Theory and Applications of Large Language Models

A Spring 2026 topics course examining transformer architecture, sampling, search, and the critical evaluation of large language models. Students built small models and applied pretrained systems through fine-tuning, prompt engineering, retrieval-augmented generation, and agents, with attention to bias, safety, and responsible deployment.