Generative Artificial Intelligence

Catalog description

This course provides an in-depth study of generative artificial intelligence methods and systems. Students explore the theoretical foundations and practical implementations of generative models, including autoregressive models, variational autoencoders, diffusion models, and large-scale foundation models. Emphasis is placed on representation learning, model training at scale, prompt and conditioning strategies, evaluation of generative outputs, and deployment considerations.