AI STARTUP FOUNDATIONS

Startup Foundations: Learnings from Early-Stage AI Founders

This course provides students, researchers, and aspiring entrepreneurs with a structured and practice-oriented introduction to building startups in artificial intelligence (AI) and other deep tech domains. Its purpose is to make entrepreneurial education and AI expertise combined accessible in a modular fashion, offering a flexible format that can be used as a stand-alone online training, embeddable in university courses, workshops and hackathons.

The course is designed around eight interconnected modules that mirror the Lean Startup journey: Introduction, Timing, Focus, Execution, Validation, Insights, Trust, and Fuel. Each module combines short theory inputs from actual early stage AI Startups with reflective tasks, team-based exercises, and hands-on tool use. This modular structure ensures that knowledge transfer is easy and that content can be integrated into existing curricula while still working independently.

Learners will gain competences in problem discovery, ideation, and value proposition design; develop the ability to rapidly create AI-enabled prototypes using no-code and AI tools; design lightweight validation experiments; synthesize customer insights into strategy; plan for trust, ethics, and compliance; and finally prepare for growth through storytelling, pitch creation, and partnership strategies. Practical skills are always linked to entrepreneurial competences such as opportunity recognition, resource mobilization, and risk management.

The program strongly emphasizes active learning. Participants will work on tangible deliverables including an elevator pitch, Lean Canvas, Minimum Viable Product (MVP) prototype, Validation Report, Trust & Ethics Plan, and a final Pitch Deck. Hackathon-style challenges to outline AI based automation processes, flipped classroom exercises, and reflection prompts encourage experimentation and iteration. The open-source Founders AI Toolbox complements the modules, offering continuously updated tools, workflows, links to tool tutorials, and use cases for practical exploration.

Assessment is based on module deliverables and self-tests, with optional certification per module. The full course represents at least 50 hours of learning (including online lessons, tasks, and project work). Offered free of charge under the AI+MUNICH / AI NATION initiative, the course is continuously enriched through real startup cases and contributions from Germany’s innovation ecosystem.