24-880 AI Agents for Engineers

12 units, Carnegie Mellon University

This course provides engineers with the theoretical background and hands-on skills to design and deploy LLM-based agents that streamline and enhance engineering workflows. This course introduces students to the integration of models like GPT, Claude, Gemini, and LLaMA into engineering pipelines for simulation, optimization, analysis, and documentation in real-world applications. Students will learn about LLM internals, prompting, fine-tuning, and frameworks for building agents capable of reasoning, planning, and using tools across complex engineering tasks. The course centers on LLMs as autonomous collaborators that can interact with CAD tools, simulations, APIs, and codebases to perform tasks such as simulation setup, technical report generation, code development, and design optimization. Topics include retrieval-augmented generation, multi-agent systems, tool calling, agent memory, and human-in-the-loop workflows. Students will complete hands-on assignments and a capstone project applying LLM agents to a specific engineering domain such as robotics, materials, or biomedicine. By the end, students will be able to design, evaluate, and deploy reliable LLM agents in practical engineering settings.

Prerequisites: none listed

Offered: Spring 2027, Fall 2026, Spring 2026

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