Welcome to the official repository of the "Applied Artificial Intelligence" course! This course is offered at the University of Bayreuth, Karlsruhe Institute of Technology ("Artificial Intelligence in Service Systems"), and Technical University of Munich. It was made possible through the support of the ABBA project.
"Applied Artificial Intelligence" is a comprehensive course designed to provide students with both theoretical and practical knowledge in the field of Artificial Intelligence (AI). The course covers a wide range of AI examples and applications, covering the entire machine learning pipeline from problem definition up to successful deployment and monitoring. As part of this course, we are focusing on how these technologies are applied in real-world scenarios. Furthermore, we will cover important aspects around foundation models (like LLMs), human-AI collaboration, creative AI, as well as AI ethics & fairness.
This repository contains the following materials:
- Lecture Slides: Presentations used during the lectures.
- Papers (Reading Materials): Suggested readings and reference materials to deepen understanding.
The videos are hosted on the Applied Artificial Intelligence Youtube Playlist.
To benefit fully from this course, it is helpful for students to have a basic understanding of programming (preferably Python), basic statistics, and a general interest in AI and its applications.
- Clone the repository:
git clone https://github.com/nkukit/aai.git
- Navigate through the directories to find lecture materials, assignments, and other resources.
- Follow the instructions in each folder to complete the exercises and projects.
This repository is intended for educational purposes only. Contributions are currently not accepted, but suggestions for improvements can be made by opening an issue.
Applied Artificial Intelligence © 2024 by Niklas Kühl is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International.
You are free to:
- Share — copy and redistribute the material in any medium or format.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
For more details, please refer to the full license here.
This course was made possible by the ABBA project, which supports advanced AI education across multiple institutions.
For any questions or further information, please contact the course instructor:
We hope you enjoy the course and gain valuable insights into the world of Applied Artificial Intelligence!