MATH 525 - Mathematics for Data Science

Eigenvalues and eigenvectors, the singular value decomposition, principal components, optimization, and gradient descent.

Credit(s): 3

Repeatable for Credit? No
Disciplinary Perspective(s):
None
Interconnecting Perspective(s):
None
University Graduation Requirement(s):
None

Prerequisite(s): MATH 198 - Analytic Geometry and Calculus I with a grade of “C” or higher, and STAT 190 - Basic Statistics.