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Free courses, tutorials, research discussions, and practical guides to help you learn about AI agents, at your own pace.
A university lecture series introducing LLM reasoning, planning, tools, retrieval, agent frameworks, applications, evaluation, and safety. The official schedule links public edited videos and slides. Basic machine learning and deep learning background is recommended. Campus grading, discussion systems, and credit are separate from the public materials.
Open resourceA graduate course on LLM agents, tools, context, memory, planning, evaluation, training, safety, and interaction. The official site links public slides, recordings, and assignments as they are released. Requires prior experience training neural language models. The Fall 2026 course is still in progress; it is an advanced resource, not a zero-background introduction.
Open resourceAn advanced university lecture series on agent reasoning, inference-time search, post-training, code generation, verification, and mathematical problem solving. Public videos and slides are linked from the official course schedule. Best for learners who already understand LLMs and basic agents; campus enrollment and grading are separate.
Open resourcePublic slides, readings, and released assignments from a university course on agent engineering, retrieval, tools, memory, evaluation, and safety. The Fall 2026 course is in progress and assumes NLP background. Lecture recordings are accessed through Stanford Canvas; this entry covers public materials and does not promise an open video course.
Open resource