Foundation Models and Generative AI

Description

This course explores the principles, architectures, and applications of foundation models and generative AI, including large language models (LLMs), diffusion models, and multimodal AI systems. Students will study the underlying techniques behind models such as GPT, BERT, and Stable Diffusion, focusing on training methodologies, fine-tuning strategies, and deployment considerations. The course covers key topics such as transfer learning, prompt engineering, ethical implications, and real-world applications in text, image, and code generation. Through hands-on projects, students will gain practical experience in building, customizing, and integrating generative AI models into software systems, preparing them for the rapidly evolving AI landscape. Prerequisite(s): SOFE 3620U