huggingface/agents-course

This repository contains the Hugging Face Agents Course.

MDX

33,742

1,769 commits

updated Oct 14, 2026

See the code

README

The Hugging Face Agents Course

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

Star the repo

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) 👉 https://bit.ly/hf-learn-agents

You can access the course here 👉 https://hf.co/learn/agents-course

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:

@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},
}
agentic-ai
agents
course
huggingface
langchain
llamaindex
smolagents

huggingface/agents-course

This repository contains the Hugging Face Agents Course.

MDX

33,742

1,769 commits

updated Oct 14, 2026

See the code

README

The Hugging Face Agents Course

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

Star the repo

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) 👉 https://bit.ly/hf-learn-agents

You can access the course here 👉 https://hf.co/learn/agents-course

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:

@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},
}
agentic-ai
agents
course
huggingface
langchain
llamaindex
smolagents

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