The Master of Science in Data Science program provides students from a variety of backgrounds with a strong technical education in data scientific concepts and tools so that they may create innovative solutions to address societal challenges using data, state-of-the-art analytical methods and computing technology. Graduates from the program will gain proficiency required for positions in research and development within data science and its application in a variety of fields, and have the academic training to pursue doctoral research in or using data science.
Full-time students can complete the 30-credit program in as little as 11 months; part-time students may require up to 3 years. DSCI courses are available in person or online. A program of study must be submitted in compliance with college regulations.
Program Requirements
The program consists of:
| DSCI Core Courses | 21 |
| Approves Electives | 9 |
| Total Credits | 30 |
The seven required DSCI core courses are:
| DSCI 310 - Introduction to Data Science | 3 |
| DSCI 311 - Optimization and Mathematical Foundations for Data Science | 3 |
| DSCI 321 - Algorithms and Software Foundations for Data Science | 3 |
| DSCI 411 - Data Management for Big Data OR DSCI 421 - Accelerated Computing for Machine Learning |
3 |
| DSCI 431 - Introduction to Statistical Modeling | 3 |
| DSCI 441 - Statistical and Machine Learning | 3 |
| DSCI 451 - Ethics in Data Science | 3 |
Approved Electives
In addition to the core requirements, students are required to complete a minimum of 9 credits from a list of approved electives on the program website, at least 6 of which must be at the 400 level, and can optionally include up to six credits of thesis work. At most 3 courses (totaling 9 credits) from other programs can be applied towards the requirements of this program.
Any classes not listed will be considered through discussion with the program chairs.
Click here to view the approved elective courses.
