MS Data Science at Saint Peter's University

The Master’s in Data Science (Professional Hybrid) prepares professionals for Data Science roles in all industries. It is a rapidly growing employment sector globally. Job opportunities for Data Scientists and Advanced Analysts are predicted to grow by 28% between 2015-2020, with Finance and Insurance, Professional Services, and IT leading the demand. The Quant Crunch report emphasizes the need for these specialized skills and the continued growth in demand for qualified Data Scientists.

Degree Course Requirements - 36 credit hours

DS-510. Introduction to Data Science. 3 Credits.
DS-520. Data Analysis and Decision Modeling. 3 Credits.
DS-650. Data Law, Ethics and Business Intelligence. 3 Credits.
DS-542. Python in Data Science. 3 Credits.
DS-597. Applied Research Experience. 0 Credits.
DS-598. Applied Work Experience and Curricular Practical Training. 0 Credits.
DS-660. Business Analytics. 3 Credits.
DS-600. Data Mining. 3 Credits.
DS-610. Big Data Analytics. 3 Credits.
DS-640. Predictive Analytics and Financial Modeling. 3 Credits.
DS-620. Data Visualization. 3 Credits.
DS-630. Machine Learning. 3 Credits.
DS-680. Marketing Analytics and Operations Research. 3 Credits.
DS-670. Capstone: Big Data and Business Analytics. 3 Credits.

For a complete description of the above requirements, please go to the Course Catalog.

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