MAT 3201 - Data Analysis

Credits: 4
Data analysis is the study of the extraction of knowledge from data. This course is an introduction to the mathematical methods behind the scientific techniques developed for extracting information from large data sets. We will explore several fundamental topics in computational data analysis, including basic concepts in probability, Bayes’ rule, central limit theory, linear regression, dimension reduction, gradient descent, principal component analysis, clustering and classification. We will use Python to demonstrate and explore basic concepts, but programming will not be the main focus of the course.
Prerequisite(s) MAT-2218, MAT-2219, and CSC-1106