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Nov 27, 2024
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2021-2022 Graduate Catalog [ARCHIVED CATALOG]
Data Science, M.P.S.
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The Master of Professional Studies (MPS) in Data Science program prepares students from a wide range of disciplinary backgrounds for careers in data science. In the core courses, students get a fundamental understanding of data science through classes that highlight machine learning, data analysis and data management. The core courses also introduce students to ethical and legal implications surrounding data science. Beyond the core courses, students take three courses in domain specific pathways developed in collaboration with academic departments across the university. Through these pathways, students utilize the skills and techniques they learned in the core courses within their own field or area of expertise.
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Required Courses (21 Credits)
Pathways (select one pathway)
Advanced Computing and Analytics (Main Campus)
In collaboration with the Department of Computer Science and Electrical Engineering:
Aging Studies (Main Campus and Shady Grove)
In collaboration with the UMBC Erickson School of Aging
Bioinformatics (Shady Grove)
In partnership with Foundation for Advanced Education Services (FAES) at the National Institutes of Health (NIH).
Students can transfer in coursework from FAES at NIH to serve as a nine-credit Bioinformatics pathway within the MPS. See more at professional.umbc.edu/faes.
Cybersecurity (Main Campus and Shady Grove)
In collaboration with the MPS Cybersecurity program.
Data Science Analytics (Main Campus)
In collaboration with the Department of Information Systems
Economics/Econometrics (Main Campus)
In collaboration with the Department of Economics.
Healthcare Analytics (Main Campus)
In collaboration with the MPS Health Information Technology program.
Management Science (Main Campus and Shady Grove)
In collaboration with the College of Engineering and Information Technology.
Policy Analysis (Main Campus)
In collaboration with the Department of Public Policy:
Project Management (Main Campus and Shady Grove)
In collaboration with the College of Engineering and Information Technology
Spatial Analytics (Shady Grove)
In collaboration with the Department of Geography and Environmental Systems.
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