Course plan
AI Literacy @ TUM is planned as a voluntary, ungraded course in English for first-year students in the School of Computation, Information and Technology. It aims to help you use AI in your studies, check its results, and understand the rules for your coursework.
Planned; enrolment is not yet available.
You can read the public guides now. They provide additional explanations and examples; the planned course will stand on its own.
Format and study time
The plan contains 9 modules and 28 units. Each unit is planned to include a video, a short text summary, and formative quiz questions with explanatory feedback. Videos total 185 minutes, with 115 quiz questions across the course.
Allow about 5.9 hours in total. This estimate adds two minutes for each short summary and one minute per quiz question to the video time. Your study time may differ.
These are figures from the course plan, not enrolment or completion statistics. Plan reviewed on 5 October 2026.
Modules and units
Open a module to see its learning outcome, planned units, and related guides. Know what the course covers, how its units and quizzes work, and how to use Iris within the course. 4 formative quiz questions planned. Related public guides: Distinguish a model from the product around it and explain how prompts, context, and agent actions shape an interaction. 16 formative quiz questions planned. Related public guides: Explain why a plausible answer may be wrong, how retrieval can improve its information basis, and why source-backed answers still need checking. 12 formative quiz questions planned. Related public guides: For a concrete assignment, identify who is accountable, what assistance is permitted, and how to explain and declare your work while retaining understanding. 15 formative quiz questions planned. Related public guides: Find a TUM-related service for a concrete need, check who has access, and understand the purpose of the service. 12 formative quiz questions planned. Related public guides: Compare services and local models by their actual data flows, decide what material to enter, and identify the conditions to check. 12 formative quiz questions planned. Related public guides: Use AI to support learning, decide what to delegate, and verify the results in code, proofs, and data analysis. 18 formative quiz questions planned. Related public guides: Assess synthetic content, recognise the effects of bias and ranking, account for the costs of use, and inspect the interests behind product claims. 18 formative quiz questions planned. Related public guides: Evaluate an AI system and state what you will and will not delegate. 8 formative quiz questions planned. Related public guides:M0: Getting started 2 units · 12 video minutes
M1: AI foundations and language models 4 units · 27 video minutes
M2: Hallucinations, sources and grounding 3 units · 20 video minutes
M3: Responsible use and academic integrity 3 units · 22 video minutes
M4: TUM AI resources 3 units · 18 video minutes
M5: Data privacy and processing choices 3 units · 20 video minutes
M6: Applications in studying and research 4 units · 27 video minutes
M7: Generated media, bias and critical assessment 4 units · 26 video minutes
M8: Careers and human expertise 2 units · 13 video minutes
Questions about the plan
For a question about this course or a correction to the plan, use the AET contact information.