Areas of Competence: Knowledge and Understanding; Use, application and generation of knowledge; Communication and cooperation; Scientific self-understanding / professionalism.
Students
- know the fundamentals of generative AI systems.
- know various modern applications of generative AI systems.
- know the theoretical foundations and practical applications of generative AI systems.
Students
- are able to explain and apply various open-source language models.
- are able to implement and utilize agent systems and their functionalities.
- are able to understand and use embeddings and vector stores for semantic search and recommendations.
- are able to explain and practically apply different methods for image generation.
- are able to fine-tune large language models (LLMs) and diffusion models for specific tasks.
Students
- are able to successfully organize teamwork for generative AI projects.
- are able to report and present team solutions for practical project tasks.
- are able to interpret and communicate the approaches in technical and functional terms.
Students
- are able to work professionally in the field of generative AI systems.
- are able to give and accept professional feedback to different topics of generative AI systems.
- are able to select relevant scientific literature about generative AI systems.