Course schedule for the Analytics and Modeling Graduate Certificate Program, Northwestern University School of Professional Studies - Northwestern School of Professional Studies

Course Schedule

MSDS 411-DL : Unsupervised Learning Methods

Description

This course introduces traditional and modern methods of unsupervised learning. Students see how to represent relationships among many continuous variables using principal components and factor analysis. They identify groups of individuals and groups of variables with cluster analysis and block clustering. They explore relationships among categorical variables with log-linear models and association rules. They visualize multivariate data with lattice displays, multidimensional scaling, and t-distributed stochastic neighbor embedding. And they detect anomalies using autoencoders and probabilistic deep learning. This is a project-based course with extensive programming assignments.

This is a required course for the Analytics and Modeling specialization.

Prerequisites: MSDS 400-DL Math for Modelers and MSDS 401-DL Applied Statistics with R