MAT 235 - Introduction to Data Science

4 credit hours - 3 hours of lecture and 2 hours of lab weekly; one term.
Apply standards and practices for collecting, organizing, managing, and exploring data, combining principles and skills from statistics and computer programming with a goal of using these tools to provide information to decision makers. Topics include causality, single and multivariable data manipulation, data visualization and generation, statistical inference, statistical modeling, and machine learning.

Prerequisite(s): A grade of C or better in any college level math course, or CTP 160 - Python , or permission from the Mathematics Assistant Dean. In addition to these course requirements, students must possess proficiency in basic computing tasks, including file storage and management and online communications.