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Starts 3 June 2026 23:08
Ends 3 June 2026
Vibe Coding: AI-Powered App Development for Product Managers
University of Maryland, College Park
15 Courses
The University of Maryland, College Park is a public research university renowned for its diverse student community and prestigious academic programs. With more than 200 degree courses, exclusive internships, and progressive research opportunities, UMD provides a top-tier educational experience.
4 weeks, 1-2 hours a week
Optional upgrade avallable
Beginner
Progress at your own speed
Free Online Course (Audit)
Optional upgrade avallable
Overview
This course shows product managers how to turn AI from a buzzword into a hands‑on build partner. By the end, you’ll be able to design and ship real applications by “vibe coding” with AI.
Describing outcomes, flows, and emotional tone in natural language while the model handles code, architecture, and integration. You’ll learn how to use Model Context Protocol (MCP) to make your agents predictable and safe, engineer context so they reflect your product’s voice and guardrails, and run fast, AI‑assisted iterations from first prototype through testing and retrospective.
Drawing on real case studies like a PTSD support app and a four‑day health platform, you’ll practice shipping useful, user‑centered AI products without needing deep engineering skills. This course is practical for product managers who want to compress timelines, validate ideas quickly, and stay in control of experience and ethics while AI does the heavy lifting.
Syllabus
- Describe product ideas, user flows, and emotional tone in natural language
- Use natural language to design AI-powered apps by “vibe coding”
- Apply "vibe coding" to shift from thinking in code and syntax to thinking in outcomes, experience, and user emotion.
- Use Model Context Protocol to make AI agents reliable and safe
- Run AI-assisted product cycles from prototype through testing and launch
- Co‑develop with AI through rapid, conversational iteration to refine UX, flows, and features based on real feedback.
- Drive an AI‑assisted product lifecycle end‑to‑end, from first build through testing, troubleshooting, and retrospective planning.
Subjects
Programming