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Artificial Intelligence and Machine Learning
Description: This course introduces large language models (LLMs) and their use in modern artificial intelligence applications. Topics include the principles behind LLMs, prompting and in-context learning, retrieval-augmented generation, fine-tuning and adaptation techniques, tool-augmented and agent-based workflows, and evaluation of LLM-powered systems. Emphasis is placed on designing, implementing, and assessing LLM applications for tasks such as question answering, summarization, information extraction, and decision support. Ethical considerations, limitations, and responsible use of LLMs are addressed throughout the course. Letter grade only.
Units: 3
Sections offered: Spring 2027
Prerequisite: AIBS: AIML 249, AI 210. CSBS, SEBS: CS 249
Artificial Intelligence and Machine Learning
Term : Fall 2026
Catalog Year : 2026-2027
AIML 366 - Large Language Models
Description: This course introduces large language models (LLMs) and their use in modern artificial intelligence applications. Topics include the principles behind LLMs, prompting and in-context learning, retrieval-augmented generation, fine-tuning and adaptation techniques, tool-augmented and agent-based workflows, and evaluation of LLM-powered systems. Emphasis is placed on designing, implementing, and assessing LLM applications for tasks such as question answering, summarization, information extraction, and decision support. Ethical considerations, limitations, and responsible use of LLMs are addressed throughout the course. Letter grade only.
Units: 3
Sections offered: Spring 2027
Prerequisite: AIBS: AIML 249, AI 210. CSBS, SEBS: CS 249