Small Campus, Smart Future: UW-Superior's hands-on approach to AI education
Something important is happening at the University of Wisconsin-Superior: a new online AI Essentials: Strategies for Efficiency & Productivity certificate is live, and an artificial intelligence minor will enroll students starting Fall 2026. The focus is practical, hands-on learning that connects directly to workplace skills. It builds on a strong computer science foundation and a clear promise: timely, meaningful education.
"Employers today in our region expect graduates to be conversant and competent in working with AI integrations across many sectors," said Maria Cuzzo, provost and vice chancellor of Academic Affairs. "By offering both an AI minor through our Mathematics and Computer Science Department and a certificate through the Center for Continuing Education, UW-Superior ensures our graduates are competitive, capable, and confident in AI literacy - making them prime candidates for employment."
Why this matters for educators
AI fluency is now basic literacy. Students need to build models, question outputs, and apply tools with clear guardrails. Programs that tie theory to projects shorten the gap between classroom and job.
Built by passion, powered by math
The program is guided by Josh Stangle, associate professor and academic program manager in the Mathematics and Computer Science Department. "AI is just math at high speed," Stangle said. What keeps him engaged is student energy: "It's really fun to work with students on something they find exciting and relevant. That energy makes everything better."
Learning by doing
Housed in the Mathematics and Computer Science Department, the AI minor puts experimentation first. Students learn how computers find patterns, make predictions, and adapt from data by building real projects.
- Train a computer to play Connect Four and explain why it wins or loses.
- Prototype image recognition and test edge cases for bias.
- Work with smart devices to mirror home and workplace use.
"The AI minor focuses on developing a wide range of AI literacy and practice competencies, so graduates are job-ready," said Cuzzo. "Together with the certificate, it creates an opportunity for students and community members to understand how AI works and how to use it responsibly."
Two on-ramps: minor and certificate
AI minor (launching Fall 2026): Project-based coursework grounded in math and computing. Students learn how models learn, how to evaluate outputs, and how to document decisions.
AI Essentials certificate (online): Built for non-technical, practical use. Complete it for academic credit (IDS 499, three undergraduate credits) or on a non-credit basis. Open to the public for professional development.
- Interactive Zoom workshops with hands-on assignments.
- How to design, test, and refine prompts and workflows for accurate, ethical, context-appropriate results.
- Ethical and legal topics: bias, equity, privacy, accountability, and responsible use.
- Build a personal AI strategy that plugs into your daily workflow for better outcomes.
Graduates of the certificate will leave with a clear picture of how AI works, its main types, and everyday applications at home and at work. You'll learn to use AI as an assistant, a partner, and a co-intelligence tool to improve productivity and problem-solving.
Practical outcomes you can measure
- AI literacy that translates to classrooms, labs, and offices.
- Portfolio projects that demonstrate real use, not just theory.
- Clear ethical framing and risk checks built into workflows.
- Confidence using common tools and evaluating results.
A UW-Superior success story
Before there were AI-specific courses, May 2025 graduate Andrew Laack used his computer science degree to step into a machine learning engineer role. Raised in Waunakee, Wisconsin, he chose UW-Superior for its fully online comprehensive computer science program while working full time as lead software developer for the Wisconsin Department of Corrections.
Laack now works in San Francisco at Imbue as a machine learning engineer and researcher. "I work on systems that validate the completeness and quality of LLM-generated code," he said. "More broadly, the company is building an accessible interface for coordinating AI agents and making coding more approachable for people with limited experience."
Professor Steve Rosenberg saw it coming: "Andrew dug deeply into the material, attended live Zoom sessions and office hours, and asked incisive questions. He explored his passion for AI and machine learning both in coursework and on the job. Imbue was so impressed that after speaking with his references, they made him an offer immediately."
Small college, big vision
Building the AI curriculum has been collaborative and flexible. "We want to teach students how to learn," said Stangle. "If they know how to think through problems, they'll be ready for anything."
What's next
A special topics course in machine learning piloted last fall offered a preview of what's ahead. While the AI minor launches in Fall 2026, students graduating sooner can engage through independent projects. Faculty across programs are mapping AI learning outcomes so students see how AI supports journalism, art, psychology, science, and more.
Future coursework includes Introduction to Python and projects that use both existing AI tools and student-built solutions. Plans also include hands-on work with devices like Raspberry Pi to show how AI powers everyday tech such as home security and voice assistants. The goal is balance. "We're not trying to create the next ChatGPT," Stangle said. "We're helping students use these tools ethically, creatively, and meaningfully - combining technical skills with problem-solving that matters."
For program leaders and faculty: quick wins you can implement now
- Map where AI outcomes fit into existing courses. Start with research methods, writing, data analysis, and media labs.
- Add a low-lift project: prompt a model, test failure cases, document what changed performance.
- Publish a simple AI use policy for classes: what's allowed, what must be cited, and how to report tool use.
- Run a short PD series for staff. See the AI Learning Path for Teachers for classroom-ready ideas.
- Adopt an ethics checklist grounded in known frameworks like the NIST AI Risk Management Framework.
- Partner with local employers to source small, real data or workflow problems students can tackle in a month.
The bottom line
UW-Superior is building AI education that looks like the work your students will do next semester, not a distant theory. Hands-on projects, clear ethics, and flexible paths mean learners can start where they are and move fast with intention.
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