Generative AI


In this module, we provide a comprehensive overview of the generative AI landscape covering both theory and practical applications. We dive into the fundamental ideas related to autoencoders, generative adversarial networks, and autoregressive

models. We explore advanced techniques, including transformers, diffusion models, and multimodal models, illustrating their

capabilities across various tasks.

The focus is on generative AI techniques and their applications in our everyday life as well as in professional environments spanning fields such as advertising, fashion design, creative writing, music production, and software engineering. We will discuss, understand, and implement various useful generative AI methods like styleGANs, large language models (LLMs) such as GPT and LLaMA, vision-language models like DALL·E, Stable Diffusion, etc. Participants will gain a deeper understanding of these cutting-edge generative AI methods and their practical utility.

Verantwortliche Person:
Prof. Dr. Purandare Mitra
Standort (angeboten):
Empfohlene Module:
Zusätzlich vorausgesetzte Kenntnisse:

Python skills are necessary. This module is taught in English. Most of the AI Literature is in English. An intermediate level is recommended. The students are free to write reports in German or English. The exam questions will be in English, the students are free to write answers in German or English.

Standard-Modul für Informatik STD_14(Empfohlenes Semester: 4)
Standard-Modul für Informatik STD_21(Empfohlenes Semester: 4)
Standard-Modul für Informatik STD_23(Empfohlenes Semester: 4)
Standard-Modul für Data Science STD_23 (VR)

Kurse in diesem Modul