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Catalog Description
Design and development of practical applications powered by large language models (LLMs), including agentic systems that can plan, take actions, and use tools to complete real-world tasks.
Instructor Description
This course explores the design and development of practical applications powered by large language models (LLMs), including agentic systems that can plan, take actions, and use tools to complete real-world tasks. The course covers both LLM fundamentals—how LLMs work, their capabilities and limitations—and applied methods for building reliable systems, including prompting, retrieval-augmented generation, orchestration, safety, and evaluation. The course is project-driven: student teams build and iterate on an LLM-based application throughout the term, complemented by guest lectures from founders, investors, and researchers on building and assessing frontier AI systems.
By the end of this course, students will be able to:
- Design and build a working LLM-powered application from idea to deployed product
- Apply core techniques—prompting, RAG, orchestration, agentic tool use, and multi-modal integration—to solve real-world problems
- Evaluate LLM systems for quality, safety, and cost
- Iterate on a product based on real user feedback
- Communicate and present an AI product to technical and non-technical audiences
Prerequisites
Graduate standing.
Restrictions
Instructor permission required. Application instructions will be provided here prior to registration.