DATA 201 - Introduction to Data Science

Credits: (3)
Prerequisite(s): CSCI 140 or CSCI 141 or DATA 141
This course will focus research design in the context of data, providing an overview of different modeling approaches, their differences, and the context(s) in which each might be most (or least) appropriate to apply. Throughout the course, students will be introduced to a variety of supervised and unsupervised machine learning techniques including methods for regression, classification, and clustering. By the end of the course, students are not expected to be an expert on any particular technique, but should exhibit a solid high-level understanding of the goals of each method and be able to determine when a particular approach would be more or less suitable to a real-world problem.
Formerly: DATA 146