MATH 166 - Advanced Mathematical Methods for Data Science

Semester Hours: 3

This course is designed to provide students with an overview of mathematical methods in data science. Topics include constrained and unconstrained optimization, singular value decomposition and principal component analysis, support vector machines, fast Fourier transform and applications. Validation methods for evaluating the performance of these methods will be discussed.

Prerequisite(s)/Course Notes:
MATH 138 , MATH 085  or both MATH 073  and MATH 135A 

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Fall 2025

January 2026

Spring 2026