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Apr 25, 2024
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2016-2017 Graduate Academic Catalogue [ARCHIVED CATALOG]
Data Science, M.S.
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Learning Aims
- Students will understand the underlying principles of data science and be able to keep up with this expanding field.
- Students will be proficient in analyzing complex data from diverse sources by discovering key relationships within the data.
- Students will be able to model data using machine learning techniques.
- Students will be able to model data using statistical models.
- Students will be able to predict future outcomes that can be used to advise decision makers on their course of action.
- Students will be knowledgeable of general ethical principles, how these principles apply to data science, and the social context of data science.
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Prerequisites for the Program
Students are expected to have taken university-level calculus and at least one other math course, and to have had an introduction to computer science/programming course. The programming prerequisite can be satisfied by taking an online programming course such as Code Academy's Python course and then passing a proficiency exam.
Degree Requirements
The degree consists of 31 graduate credit hours, as follows:
Preparatory Course
The preparatory must be taken, unless waived based on previous college experience. This course does not count toward the 31 required credit hours.
Electives
Choose one elective from computer science, one elective from from statistics, and a third elective from computer science, statistics, or one of the approved graduate business courses (GB) offered by the Sellinger School of Business and Management:
Computer Science Electives
Program of Study
The program is designed around a set of four core courses consisting of CS 703 , ST 710 , GB 730 , and GB 851 . Depth in computing and statistics is achieved in CS 737 and ST 765 . The program concludes with a year-long data science project where students practice the skills they have acquired through their course work in a real-world project, working with a client who has a data need.
Spring Term
- DS 796 - Data Science Project
- Computer Science Elective or
- Statistics Elective
- Computer Science Elective or
- Statistics Elective or
- Business Elective
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