Applied Econometrics and Machine Learning Graduate Microcredential
This graduate microcredential combines competency-based and traditional learning objectives to provide students with practical skills in applied econometrics and machine learning. The program equips participants with the ability to apply econometric methods to analyze economic data, implement machine learning techniques to solve real-world problems, integrate econometric and machine learning approaches for predictive modeling, and develop data-driven decision-making capabilities. The competency conferred enables graduates to bridge technical implementation with business and policy applications in data science, economic analysis, policy evaluation, and business intelligence.
Program Type
Graduate Microcredential
Program Format
On Campus
Credits and Courses
| Code | Title | Credits |
|---|---|---|
| Required Courses | ||
| ECON 703 | Econometrics | 4 |
| Electives | ||
| Choose one of the following: | 3 | |
| ECON 734 | Econometrics and Machine Learning Methods | |
| COMPSCI 711 | Introduction to Machine Learning | |
| COMPSCI 715 | Programming for Machine Learning | |
| Total Credits | 7 | |
Admission Requirements
Application Deadlines
Application deadlines vary by program, please review the application deadline chart for specific programs. Other important dates and deadlines can be found by using the One Stop calendars.
Admission
Admission eligibility is as follows:
- UWM students already enrolled in another degree or certificate program: Graduate-level standing required. Pre-program assessment and preparation materials will be provided to ensure readiness for quantitative coursework.
- Non-degree or special students enrolling in credit-bearing microcredentials: Graduate-level educational attainment or equivalent professional experience in quantitative fields. Pre-program assessment to ensure readiness for graduate-level econometrics and machine learning coursework.