The Master of Science in Advanced Data Analytics teaches students methods that focus on data management, data visualiza tion, data mining, forecasting, inferential statistics, machine learning, operations research, and statistical modeling. Students will learn to identify, build, select, and fit models to data using relevant computer software.
The program curriculum requires 30 hours, of which 21 hours are core courses and 9 hours are elective courses. The required courses include a capstone course offered in lieu of a master thesis, which will allow students to apply the methods learned in the core and elective courses to a data analytics project using real world data.
Each student will take 7 required graduate courses (21 semester hours) plus 3 graduate Data Analytics electives (9 semester hours) for a total of 30 semester hours.
- BUAD 5603 - Advanced Applied Business Statistics
- BUAD 5633 - Causal Inference Applications in Business Analytics
- BUAD 5643 - Machine Learning Applications in Business I
- ECON 5123 - Regression Model Applications to Data Analytics
- ECON 5143 - Data Modeling and Forecasting
- MIS 5113 - Introduction to Business Analytics
- BUAD 5843 - Data Analytics Capstone
- BUAD 5623 - Model-Based Problem Solving
- BUAD 5743 - Machine Learning Applications in Business II
- FINC 5723 - Financial Data Analytics
- MIS 5603 - Data Visualization
- MIS 5613 - Data Mining and Text Analytics in Business
- Total: 30 hours