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 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.
Cross Listed Courses
Double-numbered course; offered with graduate-level
CS 527
Offered
Spring Semester