Search Results

This course offers a comprehensive introduction to the core concepts and recent advancements in natural language processing (NLP) and language modeling. Students will begin with foundational topics such as n-gram models and basic probabilistic approaches, building a strong understanding of the fundamentals of NLP. The course will then progress to state-of-the-art language model architectures, including transformers, GPT-3, and other large language models (LLMs). Students will explore the theoretical foundations of these models, learn about their architecture and training methods, and gain practical experience in building, fine-tuning, and deploying them to address real-world tasks like text understanding, generation, and conversational AI.

College/Department: College of Computing and Informatics
Repeat Status: Not repeatable for credit
Prerequisites: DSCI 521 [Min Grade: B-] or DSCI 501 [Min Grade: B-] or CS 613 [Min Grade: B-] or INFO 624 [Min Grade: B-] or INFO 659 [Min Grade: B-]