MATH 3190 - Fundamentals of Data Science

3 Credit(s)

This class will be an introduction to the mathematics and algorithms underlying the analytic techniques of data science. Topics covered will include regression and cross validation, gradient descent, dimension reduction, clustering and classification. The ethical issues of data science will also be discussed. Students will use Python and GitHub throughout this course. (Spring) [Graded (Standard Letter)]

Prerequisite(s): MATH 2140 and (MATH 2170 or MATH 2270) and ANLY 4100 and (CS 1400 or CSIS 1300) - Prerequisite Min. Grade: C
Registration Restriction(s): None