Master of Science in Data Science Curriculum and Course Planning
Students choose one of two specializations: Technical or Business Analytics. The Technical
specialization is designed for students with some mathematics and statistics background
and computer programming experience who have the requisite background to develop machine
learning algorithms and utilize advanced statistical insight.
The Business Analytics specialization is designed for students who have introductory
statistics, and who are interested in business applications of data science such as
marketing or management. The specialization requires two courses in computer science,
two courses in data science, and two courses in statistics followed by electives in
business, computer science, or statistics; and a capstone research project conducted
with a partner in local industry/government/non-profit.
The Technical specialization requires three courses in computer science, two courses
in data science, and two courses in statistics followed by electives in computer science,
statistics, and/or business; and a capstone research project conducted with a partner
in local industry/government/non-profit.
For students beginning in Fall 2021 and thereafter, all courses will be offered 100% online. Depending on the instructor, the course may be offered either synchronously or asynchronously.
Degree Requirements
The degree consists of 34 graduate credit hours (three credits may be waived) as follows:
Required Courses
- CS701 - Introduction to Programming (may be waived)
- CS703 - Programming for Data Science
- CS737 - Machine Learning (only Technical Specialization) (CS703)
- DS730 - Introduction to Data Science
- DS795 - Data Science Project Design (CS703, DS851, ST710)
- DS796 - Data Science Project (DS795)
- DS851 - Business Intelligence and Data Mining (DS730 or permission of the instructor)
- ST710 - Statistical Computing
- ST765 - Linear Statistical Models (ST710)
Computer Science Electives
- CS745 - Multimedia Data Analysis and Mining (CS737, ST710)
- CS766 - Information Retrieval and Natural Language Processing (CS737)
Statistics Electives
- ST767 - Multivariate Analysis (ST710)
- ST775 - Generalized Linear Models and Multilevel Models (ST765)
- ST778 - Time Series Analysis (ST710)
Business Electives
- GB712 - Law, Ethics, and Social Responsibility
- GB735 - Project Management (GB704 or GB705)
- DS736 - Data Visualization for Decision Making (DS730 or permission of the instructor)
- DS739 - Data Management and Database Systems
- GB740 - Digital Marketing and Analytics (only Business Analytics Specialization)
- GB759 - Special Topics in Management Information Systems: Location Analytics (only Business Analytics Specialization) (DS730 or CS703)
For course descriptions, please see the Graduate Academic Catalog.
Program of Study
The program is designed around a set of required courses and electives. 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.
| Required Courses | Electives | |
| Fall | CS701 - Introduction to Programming CS703 - Programming for Data Science DS730 - Introduction to Data Science ST765 - Linear Statistical Models DS795 - Data Science Project Design |
Computer Science Elective |
| Spring | CS737 - Machine Learning (only Technical Specialization) ST710 - Statistical Computing DS796 - Data Science Project |
Computer Science Elective or Statistics Elective or Business Elective |
| Summer | DS851 - Business Intelligence and Data Mining | Statistics Elective |