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Jan 15, 2025
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2023-2024 Graduate & Professional Studies Catalog [Archived Catalog]
Master of Data Science
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Return to: Academic Programs
This online professional master’s degree builds upon strengths that span the School’s three departments, providing broad perspectives on topics related to the collection, management, processing, and stewardship of data; data-driven problem-solving and information ethics; and the selection, application, and evaluation of various approaches to predictive modeling and machine learning. This curriculum emphasizes workforce readiness, with a focus on real-world, data-oriented problem solving and portfolio-building projects throughout. To reach a broad audience, this program is offered via an online, self-paced, asynchronous modality to increase access to and completion of the degree by working professionals. Additionally, this degree builds upon the School’s Applied Data-Driven Methods Graduate Certificate , which has no STEM prerequisites for admission nor assumption of programming experience to target a diverse population of adult learners from many disciplinary backgrounds.
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Admissions Requirements
To be considered for admission to this Master’s program, students are expected to meet the following requirements:
- Required: Have obtained a Bachelor’s degree with a B average (a grade point average of 3.00 on a 4.00 scale) or better in the total undergraduate program.
- Recommended: Completed an introductory mathematics or statistics course with a grade of C or higher. Example courses at the University of Pittsburgh include INFSCI 2020 - MATHEMATICAL FOUNDATIONS FOR INFORMATION SCIENCE which introduces the primary mathematical foundations underlying principles of information science, particularly the concepts, representations, and functions associated with areas such as data mining, information retrieval, machine learning, cloud computing, and network science.
No prior programming experience is required for admission to this Master’s program.
Degree Requirements
This is an online professional master’s degree requiring 30 credits of coursework completed with a minimum B grade or higher. The distribution of credits is outlined below.
Core Courses
Students are required to complete the following core courses.
Electives
Students must complete three electives. The list below is a sampling of electives offered; More electives will be developed as the program grows.
- CMPINF 2211 - FOUNDATIONS OF CLOUD COMPUTING FOR DATA SCIENCE PROFESSIONALS
- CMPINF 2221 - APPLIED BAYESIAN DATA ANALYSIS
- CMPINF 2222 - APPLIED DEEP LEARNING
- CMPINF 2223 - TEXT AS DATA
Capstone
The Master’s of Data Science culminates in a required capstone. Students will enroll in a capstone course, working in teams on projects that address inquiries from the point of data ingestion to results explanation.
- CMPINF XXXX - CASE STUDIES IN DATA SCIENCE (under development)
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