Master's of Data Science Curriculum
The MS in Data Science is 33 credits. Students work with their advisor to create a course plan that includes all required courses and a selection of electives to fulfill the 33 credits.
| Term 1 | Term 2 | Term 3 |
| Applied Statistics for Research(3 cr) | Data Management (3 cr) | Elective (3 cr) |
| Data Visualization (3 cr) | Machine Learning for DS (3 cr) | Elective (3 cr) |
| DS Foundations (3 cr) | Elective (3 cr) | Elective (3 cr) |
| Capstone (3 cr) | Capstone 2 (3 cr) | |
| 9 credits | 12 credits | 12 credits |
| Term 1 | Term 2 | Term 3 |
| Data Visualization (3 cr) | Data Management (3 cr) | Elective (3 cr) |
| DS Foundations (3 cr) | Machine Learning for DS (3 cr) | Elective (3 cr) |
| 6 credits | 6 credits | 6 credits |
Second Year
| Term 4 | Term 5 | Term 6 |
| Applied Statistics for Research (3cr) | Elective (3 cr) | Elective (3 cr) |
| Capstone (3 cr) | Capstone (3 cr) | |
| 3 credits | 6 credits | 6 credits |
*Electives may include subjects such as Behavior Analytics, Digital Marketing, Strategic Financial Decision Making, and Risk Management.