CSC 7026 Large Language Models and RAG
This course provides a comprehensive study of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems, two transformative paradigms in modern artificial intelligence. Students will examine the theoretical foundations and architectural principles of transformer-based language models, including pre-training strategies, fine-tuning methodologies, and prompt engineering techniques. The course further explores how RAG frameworks integrate external knowledge retrieval with generative language models to produce more accurate, grounded, and contextually relevant outputs. Students will gain hands-on experience designing, implementing, and evaluating LLM-powered pipelines and RAG architectures for real-world applications.