Building AI Agents with Hugging Face
by Hugging Face Team · Hugging Face
Our Verdict
Worth takingHugging Face's AI Agents Course is a free, self-paced, open-source course (29.4k GitHub stars, 2.1k forks) that takes you from agent fundamentals to building and benchmarking your own agents, and for hands-on learners new to agent frameworks it is one of the best free starting points available in 2026. It teaches both the theory (the Thought-Action-Observation loop, tools, LLM messages and chat templates) and three real frameworks - smolagents, LlamaIndex, and LangGraph - with runnable notebooks in pre-configured Hugging Face Spaces. The certification path is genuinely free and has no deadline, culminating in a final assignment evaluated on the GAIA-style benchmark with a public student leaderboard. The honest caveat, echoed by multiple learners, is that despite its 'beginner to expert' framing you will not become an expert from the four core units alone; it is a strong foundation that requires supplementary study to truly master. Note: the course covers smolagents, LlamaIndex and LangGraph - it is not a smolagents-only course, unlike the separate shorter DeepLearning.AI and DataCamp smolagents courses.
It is free, maintained by the framework's own authors, hands-on with working notebooks, and offers a no-deadline free certificate plus a competitive final project - excellent value for anyone with basic Python who wants a practical, framework-agnostic introduction to building AI agents.
Best for: Developers with basic Python and some exposure to LLM/GenAI APIs who have never built with an agent framework and want a free, hands-on path through the core concepts and the three major libraries (smolagents, LlamaIndex, LangGraph), ending in a real, leaderboard-graded project.
Skip if: Complete programming beginners (basic Python is assumed), people who want a deep production-grade or comprehensive treatment of the full agent landscape (MCP, A2A, advanced orchestration are largely absent), and anyone wanting passive video lectures rather than reading plus self-driven notebook work.
About This Course
Build AI agents that use tools, search the web, and generate code using Hugging Face's smolagents framework.
What You'll Learn
Curriculum
Sets you up with the tools and platforms: Hugging Face account, Discord, and choosing the audit vs certification path.
Tools, Thoughts, Actions, Observations and their formats; LLMs, messages, special tokens and chat templates; a simple use case using Python functions as tools. Completing this unit alone earns the 'fundamentals' certificate.
How the fundamentals are implemented in popular libraries: smolagents (CodeAgents, ToolCallingAgents, tools, retrieval/RAG agents, multi-agent systems, vision and browser agents), plus LangGraph and LlamaIndex. Requires ~80% on code-sample assessments to validate.
Real-life agent use cases (community/PR-driven, open to contributions from experienced agent builders).
Build an agent for a selected benchmark (GAIA-style) and prove your understanding on the public student leaderboard.
Train an LLM to better support tool/function calling.
Instrument and evaluate agents - praised by learners as addressing a real in-production concern.
Build an agent that plays Pokemon battles.
Prerequisites
- Basic knowledge of Python
- Basic knowledge of LLMs (Unit 1 includes a recap section)
- A computer with an internet connection
- A free Hugging Face account (to push/load models and create Spaces)
Instructor
Hugging Face Team
Instructor · Hugging Face
Pros & Cons
Pros
- Completely free, including the certification path, with no deadline - you can audit or certify at your own pace
- Genuinely hands-on: each concept is followed by a working notebook in a pre-configured Hugging Face Space, and learners specifically praise the practical, runnable experience
- Framework-agnostic breadth - covers smolagents, LlamaIndex and LangGraph rather than locking you into one library, helping you compare design tradeoffs
- Maintained by Hugging Face and written by the people behind smolagents (Ben Burtenshaw, Sergio Paniego, Joffrey Thomas, Thomas Simonini), with an active open-source repo (29.4k stars) and Discord community
- The final GAIA-style benchmark project with a public student leaderboard is described by learners as fun, challenging and the most valuable part
Cons
- Overpromises on its 'beginner to expert' framing - multiple learners note you will not become an expert from the four core units alone and must supplement with external resources
- Coverage gaps: learners wanted a broader view of the framework landscape, including newer topics like MCP and A2A that are largely absent
- Assessment friction reported in Unit 2: at least one learner found the auto-grading expectations unclear (e.g., the agent-security question repeatedly failing validation despite multiple attempts), requiring trial-and-error to reach the 80% pass mark
- It is a living, partly community/PR-driven course (especially Unit 3 use cases), so depth and currency can vary across units, and it leans on reading plus self-driven notebooks rather than structured video lectures
Alternatives To Consider
Frequently Asked Questions
Is Building AI Agents with Hugging Face free?
Yes — Building AI Agents with Hugging Face is free to access. Free, including the certificate of completion and the 'fundamentals' certificate - there is no paid tier and no deadline. The only requirement is a free Hugging Face account. Note: the catalog lists certificate:false, but the official course page confirms certificates ARE issued for completing the required units and the final challenge.
Who is Building AI Agents with Hugging Face for?
Developers with basic Python and some exposure to LLM/GenAI APIs who have never built with an agent framework and want a free, hands-on path through the core concepts and the three major libraries (smolagents, LlamaIndex, LangGraph), ending in a real, leaderboard-graded project.
What will you learn in Building AI Agents with Hugging Face?
The core anatomy of an agent: Tools, Thoughts, Actions, Observations and their formats, plus how LLM messages, special tokens and chat templates work; Building a simple agent from scratch using plain Python functions as tools (Unit 1); Building agents with smolagents, including CodeAgents (which emit Python) vs ToolCallingAgents (which emit JSON), custom tools via the Tool class or @tool decorator, retrieval/RAG agents, multi-agent orchestration, and vision/browser agents; Implementing the same agentic patterns in two other frameworks - LlamaIndex and LangGraph - to compare design approaches.
What are the prerequisites for Building AI Agents with Hugging Face?
Basic knowledge of Python; Basic knowledge of LLMs (Unit 1 includes a recap section); A computer with an internet connection; A free Hugging Face account (to push/load models and create Spaces).
Is Building AI Agents with Hugging Face worth it?
It is free, maintained by the framework's own authors, hands-on with working notebooks, and offers a no-deadline free certificate plus a competitive final project - excellent value for anyone with basic Python who wants a practical, framework-agnostic introduction to building AI agents.
How we reviewed this course
This is an independent editorial assessment by Cursarium, based on Hugging Face's published course materials and aggregated public learner feedback (last reviewed 2026-06). We have not independently completed the course. Links to providers are standard references, not paid placements.
Sources
- Official course - Hugging Face AI Agents Course (syllabus, prerequisites, certification, pace)
- Official course - Unit 2 smolagents module (CodeAgents, ToolCallingAgents, tools, RAG, multi-agent, vision)
- GitHub - huggingface/agents-course (29.4k stars, 2.1k forks; popularity and open-source signal)
- Learner feedback - Mathieu Veron (Medium): hands-on praise, 'not expert from 4 units', wants MCP/A2A
- Learner feedback - Alain Airom (Medium): Unit 1 praised, Unit 2 grading/security-question friction