Graduate
Degree Programs
Master of Data Science
The M.S. in Data Science (MSDS) is a two-year program offering multidisciplinary coursework in computer science, information science, informatics, statistics, engineering, and other disciplines. It prepares students to pursue a data science related career or admission to a Ph.D. program. In addition, MSDS students may select to specialize in the Computational and Analytical Data Science track.
Curriculum
Students are required to complete 30 credit hours of graduate-level coursework for this degree. Individual program choices will vary. Students pursuing the program will develop expertise in four areas (15 credit hours):
Statistics
Select one course from the following:
- SPEA-V 506 Statitical Analysis for Effective Decision-making
- STAT-S 520 Introduction to Statistics
- Higher level Statistics course may be taken with approval
Machine Learning, Data Mining, Text Mining
Select two courses from the following:
- CSCI-B 505 Applied Algorithms
- CSCI-B 551 Elements of Artificial Intelligence
- CSCI-B 555 Machine Learning
- CSCI-B 565 Data Mining
- CSCI-B 657 Computer Vision
- ILS-Z 534 Search
- INFO-I 526/CSCI-P 556 Applied Machine Learning
- INFO-I 590 Topic: Applied Data Mining
- INFO-I 606 Network Science
Data Engineering and Stewardship
Select one course from the following:
- ENGR-E 516 Engineering Cloud Computing
- ENGR-E 517 High Performance Computing
- INFO-I 523 Big Data Applications and Analytics
- INFO-I 524 Big Data Software and Projects
- INFO-I 535/CSCI-B 669 Management, Access, and Use of Big and Complex Data
Visualization and Storytelling
Select one course from the following:
- ENGR-E 583/ILS-Z 637 Information Visualization
- ENGR-E 584 Scientific Visualization
- INFO-I 590 Topic: Data Visualization
- INFO-I 590 Topic: Data and Society
The remaining 15 credit hours can be selected from courses above or additional data science-related course offerings. In consultation with a Data Science faculty advisor, students may choose to pursue an independent study or relevant internship opportunity that blends the learning in data science to a major project or a custom specialization. Be creative in your course strategies.
MS in Data Science - Computational and Analytical Track
Students with a strong computer science background wishing to drive deeper into the mechanics of data science methodologies may wish to pursue a more rigorous curriculum. For those pursuing the Computational and Analytics (C&A) track, students must pursue more technical and theoretical coursework in four areas (15 credit hours):
Data Systems Foundation
Required
- CSCI-B 561 Advanced Database Concepts
Algorithmic Foundation
Select one course from the following:
- CSCI-B 503 Algorithms Design and Analysis
- CSCI-B 505 Applied Algorithms
Data Analytics Foundation
Required
- STAT-S 520 Introduction to Statistics
Select one course from the following:
- CSCI-B 555 Machine Learning
- CSCI-B 565 Data Mining
Big Data Infrastructure
Select one course from the following:
- INFO-I 535/CSCI-B 669 Management, Access and Use of Big and Complex Data
- ENGR-E 516 Engineering Cloud Computing
The remaining 15 credit hours can be selected from a wide range of data science-related course offerings. A course in data ethics or a major project is highly encouraged. Students can be advised on their individual study plans with the assistance of a Computational & Analytical faculty advisor.