Plug-in Modules
Interdisciplinary, innovative and cooperative: in plug-in modules, students work together with their peers from all schools on projects that transcend disciplinary boundaries. Thus, they develop individual talents and skills in a wide range of future-oriented fields.
Plug-in Modules in the winter semester 2024/25
AI & Data Science
This module offers TUM students a comprehensive introduction to prompt and bot engineering for text generation with large language models (LLMs). Combining practical skills in prompt engineering with a focus on legal, ethical, and societal implications, the course covers topics such as prompt effectiveness, responsible deployment, human-computer interaction, and intellectual property issues.
Detailed information and registration in TUMonline:
After this class, students will be able to apply advanced computational methods to their own research projects. They will be able to collect and manipulate data. The students will then be able to utilize existing packages in the Python programming language to analyze large text corpora and network data. They will also learn how to use standard machine learning methods on their data.
In this module, students will gain a deep understanding of how to align generative AI systems with societal values, focusing on fairness, accountability, and transparency. Through hands-on experience, they will learn to identify and mitigate biases in AI models, while developing the skills to balance innovation with ethical responsibility in real-world applications.
Detailed information and registration in TUMonline:
Upon successful competition of this module, students will have a theoretical and practical understanding of methods of social network analysis, and will further be able to apply this knowledge to their own projects. Students will be able to: (1) collect, manipulate, and visualize network data, (2) apply methods of social network analysis, and (3) utilize existing packages in the Python programming language to analyze network data.
This module offers a comprehensive understanding of open science principles, including open access, research data, and open-source projects, with a focus on democratizing knowledge. Through hands-on activities and case studies, you’ll gain practical skills to apply open science practices in your future career, contributing to a more inclusive and accessible knowledge economy.
Detailed information and registration in TUMonline:
- Lecture and seminar: Open Data – Open Science
In this module, students deal with the psychological foundations of learning and effective instructional design for AI-based systems. They learn to make use of cognitive learning theories in the context of AI applications and to understand and analyze the interaction between humans and AI from a psychological perspective