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MATH 465: Mathematics of Data Science

Important: For the most up-to-date information, refer to the official George Mason Course Catalog

General Information

Credits: 3


Covers mathematical aspects of data science including theory of linear and nonlinear dimension reduction, elements of spectral graph theory, function spaces and regularity in regression, and data-driven dynamics identification and discovery. Computational and analytic assignments are given. Offered by Mathematics. Limited to three attempts.
Recommended Prerequisite: MATH 352 or STAT 350 or STAT 360 or STAT 356
Registration Restrictions:

Required Prerequisites: ((MATH 214C or 214XS) and (MATH 464C or 464XS)).
C Requires minimum grade of C.
XS Requires minimum grade of XS.

Schedule Type: Lecture
This course is graded on the Undergraduate Regular scale.