6114Fall 2026UGRD

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