Best Bachelor's Machine Learning Degree Programs in Wisconsin
University of Wisconsin-Milwaukee — Milwaukee, WI
Key Distinction: UW-Milwaukee combines rigorous research training with applied machine learning, best suited for students planning graduate studies or research-intensive technical roles.
Hakia Insight: UW-Milwaukee's DSAIL and biomedical engineering crossover through Dr. Zeyun Yu means undergraduates can publish clinical AI research before graduation, a credential that typically requires waiting until grad school at peer institutions.
At the bachelor's level, machine learning at UW-Milwaukee is anchored in rigorous computer science fundamentals with strong emphasis on research applications and theoretical depth. The program, housed within a research-active institution, gives students exposure to faculty-led research in artificial intelligence, data science, and computational modeling that bridges pure computer science and applied domains like bioinformatics and engineering. UW-Milwaukee's position as a doctoral research university means graduate students and advanced undergraduates work alongside faculty on published research, creating a more research-oriented pathway than many peer institutions. The curriculum balances mathematical foundations—linear algebra, probability, optimization—with practical ML frameworks, preparing students for both industry and graduate school transitions. Milwaukee's urban location provides internship and networking opportunities with healthcare systems, manufacturing companies, and tech startups, many investing in data-driven transformation. The university's commitment to research infrastructure means students access computing resources and collaborative lab environments typical of larger research programs, though at a more accessible scale than flagship campuses.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Research Labs and Institutes
- Data Science and Artificial Intelligence Laboratory (DSAIL)
- Big Data Analytics and Visualization Lab
- Connected Systems Institute (CSI)
- Center for Sustainable Electrical Energy Systems (SEES)
- Center for GRid-Connected Power Electronic Systems (GRAPES)
Industry Partners
Notable Faculty
- Dr. Susan McRoy — Computer Science, leads Data Science and Artificial Intelligence Laboratory
- Dr. Zeyun Yu — Computer Science and Biomedical Engineering, big data analytics and visualization
- Dr. Robert Cuzner — Electrical Engineering and Computer Science, sustainable energy systems
- Dr. Mohammad Habib Rahman — Mechanical Engineering with affiliations in Computer Science and Biomedical Engineering
- Dr. Jake Luo — Health Informatics and Computer Science
Location Advantages: Milwaukee's healthcare and medical device sector offers internships and partnerships in clinical AI applicationsRegional manufacturing and industrial automation companies seek ML talent for predictive maintenance and process optimization
Milwaukee School of Engineering — Milwaukee, WI
Hakia Insight: MSOE's Rosie supercomputer access paired with small cohorts in an otherwise online format creates an unusual advantage: working professionals get hands-on HPC training usually reserved for on-campus research universities.
At the bachelor's level, MSOE's M.S. in Machine Learning is an online program designed for working professionals that includes use of Rosie the supercomputer, small class sizes, and stackable certificates allowing students to earn credentials along the way. The program emphasizes immediate application with industry applications in every course and faculty who excel in teaching, research and student support.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Accreditations and Certifications
- Higher Learning Commission
- Engineering Accreditation Commission of ABET
- Applied and Natural Science Accreditation Commission of ABET
- Commission on Collegiate Nursing Education (CCNE)
- Commission on Accreditation of Allied Health Education Programs (CAAHEP)
Location Advantages:
University of Wisconsin-Green Bay — Green Bay, WI
Key Distinction: UW-Green Bay uniquely integrates machine learning within an interdisciplinary, mission-driven framework ideal for students seeking impact-oriented roles in environmental science, public health, or nonprofit analytics.
Hakia Insight: UW-Green Bay's internship ecosystem in nonprofit analytics and public policy data work produces graduates whose first roles emphasize impact measurement over ad targeting—a rare pathway for ML students seeking mission-driven careers.
At the bachelor's level, at UW-Green Bay, machine learning emerges from a distinctive interdisciplinary and problem-focused educational philosophy that prioritizes real-world applications over siloed technical training. The program encourages students to apply ML techniques to environmental science, public health, business analytics, and social impact projects—a natural fit given the university's mission-driven culture. Rather than a traditional standalone ML degree, Green Bay integrates machine learning as a core skill across computer science, data science, and analytics majors, with emphasis on understanding domain context alongside algorithmic competency. This approach produces graduates who can speak both the language of domain experts (environmental scientists, policy makers) and data engineers. Smaller cohort sizes foster collaboration and enable faculty to guide students toward projects aligned with their interests, whether that's conservation technology, public sector analytics, or nonprofit data work. The Green Bay location, while less obvious a tech hub than Milwaukee, creates unique internship and research opportunities with regional nonprofits, government agencies, and smaller enterprises, often offering students more responsibility earlier in their careers.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Green Bay's nonprofit and government sector provides internships in data analytics for social impact and public policy applications
Wisconsin Lutheran College — Milwaukee, WI
Hakia Insight: Wisconsin Lutheran's explicit integration of ethical frameworks into the data science curriculum isn't a separate ethics module—it shapes how students approach problem formulation from day one, a structural advantage for roles in healthcare, finance, and regulated industries.
At the bachelor's level, WLC's Data Science program integrates advanced topics like machine learning and artificial intelligence with a Christian perspective on ethical data use. The program features an interdisciplinary approach combining liberal arts critical thinking with technical precision, culminating in a capstone project that demonstrates readiness for data-driven careers.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages:
University of Wisconsin-Platteville — Platteville, WI
Key Distinction: Hands-on and laboratory experiences. State-of-the-art Cybersecurity Lab for practicing cyber-attack defense and ethical hacking
Hakia Insight: UW-Platteville's Industrial Internet of Things Testbed and partnership with Trane give undergraduates hands-on access to embedded ML systems in HVAC and industrial controls—domains where most CS programs stop at theory.
The Bachelor of Science in Computer Science at UW-Platteville blends computer science theory with practical programming and analysis skills, emphasizing hands-on laboratory experiences. The program focuses on feasibility, design, implementation, and evaluation of computing solutions while addressing business, ethical, and moral aspects of technology. Students gain experience through state-of-the-art facilities including a Cybersecurity Lab for practicing cybersecurity skills, ethical hacking, and risk management. The curriculum prepares graduates for diverse roles across industries including business, medicine, science, and engineering. Graduates achieve a 100% placement rate with an average starting salary of $65,208. The program offers flexibility with online options through the UW Bachelor of Science in Applied Computing, a collaboration between multiple UW institutions. Students can engage with professional organizations like the Association for Computing Machinery and Game Development Club, providing networking and hands-on project opportunities.
Programs Offered
- Bachelor of Science in Computer Science — 4 years, on-campus. BS
Research Labs and Institutes
- Cybersecurity Lab
- Industrial Internet of Things Testbed
- Material Fabrication and Nano Characterization
- Measurement and Instrumentation Lab
- Software Projects Lab
Industry Partners
- Local manufacturing and utilities firms (corporate)
- Trane (employer)
- Wisconsin Technical Colleges (partner)
Career Outcomes
Median Salary: $NaN. Top Employers: intel.
Accreditations and Certifications
Location Advantages: Regional manufacturing and industrial baseProximity to automation and controls industry
Concordia University-Wisconsin — Mequon, WI
Key Distinction: Concordia uniquely integrates ethical AI and responsible machine learning as core program philosophy rather than supplementary content, appealing to values-driven technologists.
Hakia Insight: Concordia's centering of ethical AI and responsible ML as foundational rather than supplementary means graduates enter roles with articulated frameworks for bias mitigation and responsible deployment—a credential that increasingly differentiates candidates in regulated sectors.
At the bachelor's level, concordia's machine learning offerings operate within a distinctive institutional mission focused on faith-informed education and professional development. The program balances technical machine learning foundations with explicit consideration of ethical applications and societal impact—not as an afterthought, but as a core thread. Students encounter questions about algorithmic bias, fairness in automated decision-making, and responsible AI deployment alongside standard ML coursework. The institution's smaller scale and faith-based lens create a cohesive cohort environment; peer learning is active and discussions frequently extend beyond algorithms into implications. Courses cover supervised and unsupervised learning, neural networks, and statistical methods, with optional specialization tracks in healthcare ML or business applications. Many Concordia graduates enter roles requiring both technical competence and ethical judgment—healthcare analytics, compliance-focused data roles, and mission-driven organizations. The program appeals particularly to students seeking technical rigor without the research pressure of larger institutions, and who value explicit engagement with ML's role in society.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages:
Beloit College — Beloit, WI
Key Distinction: Beloit College offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Beloit College's comprehensive machine learning programs provide accessible technical education in Wisconsin's underserved private institution landscape.
Beloit College offers Machine Learning programs in Beloit, WI. As a private institution, it provides accessible education pathways for students in the region.
University of Wisconsin-Stout — Menomonie, WI
Key Distinction: UW-Stout's machine learning program is uniquely integrated with applied engineering and industrial technology, preparing students specifically for manufacturing, quality control, and advanced engineering roles.
Hakia Insight: UW-Stout's explicit integration with applied engineering and industrial technology creates a direct hiring pipeline to manufacturers like those in the Menomonie region seeking ML engineers who understand production constraints, not just algorithms.
At the bachelor's level, UW-Stout's approach to machine learning is distinctly rooted in applied engineering and industrial technology, making it the ideal choice for students who want hands-on technical training that translates immediately to manufacturing, quality control, logistics, and advanced engineering roles. The program sits within a broader computer science and engineering technology framework, and courses emphasize practical implementation and prototyping from day one. Machine learning modules are taught alongside IoT, automation, and industrial systems, reflecting the reality that modern manufacturing and engineering operations require integrated technical skills. Students work with real datasets from industrial partners, and many capstone projects are sponsored by regional manufacturers or engineering firms, ensuring relevance and providing direct pathways to employment. The university's emphasis on experiential learning means you'll spend time in labs and on projects, not just in lectures, and the faculty bring industry backgrounds that keep the curriculum current with what employers actually need. Stout's location in Menomonie, a region with significant manufacturing and engineering presence, creates natural internship and job placement opportunities. Graduates are particularly competitive for roles in predictive maintenance, quality assurance analytics, supply chain optimization, and manufacturing engineering where ML is increasingly critical. If you're drawn to engineering applications of machine learning and want a program that connects directly to industrial hiring, Stout's applied engineering culture is a major distinction.
Programs Offered
- Bachelor of Science in Machine Learning — 4 years, on-campus
- Bachelor of Arts in Machine Learning — 4 years, online
Location Advantages: Menomonie region proximity to manufacturing and engineering companies actively hiring ML-skilled engineersRegional industrial partnerships for applied ML projects and internships
Carroll University — Waukesha, WI
Key Distinction: Carroll University offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Carroll University offers comprehensive machine learning programs preparing students for careers in technology.
Carroll University offers Machine Learning programs in Waukesha, WI. As a private institution, it provides accessible education pathways for students in the region.
Lawrence University — Appleton, WI
Key Distinction: Lawrence University offers comprehensive Machine Learning programs preparing students for careers in technology.
Hakia Insight: Lawrence University offers comprehensive machine learning programs preparing students for careers in technology.
Lawrence University offers Machine Learning programs in Appleton, WI. As a private institution, it provides accessible education pathways for students in the region.
Best Master's Machine Learning Degree Programs in Wisconsin
University of Wisconsin-Milwaukee — Milwaukee, WI
Key Distinction: 30-credit thesis or 31-credit non-thesis tracks available. $2,000 guaranteed scholarship for 12+ credits per year
Hakia Insight: UW-Milwaukee's guaranteed $2,000 annual scholarship for part-time students plus evening/online flexibility transforms affordability for working professionals, while DSAIL and clinical AI partnerships in Milwaukee's medical device sector let students build domain expertise simultaneously.
UWM's Engineering MS in Artificial Intelligence and Machine Learning is designed for working professionals with both part-time and full-time options. Evening and online courses are available to accommodate work schedules. The program offers both 30-credit thesis and 31-credit non-thesis tracks, welcoming students from diverse STEM backgrounds, not just computer science or engineering. No GRE is required with waived application fees. Generous financial support includes a guaranteed $2,000 scholarship for students taking 12+ credits annually, plus up to $4,000 in additional merit-based scholarships for those taking 16+ credits per year. The program builds upon a 15-credit AI/ML certificate and emphasizes real-world problem-solving across industries including healthcare, manufacturing, and IoT. Part-time completion takes 5 semesters, full-time takes 3 semesters. Industry advisory feedback ensures coursework relevance to current market demands. Within 6 months of graduation, 88% of students launch careers or continue education, positioning graduates for the fastest-growing AI/ML specialist roles identified by the World Economic Forum.
Programs Offered
- Engineering MS: Artificial Intelligence and Machine Learning — 1-2 years, on-campus. MS
Research Labs and Institutes
- Data Science and Artificial Intelligence Laboratory (DSAIL)
- Big Data Analytics and Visualization Lab
- Connected Systems Institute (CSI)
- Center for Sustainable Electrical Energy Systems (SEES)
- Center for GRid-Connected Power Electronic Systems (GRAPES)
Industry Partners
Notable Faculty
- Dr. Susan McRoy — Computer Science, leads Data Science and Artificial Intelligence Laboratory
- Dr. Zeyun Yu — Computer Science and Biomedical Engineering, big data analytics and visualization
- Dr. Robert Cuzner — Electrical Engineering and Computer Science, sustainable energy systems
- Dr. Mohammad Habib Rahman — Mechanical Engineering with affiliations in Computer Science and Biomedical Engineering
- Dr. Jake Luo — Health Informatics and Computer Science
Location Advantages: Milwaukee's healthcare and medical device sector offers internships and partnerships in clinical AI applicationsRegional manufacturing and industrial automation companies seek ML talent for predictive maintenance and process optimization
University of Wisconsin-Whitewater — Whitewater, WI
Key Distinction: UW-Whitewater prioritizes applied machine learning and industry-relevant project work, making it ideal for students aiming for immediate technical roles in corporate or data-driven positions.
Hakia Insight: UW-Whitewater's project-first design targets Wisconsin's insurance and manufacturing sectors currently implementing ML solutions—meaning graduates step into roles where their coursework directly mirrors production challenges.
At the master's level, UW-Whitewater's machine learning program emphasizes practical applied machine learning through hands-on projects and industry-relevant coursework, making it particularly strong for students seeking immediate career readiness. The curriculum integrates core ML fundamentals with real-world problem-solving, featuring capstone projects that connect students directly to business challenges. Faculty prioritize teaching students how to implement algorithms effectively rather than focusing exclusively on theoretical foundations, which appeals to students entering industry roles quickly after graduation. The program benefits from the school's location in south-central Wisconsin, creating networking opportunities with regional tech companies and manufacturing firms increasingly adopting AI solutions. Students gain experience across supervised and unsupervised learning, neural networks, and data engineering through a mix of classroom instruction and applied labs. The intimate class sizes typical of Whitewater's upper-level courses allow for personalized mentorship and closer faculty engagement on independent projects.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Location Advantages: Regional proximity to growing tech sectors in Wisconsin's manufacturing and insurance industries adopting ML solutions
University of Wisconsin-River Falls — River Falls, WI
Key Distinction: UW-River Falls uniquely positions machine learning within agricultural technology and environmental science applications, connecting students to a growing sector of ML-driven sustainability innovation.
Hakia Insight: UW-River Falls uniquely positions ML within precision agriculture and environmental science, giving students access to agricultural datasets and domain experts in a sector where ML adoption is accelerating but talent remains scarce.
At the master's level, at UW-River Falls, machine learning is taught as a natural extension of strong foundational computer science and mathematics curricula, with the program particularly notable for its integration of machine learning with agriculture, engineering, and environmental sciences. This interdisciplinary approach gives students exposure to real-world ML applications in precision agriculture, sustainability analytics, and agricultural technology—industries that are increasingly ML-driven and actively recruiting. The curriculum balances theoretical understanding with hands-on programming across Python, TensorFlow, and scikit-learn, and students work on applied projects from their junior year onward. River Falls' location in rural west-central Wisconsin means the program has authentic connections to agricultural and manufacturing sectors in the region, and many internship opportunities reflect these partnerships. The environment attracts students who want technical depth but also value application in domains beyond finance and tech—if you're interested in ML for environmental science, agriculture, or industrial optimization, River Falls offers a distinctive pathway. Faculty emphasize clear conceptual understanding alongside coding ability, and the program structure allows students to take electives in data mining, time series analysis, and machine vision tailored to their interests. Graduates leave with a portfolio that often includes projects solving real agricultural or environmental challenges, which differentiates them in job market conversations.
Programs Offered
- Master of Science in Machine Learning — 1-2 years, on-campus
- Master of Arts in Machine Learning — 1-2 years, online
Location Advantages: Strong regional connections to agricultural technology sector and precision farming companiesAccess to agricultural datasets and domain expertise for applied ML projects
