AI 451 - Generative AI (GANs, VAEs, Diffusion Models)

3 Credit Hours

This course explores generative models used to create new data from learned distributions. Topics include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models. Students implement generative architectures for creative applications such as image synthesis, style transfer, and data augmentation.
Corequisite: A “C” or better in:

AI 332 - Deep Learning II

AND AI 351 - Transformer Models and Large Language Models (LLMs)
Lecture Hours: 3
Term(s) Offered: Fall