Wisconsin offers two strong graduate options for students who want advanced training in machine learning. The programs take different approaches, which makes the choice between them relatively straightforward.
The Milwaukee School of Engineering (MSOE) offers a dedicated Master of Science in Machine Learning delivered fully online. The University of Wisconsin–Madison offers a campus-based Master of Science in Electrical and Computer Engineering with a Machine Learning and Signal Processing option.
Students can compare the two Wisconsin programs below based on format, curriculum, credits, and career focus.
Wisconsin Machine Learning Master’s Programs at a Glance
| School | Master’s Program | Format | Credits | ML Focus |
|---|---|---|---|---|
| Milwaukee School of Engineering | M.S. in Machine Learning | Online, synchronous | 32 | Applied ML, ML systems, AI, production |
| University of Wisconsin–Madison | M.S. in Electrical and Computer Engineering: Machine Learning and Signal Processing | Campus | 30 | Machine learning, signal processing, mathematical data science |
These programs serve different types of students. MSOE provides a dedicated machine learning degree with an online format aimed in part at working professionals. UW–Madison combines machine learning with electrical engineering, mathematics, statistics, and signal processing in an accelerated campus program.
Milwaukee School of Engineering M.S. in Machine Learning
Location: Milwaukee, Wisconsin
Format: Online, synchronous
Degree: Master of Science in Machine Learning
Credits: 32
The Milwaukee School of Engineering M.S. in Machine Learning is the most direct machine learning master’s option in Wisconsin.
The 32-credit program is fully online, but classes are synchronous rather than self-paced. Students attend live online classes two evenings per week.
The curriculum covers the technical and practical sides of machine learning. Required coursework includes subjects such as Applied Machine Learning, Machine Learning Production Systems, Mathematical Methods for Machine Learning, AI Tools and Paradigms, Microservices and Cloud Computing, and AI Ethics and Governance.
Students also complete a machine learning capstone.
One of MSOE’s distinguishing features is access to Rosie, the university’s high-performance computing system. Students can use these computing resources for machine learning projects and coursework.
MSOE May Be a Good Fit For
- Students who want a degree specifically in machine learning
- Working professionals who need an online program
- Students interested in applied machine learning and ML production systems
- Students who want experience with high-performance computing resources
- Students interested in deploying machine learning models in real-world environments
Learn more about MSOE’s M.S. in Machine Learning.
University of Wisconsin–Madison Machine Learning and Signal Processing M.S.
Location: Madison, Wisconsin
Format: Campus-based
Degree: M.S. in Electrical and Computer Engineering
Option: Machine Learning and Signal Processing
Credits: 30
Typical Length: 12–16 months
The University of Wisconsin–Madison Machine Learning and Signal Processing master’s program provides a different path into machine learning.
Rather than awarding a standalone machine learning degree, UW–Madison offers Machine Learning and Signal Processing as an option within its Master of Science in Electrical and Computer Engineering.
The 30-credit program is accelerated and course-based. Students study machine learning alongside subjects such as probability, statistics, mathematical data science, optimization, and signal processing.
Students can also complete a hands-on project, independent study, or internship as part of the program.
UW–Madison designed the program as a professional master’s degree for students preparing to enter industry. It is delivered face-to-face on the Madison campus and normally takes about 12 to 16 months to complete.
UW–Madison May Be a Good Fit For
- Students who want an accelerated master’s program
- Students interested in both machine learning and signal processing
- Students with strong mathematics, engineering, or computer science backgrounds
- Students who prefer an in-person graduate experience
- Students interested in ML applications involving signals, sensors, communications, imaging, or related engineering systems
Learn more about UW–Madison’s Machine Learning and Signal Processing M.S..
MSOE vs. UW–Madison
The main differences between Wisconsin’s two machine learning master’s programs are format and academic focus.
| If You Want… | Program to Consider |
|---|---|
| A degree specifically titled Machine Learning | MSOE |
| A fully online program | MSOE |
| Live online classes for working professionals | MSOE |
| Applied ML and production systems | MSOE |
| A campus-based program | UW–Madison |
| An accelerated 12–16 month curriculum | UW–Madison |
| Machine learning combined with signal processing | UW–Madison |
| An electrical and computer engineering foundation | UW–Madison |
Neither program is automatically the better choice.
A software engineer who wants to study machine learning while continuing to work may find MSOE’s online format more practical. A student interested in signal processing, mathematical methods, and engineering applications may prefer UW–Madison.
Online Machine Learning Master’s Programs in Wisconsin
MSOE provides the clear online option among the Wisconsin programs covered here.
Its M.S. in Machine Learning is delivered fully online with live synchronous classes. Students typically attend two-hour online class sessions twice each week for each course.
UW–Madison’s Machine Learning and Signal Processing program is a face-to-face program based in Madison.
Students who need a fully online program should therefore look closely at MSOE or compare Wisconsin’s programs with online machine learning master’s programs.
What Will You Study in a Wisconsin Machine Learning Master’s Program?
Both Wisconsin programs teach machine learning, but their curricula reflect different academic goals.
MSOE emphasizes applied machine learning and deployment. Coursework covers machine learning models, AI tools, cloud computing, production systems, mathematical foundations, ethics, and a capstone project.
UW–Madison combines machine learning with signal processing and quantitative engineering. Students build a foundation that can include machine learning, probability, statistics, mathematical data science, optimization, and digital signal processing.
This distinction can matter more than the name of the university.
Students interested in building and deploying ML systems may prefer MSOE’s applied curriculum. Students interested in mathematical and engineering applications of machine learning may prefer UW–Madison’s approach.
Machine Learning Careers in Wisconsin
A master’s degree in machine learning can support careers across software development, data science, engineering, manufacturing, healthcare, and other data-intensive fields.
Common career paths include:
- Machine learning engineer
- AI engineer
- Data scientist
- Applied machine learning scientist
- ML software engineer
- Data engineer
- Computer vision engineer
- Signal processing engineer
Wisconsin’s manufacturing, healthcare, engineering, and technology sectors also create opportunities to apply machine learning outside traditional software companies.
Students should consider the type of work they want to pursue when comparing programs. MSOE places greater emphasis on applied ML systems and deployment, while UW–Madison provides deeper integration with signal processing and electrical and computer engineering.
Choosing a Machine Learning Master’s Program in Wisconsin
Wisconsin does not have a large number of master’s programs dedicated specifically to machine learning, but its two main options cover very different student needs.
Choose MSOE if you want a dedicated machine learning master’s degree, online study, and an applied curriculum focused on building and deploying ML systems.
Consider UW–Madison if you want an accelerated campus program that combines machine learning with signal processing, mathematics, and electrical and computer engineering.
Students who want additional choices can also compare machine learning master’s programs across the United States.