New Course: AI-Assisted Problem Solving — No Coding Required
This fall, the Department of Computer Science is offering a new course built on a simple premise: you don’t need to know how to code — you need a problem worth solving. AI-Assisted Problem Solving (AI 5000 / CSCI 4930 / CSCI 5930) turns AI into a research partner for your own discipline, whether that’s health sciences, business, the humanities, or wherever you work.
Most courses about artificial intelligence start by teaching you to build AI. This one starts somewhere else: with a real problem in your field, and the question of how AI can help you solve it — responsibly, and with judgment you can defend.
Offered fully online and asynchronous over 14 weeks, the course is open to students with no computer science experience. It fits around work and life at roughly ten hours a week, and every example is drawn from a real discipline — health sciences, business, STEM, the humanities, or your own.
Not a Prompting Course
The goal isn’t to paste a prompt and hope. Over the semester, students learn to dig into real problems with AI, question and verify what it gives back, and build a repeatable process they can trust. The course is organized around three ideas:
- Research your field, faster. Use AI to gather, clean, and make sense of real data and literature in your own discipline — the actual work of getting from a messy question to something you can analyze.
- Judgment, not just prompts. Learn to catch hallucinations, bias, and overconfident answers, and — just as important — know when to trust an AI’s output, when to refine it, and when to override it entirely.
- Ship a real deliverable. The course ends with an AI-assisted solution to an authentic problem in your field: built, defended, and yours.
What You’ll Be Able to Do
By the end of the course, students can:
- Explain, in plain language, how AI models actually learn and generate answers — enough to predict where they’ll shine and where they’ll fail.
- Prepare and analyze data, turning messy, real-world information into patterns and predictions you can interpret.
- Evaluate critically, checking AI output for accuracy, bias, and reliability with concrete tests rather than gut feel.
- Engineer a process — a repeatable, human-in-the-loop workflow you can reuse on any new problem.
- Develop a domain solution, applying everything to a real project in your field, from proposal to finished deliverable.
- Use AI responsibly, spotting ethical risks like bias, fairness, and over-reliance, and acting on them.
Built for Every Discipline
The course is deliberately field-agnostic. A health sciences student and a humanities student sit in the same course and work on entirely different problems — the method transfers, the domain is yours. Coursework is interactive and project-based, with weekly peer interaction and hands-on experience using the latest AI tools.
The Capstone: Your Own AI Project
Every student picks a real problem in their own discipline and builds a complete, AI-assisted solution to it — then defends the human judgment behind every step. The deliverable is meant to be authentic and usable, not a classroom exercise: something students can carry back into their field and their work.
AI-Assisted Problem Solving runs in Fall 2026 as AI 5000, CSCI 4930, or CSCI 5930. Students interested in enrolling are encouraged to speak with their academic advisor or contact the Department of Computer Science. The course is taught by Dr. David Letscher (david.letscher@slu.edu).
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