This is the preliminary (or launch) version of the 2024-2025 VCU Bulletin. Courses that expose students to cutting-edge content and transformative learning may be added and notification of additional program approvals may be received prior to finalization. General education program content is also subject to change. The final edition and full PDF version will include these updates and will be available in August prior to the beginning of the fall semester.
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.