Data Science Minor

The data science minor is an interdisciplinary program that emphasizes computational-based applications of traditional data analysis methods and current trends in data mining and machine learning. The program is a collaborative effort between departments, the larger academic community and the business community that emphasizes computational-based applications.

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 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
CSC 131 - Introduction to Computer Science (Python)
DSC 301 - Introduction to Machine Learning or
CSC 340 - Scientific Computing
DSC 302 - Foundations of Data Science

Total 19-21 hours

Additional Information

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