Master of Science in Data Analytics
Through a unique and innovative collaboration between the School of Management, the Department of Mathematical Sciences, the Department of Computer Science and the Department of Systems Science and Industrial Engineering, the MS in Data Analytics program is designed to prepare students with diverse backgrounds with balanced business intelligence, leadership, quantitative, and technical skills and abilities. Given the highly quantitative nature of the program, it qualifies as a STEM degree. The MSDA is a 30 credit, 10-month program.
Admission
A bachelor's degree (or its equivalent) from a nationally or regionally accredited college or university with a minimum 3.0 GPA is required. Applicants with a bachelor's or graduate degree in mathematics, statistics or an applied science such as economics, business, management science, computer science, system science or industrial engineering are preferred.
Applicants with at least two years of work experience in a business or industrial setting will be preferred, and some requirements for the program may be substituted by relevant work experience in a related field.
Applicants should provide academic transcripts, two letters of recommendation, a current resume, a
personal statement and GMAT/GRE scores. The GMAT/GRE requirements may be waived based on the applicant's undergraduate degree, GPA, and/or relevant work experience.
Requirements
| Courses | Credits |
| DATA 500 Introduction to Data Analytics | 3 |
| DATA 501 Predictive and Inferential Analytics | 3 |
| DATA 502 Machine Learning and Data Mining | 3 |
| DATA 503 Applied Optimization and Decision Analytics | 3 |
| DATA 504 Database and Large Data Repositories | 3 |
| DATA 580A Communicating and Visualizing Data | 3 |
| DATA 510 Analytics Practicum I | 3 |
| DATA 511 Analytics Practicum II | 3 |
| Elective 1 | 3 |
| Elective 2 | 3 |
Electives
Electives should be selected in consultation with the Program Director and the instructor of the course to ensure adequate preparation. The following is a list of potential electives:
- MKTG 580L. Optimizing Customer Strategy
- SCM 560. Decision Modeling & Risk Analysis
- MATH 535. Statistical Leaming & Data Mining
- MATH 559. Time Series Analysis
- CS 533. Information Retrieval
- SSIE 519. Applied Soft Computing