Data Science Minor

The Data Science minor introduces students to computational-based applications of traditional data analysis methods and current trends in machine learning. The minor is designed to encourage students from a wide range of disciplines to explore the use of data science within their main field of study.

Coordinator: Xuemei Chen

Requirements for a Minor in Data Science

STT 215 - Introduction to Statistics or
PSY 225 - Introductory Statistics for the Behavioral Sciences or
BAN 280 - Statistical Analysis for Business and Economics or
STT 301 - Probability and Statistics
or other approved statistics course
MAT 151 - Basic Calculus with Applications I or
MAT 161 - Calculus with Analytical Geometry I
STT 305 - Statistical Programming or
DSC 303 - R for Data Science or
STT 303 - R for Data Science or
EGN 340 - Matlab for Engineering Analysis
CSC 131 - Introduction to Computer Science (Python)
DSC 301 - Introduction to Machine Learning or
CSC 322 - Data and Machine Learning
DSC 302 - Foundations of Data Science

Total Credit Hours: 19-21

Additional Information

An overall quality point average of “C” (2.00) or better is required for all courses counted toward the minor.