21 June 2024
Generative AI for Text, Audio and Images
We will cover the basic concepts of prominent methods for generative deep learning before starting a deep dive on their application to text, audio and images. Since we will focus on applications and the usage of respective foundation models and toolkits, we strongly recommend you get familiar with deep learning ahead of this course. In detail, we will cover:
Theory: Prominent generative Deep Learning Methods
-Generative Pretrained Transformers (GPT), Fine-Tuning, RLHF, Instruction Learning, Zero-Shot Learning, In-Context Learning, Chain-of-Thought
-Generative Adversarial Networks (GAN)
-Variational Auto-Encoders (VAE)
-Diffusion
-Style transfer
Hands-On:
-Text: GPT Prompt Engineering
-Text to Speech, Voice Conversion
-Image generation and captioning
We will conclude the course with an outlook on risks, limitations, ethical and legal implications.
Course leader
Korbinian Riedhammer | Damian Borth
Target group
Master | PhD | Postdoc | Professional
Fee info
CHF 1100: Master | PhD
CHF 2000: Postdoc | Professional