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This minor in data science is primarily for students majoring in computer science and mathematical sciences with a concentration in statistics. The minor consists of a minimum of 19 credits, including the following:
| Course | Title | Hours |
|---|---|---|
| Required courses | ||
| CMSC 256 | Introduction to Data Structures | 4 |
| CMSC 302 | Introduction to Discrete Structures | 3 |
| CMSC 401 | Algorithm Analysis with Advanced Data Structures | 3 |
| CMSC 435 | Introduction to Data Science | 3 |
| STAT 321 | Introduction to Statistical Computing for Data Science | 3 |
| Elective | ||
| Select one course from: | 3 | |
| Applied Statistical Computing Using R | ||
| Nonparametric Statistics | ||
| Industrial Statistics | ||
| Regression | ||
| Introduction to Statistical Data Science | ||
| Time Series | ||
| Total Hours | 19 | |
All courses required for the minor must be completed with a minimum grade of C.