Natural Language Processing: From Foundations to Large Language Models

Catalog description

This course introduces the core principles, models, and real-world applications of Natural Language Processing (NLP) and Large Language Models (LLMs) in the context of modern data science. Students will explore NLP tasks, build deep learning models for language understanding and generation, and apply LLMs to solve problems such as information extraction, conversational AI, summarization, and data querying. Students will interact with state-of-the-art LLMs using industry-standard APIs, gaining practical skills in prompt design, system integration, and application development. The course also includes a critical focus on LLM trust, safety, and ethical deployment, preparing students to responsibly build and evaluate generative AI systems. Through projects, students will emerge with both conceptual understanding and practical fluency in applied NLP and LLM development. Recommended background: Programming skills equivalent to (CS 1004 or CS 1101 or CS 1102) and (CS 2102 or CS2103 or CS 2119); and machine learning equivalent to (DS 3010, CS 4445, or CS4342). Units: 1/3 Category: II