MS in Data Science - Customized Focus
When you know best: Advance your career with an individualized focus on data science.
University of Connecticut (UConn) MS in Data Science students have the option to work with an advisor to create a customized approach, selecting elective courses (9 credits) that best align with their professional and career goals.
Paired with 18 universally important core data science courses designed to provide a broad spectrum of skills and knowledge, the 9 credits of elective courses enable students to create a truly interdisciplinary program. Students can select 3 courses from a wide array of electives. The MS DS program concludes with a 3-credit applied capstone project.
The 30-credit MS DS degree is an on-campus (Storrs Campus) graduate degree.
To learn more about this option, please contact Dr. Jeremy Teitelbaum, at ms.datascience@uconn.edu.
18 Credits of Core Courses
- STAT 5405 Applied Statistics for Data Science (3 credits)
- STAT 5125 Statistical Computing for Data Science (3 credits)
- CSE 5819 Introduction to Machine Learning (3 credits)
- CSE 5713 Data Mining and Management (3 credits)
- OPIM 5501 Data Visualization and Communication (2 credits)
- EPSY 5641 Research Design and Measurement for Data Science (2 credits)
- ARE 5353 Data Ethics and Equity (2 credits)
9 Credits of Electives
- Elective 1 (3 credits)
- Elective 2 (3 credits)
- Elective 3 (3 credits)
Capstone Project
- GRAD 5800 Applied Capstone in Data Science (3 credits)
Department Contact
Peter Diplock
Peter.Diplock@UConn.edu
UConn’s Master’s in Data Science is an 11-month cohort based full-time in-person program and is eligible for F-1 and J-1 visa sponsorship. Courses are offered on the University of Connecticut’s Storrs, CT USA Campus. This program is eligible for the STEM OPT extension that affords certain F-1 graduate students an opportunity to apply for a 24-month extension of their post-completion optional practical training (OPT). The program does not offer graduate assistantships and scholarships at this time.