Catalog Course Description

This connector will cover introductory topics in the mathematics of data science, focusing on discrete probability and linear algebra and the connections between them that are useful in modern theory and practice. We will focus on matrices and graphs as popular mathematical structures with which to model data. For examples, as models for term-document corpora, high-dimensional regression problems, ranking/classification of web data, adjacency properties of social network data, etc.

Fall Term

2 hours of Instructor presentation of course materials per week and 4 hours of Outside Work Hours per week.

Spring Term

2 hours of Instructor presentation of course materials per week and 4 hours of Outside Work Hours per week.