M.S. in Applied Data Science Program Requirements
The 36 credit hour M.S. in applied data science program offers courses designed for the working professional. The program typically takes two calendar years to complete, although well-prepared students with minimal external obligations may be able to complete it in one calendar year.
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.
Unless otherwise noted, courses are three credits each.
Required Courses – 27 credits
- GDAT 501 – Introduction to Statistics for Data Science
- GDAT 502 – Foundations of Working with Data
- GDAT 511 – Data Mining & Machine Learning
- GDAT 512 – Predictive Modeling I
- GDAT 514 – Databases
- GDAT 515 – Communicating with Data: Visualization and Presentation
- GDAT 613 – Predictive Modeling II
- GDAT 640 – Capstone I
- GDAT 641 – Capstone II
Electives – 9 credits
Choose three courses from below.
- GDAT 531 – Healthcare Analytics
- GDAT 532 – Education Analytics
- GDAT 541 – Applied Modeling
- GDAT 621 – Nonparametric Analysis
- GDAT 622 – Network Analysis
- GDAT 623 – Textual Analysis
- GDAT 624 – Web Analytics
Total: 36 credits
Note: The information here is provided for informational purposes only. For exact requirements as well as course descriptions, visit the Graduate Catalog.