Master of Data Science: Coursera
Collaborative program with the Department of Applied Mathematics
This professional master’s degree program, offered through our partnership with Coursera, consists of 33 credit hours of coursework including six credits awarded for relevant practical industry certificates. The program is designed primarily for those with some skills and experience in computer science, statistics, mathematics, science, or business, and who are interested in preparing for a career as a data science professional in business and industry
Admission
Admission to this program is fully performance-based; any student who successfully completes the admissions sequence of courses listed below for credit will be admitted to the full degree program.
- CS 725: Introduction to Relational Databases
- MATH 764: Linear Regression
- Either
- CS 726: Relational Database Design
- MATH 765: Model Diagnostics and Remedial Measures
Note that CS 725 and 726 count towards credit for CS 425 Database Organization and MATH 764 and 765 count towards credit for MATH 564 Applied Statistics.
Curriculum
| Code | Title | Credit Hours |
|---|---|---|
| CS 425 | Database Organization | 3 |
| MATH 564 | Applied Statistics | 3 |
| CSP 554 | Big Data Technologies | 3 |
| MATH 569 | Statistical Learning | 3 |
| SCI 522 | Public Engagement for Scientists | 3 |
| CSP 571 | Data Preparation and Analysis | 3 |
| MATH 546 | Introduction to Time Series | 3 |
| CS 577 | Deep Learning | 3 |
| MATH 574 | Bayesian Computational Statistics | 3 |
| Capstone Experience | 6 | |
| Total Credit Hours | 33 | |
Capstone experience is 6 credits of approved industry-relevant certificates (normally 3 credits each). The program steering committee will determine a list of approved such certifications and update as needed.
Examples of certifications that may be approved are the Coursera IBM Data Science Professional Certificate, the Google Data Analytics Professional Certificate, and the SAS Advanced Programmer Professional Certificate.
