Master of Science in Data Science
The Master of Science in Data Science is an interdisciplinary, online program designed to integrate computing with statistical methodologies for analysis and interpretation of large datasets. The program focuses on essential analytical and predictive modeling tools to visualize, analyze, and interpret data efficiently from a variety of data acquisition platforms. Our program is geared toward meeting the demand for university graduates with skills needed to manage, analyze, and draw insights from large volumes of data from diverse application domains.
The program is designed for students who hold bachelor of science or bachelor of arts degree and/or professional experience in fields such as statistics, mathematical sciences, computer science, information technology, geographic information science, epidemiology, or quantitative and/or computer programming based field; however, all degree backgrounds will be considered. Students without the requisite background are strongly encouraged to take remedial coursework in elementary statistics, introductory computer programming and advanced math (calculus, linear algebra).
33 credits
Core Coursework (15 Credit Hours)
| DSCI 601 | Introduction to Data Science | 3 |
| DSCI 602 | Statistical Methods for Data Science | 3 |
| DSCI 605 | Data Visualization | 3 |
| CS 617 | Introduction to Programming | 3 |
| CS 654 | Machine Learning and Data Mining | 3 |
| DSCI 692 | Data Science Exit Survey | 0 |
Computational Analytics (6 Credit Hours)
Complete 6 credit hours from the following courses.
| CS 621 | Data Analytics | 3 |
| CS 636 | Modern Database Systems with Applications | 3 |
| DSCI 604 | Data Storage and Management | 3 |
| ICS 625 | Artificial Intelligence and Machine Learning | 3 |
| ICS 664 | Cloud Technologies | 3 |
Statistical Computing and Modeling (6 Credit Hours)
Complete 6 credit hours from the following courses.
| DSCI 612 | Programming with SAS Base for Data Science | 3 |
| or | |
| MATH 610 | Statistical Programming: Base SAS 9 | 3 |
| MATH 624 | Introduction to Statistical Learning | 3 |
| MATH 627 | Generalized Linear Models with Applications | 3 |
| MATH 628 | Computational Methods in Statistics | 3 |
| DSCI 686 | Categorical Data Analysis | 3 |
Applied Research (6 Credit Hours)
Complete 6 credit hours from the following courses.
| DSCI 607 | Data Analytics for Environmental Sciences | 3 |
| DSCI 608 | Data Analytics for Bioinformatics | 3 |
| DSCI 609 | Data Analytics for Social Sciences | 3 |
| DSCI 610 | Data Analytics for Health Sciences | 3 |
| ECON 624 | Econometric Methods and Applications | 3 |
Total Credit Hours: 33