Curriculum Details
The following table lists the courses for the MS in Data Science Program.
Course List for MS in Data Science
| Code | Course Title | Credits | Prerequisite(s) |
|---|---|---|---|
| Core Requirements (15–21 cr) | |||
| DAS501 | Mathematical Foundation for Data Science* | 3 | None |
| COS501 | Computational Foundation for Data Science* | 3 | None |
| DAS502 | Probability for Data Science | 3 | DAS501, COS501 |
| DAS522 | Exploratory Data Analysis and Visualization | 3 | DAS501, COS501 |
| DAS541 | Data Mining for Business | 3 | DAS501, COS501 |
| COS536 | Applied Machine Learning | 3 | DAS541 |
| DAS548 | Ethics in Computer and Data Science | 3 | None |
| Electives (9–15 cr) Select from the the following: |
|||
| DAS512 | Statistical Inference and Modeling | 3 | DAS502 |
| COS531 | Modern Applied Statistical Learning | 3 | DAS502 |
| STA511 | Advanced Regression Analysis | 3 | DAS501 |
| COS643 | Computer Vision and Natural Language Processing | 3 | COS536 |
| COS541 | Big Data and Data Engineering | 3 | None |
| DAS631 | Generative AI: Foundation and Application | 3 | COS536 |
| STA521 | Design and Analysis of Experiments | 3 | DAS502 |
| STA541 | Survival Analysis | 3 | DAS512 |
| Capstone Project (6 cr) | |||
| DAS761 | Capstone Project for Data Science | 6 | Dept. Approval |
| Total Credits Required for Graduation | 36 | ||
* Can be exempt upon meeting certain criteria and with permission from the department. For each exemption one extra elective needs to be taken to meet the requirement for graduation.