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Agents course

This repository contains the Hugging Face Agents Course.

From huggingface·Updated June 1, 2026·View on GitHub·

If you like the course, **don't hesitate to ⭐ star this repository**. This helps us to **make the course more visible 🤗**. The project is written primarily in MDX, distributed under the Apache License 2.0 license, first published in 2025. It has gained significant community traction with 29,041 stars and 2,088 forks on GitHub. Key topics include: agentic-ai, agents, course, huggingface, langchain.

<a href="https://hf.co/learn/agents-course" target="_blank">The Hugging Face Agents Course</a>

If you like the course, don't hesitate to ⭐ star this repository. This helps us to make the course more visible 🤗.

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Content

The course is divided into 4 units. These will take you from the basics of agents to a final assignment with a benchmark.

Sign up here (it's free) 👉 <a href="https://bit.ly/hf-learn-agents" target="_blank">https://bit.ly/hf-learn-agents</a>

You can access the course here 👉 <a href="https://hf.co/learn/agents-course" target="_blank">https://hf.co/learn/agents-course</a>

UnitTopicDescription
0Welcome to the CourseWelcome, guidelines, necessary tools, and course overview.
1Introduction to AgentsDefinition of agents, LLMs, model family tree, and special tokens.
1 BonusFine-tuning an LLM for Function-callingLearn how to fine-tune an LLM for Function-Calling
2Frameworks for AI AgentsOverview of smolagents, LangGraph and LlamaIndex.
2.1The Smolagents FrameworkLearn how to build effective agents using the smolagents library, a lightweight framework for creating capable AI agents.
2.2The LlamaIndex FrameworkLearn how to build LLM-powered agents over your data using indexes and workflows using the LlamaIndex toolkit.
2.3The LangGraph FrameworkLearn how to build production-ready applications using the LangGraph framework giving you control tools over the flow of your agent.
2 BonusObservability and EvaluationLearn how to trace and evaluate your agents.
3Use Case for Agentic RAGLearn how to use Agentic RAG to help agents respond to different use cases using various frameworks.
4Final Project - Create, Test and Certify Your AgentAutomated evaluation of agents and leaderboard with student results.
3 BonusAgents in Games with PokemonExplore the exciting intersection of AI Agents and games.

Prerequisites

  • Basic knowledge of Python
  • Basic knowledge of LLMs

Contribution Guidelines

If you want to contribute to this course, you're welcome to do so. Feel free to open an issue or join the discussion in the Discord. For specific contributions, here are some guidelines:

Small typo and grammar fixes

If you find a small typo or grammar mistake, please fix it yourself and submit a pull request. This is very helpful for students.

New unit

If you want to add a new unit, please create an issue in the repository, describe the unit, and why it should be added. We will discuss it and if it's a good addition, we can collaborate on it.

Citing the project

To cite this repository in publications:

bibtex
@misc{agents-course, author = {Burtenshaw, Ben and Thomas, Joffrey and Simonini, Thomas and Paniego, Sergio}, title = {The Hugging Face Agents Course}, year = {2025}, howpublished = {\url{https://github.com/huggingface/agents-course}}, note = {GitHub repository}, }

Contributors

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This article is auto-generated from huggingface/agents-course via the GitHub API.Last fetched: 6/1/2026