CS 427 Data Science

Prerequisites: MATH 213 or MATH 112 or PSY 211 or ECMG 212, and Level III Mathematics Placement, and CS 200 or CS 219; or Permission of Instructor

This course provides an overview of Data Science, covering a broad selection of challenges and methodologies for working with big data. Topics to be covered include data collection, integration, management, modeling, analysis, visualization, prediction, and informed decision making. Students work on hands-on projects and case studies using real data sets from a variety of domains including science, business, engineering, social sciences, and life sciences.

Credits

3.0

Cross Listed Courses

Double-numbered course; offered with graduate-level CS 527

Offered

Spring Semester