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Syllabus

Course Structure Overview

First, we gather insights about AI in general and generative AI (GenAI) in particular. We explore key technologies, tools, and applications in media contexts. Students will present on specific tools and conduct a small project using one or more AI applications. Then we discuss ethical, societal and environmental implications of GenAI.

Part Topics Type Sessions
1 Introduction & Foundations Lecture + Discussion 3
2 GenAI Tools & Applications Showcase + Demos + Projects 5
3 Implications of GenAI Discussion + Debate + Talks 3

(Preliminary) Weekly Breakdown

Last update: 2025-10-03

Calendar Week Topic Type Remarks
40 Introduction with MIB1 + Course Overview Administration + Activity Term kick-off with MIB1
41 History and basics of AI Lecture + Discussion Start with mind map
42 Basics of AI Lecture + Discussion
43 Generative AI paradigms Lecture + Discussion Decision for topic
44 First research results Personal review Plan for presentation
45 AI in the industry Activity Hochschulkontaktbörse
46 Theory presentations Student presentations First four topics
47 Theory presentations Student presentations Remaining topics
48 GenAI tool and project idea presentation Student presentations + Discussion Continue working with the tool
49 First tool results Personal review Have a complete project plan
50 Final presentation of projects Student presentations
51 Final presentation of projects Student presentations
02 Reflection on using AI in creative processes Practical Lab
03 Consequences of using AI in creative processes Practical Lab
04 Rehearsal for colloquium Student Talks

Grading & Deliverables

Theory presentation (30%)

  • An application or field will be presented (e.g., text, image, ...) and a tool is chosen for deeper exploration.
  • Deliverables: Presentation of exactly 15 minutes, then 5 - 15 minutes Q&A, hand-out (pdf) summarizing key points.
  • The presentation (and the hand-out) shall cover:
    • Overview of the application area
    • Key models and architectures
    • Relevant tools and frameworks
    • Example use cases and demos
    • Challenges and future directions
  • Evaluation is based on clarity, depth of research, and engagement.
    • List all references and tools used in the hand-out.

GenAI tool and project presentation (40%)

  • Small-scale experiment using a GenAI tool
  • Deliverables: Live demo (15 minutes including Q&A), documentation

Participation (30%)

  • Active participation in sessions, discussions, and activities, including peer feedback

Tools & Resources

  • We will use a variety of AI tools. We will compare local installations with cloud-based services.
  • We will use Google Colab for cloud-based experiments and collaboration.
  • We will use Ollama to run large language models (LLMs) locally on our machines.

Reading / Resources

  • Selected articles, papers, and videos will be provided throughout the course.