Program Requirements
M.S. in Applied Data Science
Applicants who wish to be considered for course exemptions will be individually reviewed as part of the application process.
Requirements
The number of credits for each course is designated in parentheses after the course title.
Required Courses – 27 credits
- GDAT 501 – Introduction to Statistics for Data Science (3)
- GDAT 502 – Foundations of Working with Data (3)
- GDAT 511 – Data Mining & Machine Learning (3)
- GDAT 512 – Predictive Modeling I (3)
- GDAT 514 – Databases (3)
- GDAT 515 – Communicating with Data: Visualization and Presentation (3)
- GDAT 613 – Predictive Modeling II (3)
- GDAT 640 – Capstone I (3)
- GDAT 641 – Capstone II (3)
Electives – 9 credits
Choose three courses from below.
- GDAT 531 – Healthcare Analytics (3)
- GDAT 532 – Education Analytics (3)
- GDAT 541 – Applied Modeling (3)
- GDAT 621 – Nonparametric Analysis (3)
- GDAT 622 – Network Analysis (3)
- GDAT 623 – Textual Analysis (3)
- GDAT 624 – Web Analytics (3)
Total: 36 credits