CS 466Natural Language Processing & Large Language Models

Catalog

An in-depth, hands-on study of Natural Language Processing (NLP) and Large Language Models (LLMs) is provided, with emphasis placed on modern deep learning architectures and real-world AI system development. Coverage progresses from foundational NLP techniques to state-of-the-art transformer-based models, including BERT-style encoders, GPT-style decoders, and instruction-tuned LLMs. Strong emphasis is placed on practical implementation, model evaluation, and system-level design, incorporating contemporary AI paradigms such as Retrieval-Augmented Generation (RAG), tool-using LLMs, multi-agent systems, and neuro-symbolic reasoning. Modern frameworks and libraries, including PyTorch, Hugging Face Transformers, and LangChain.