Hugging Face AI Agents Course Project Introduction

Project Overview

The Hugging Face AI Agents Course is a free online course designed to help learners grow from beginners to AI agent experts. Developed by the Hugging Face team, it is an active open-source project that is continuously improved based on community feedback.

Key Features

🎯 Learning Objectives

• Balance of Theory and Practice: Learn the theory, design, and practice of AI agents.
• Mastery of Libraries and Tools: Learn to use established AI Agent libraries such as smolagents, LlamaIndex, and LangGraph.
• Community Sharing: Share your agents on the Hugging Face Hub and explore agents created by the community.
• Competition Challenges: Participate in challenges to compare your agent with those of other students.
• Certification: Earn a certificate of completion by completing assignments.

📚 Course Structure

Main Units

Chapter	Topic	Description
0	Onboarding	Setting up tools and platforms
1	Agent Fundamentals	Explaining tools, thinking, action, observation and their formats; explaining LLMs, messages, special tokens, and chat templates; demonstrating simple use cases using Python functions as tools
2	Frameworks	Understanding how fundamental concepts are implemented in popular libraries: smolagents, LangGraph, LLamaIndex
3	Use Cases	Building real-life use cases
4	Final Assignment	Building an agent for a selected benchmark and proving your understanding of agents on the student leaderboard

Extra Bonus Units

• Bonus Unit 1: Fine-tuning an LLM for Function-calling
• Bonus Unit 2: Agent Observability and Evaluation
• Bonus Unit 3: Agents in Games with Pokemon

🛠️ Technical Requirements

Prerequisites

• Basic Python knowledge
• Basic knowledge of LLMs (reviewed in the course)

Required Tools

• Computer with internet connection
• Hugging Face account (free registration)

📋 Learning Approach

Course Components

• Fundamental Units: Learning the theory of agent concepts
• Hands-on Practice: Learning to use established AI Agent libraries to train your agents in unique environments. These hands-on sections will be Hugging Face Spaces with a pre-configured environment
• Use Case Assignments: Applying learned concepts to solve real-world problems
• Challenges: Competing your agent against other agents, with a leaderboard to compare agent performance

Recommended Learning Pace

• Each chapter is designed to be completed in 1 week
• Approximately 3-4 hours of study time per week
• Certification deadline: July 1, 2025

🏆 Certification System

Certification Types

1. Basic Certification: Earned upon completion of Unit 1
2. Completion Certification: Requires completion of Unit 1, one use case assignment, and the final challenge

Certification Requirements

• Completely free
• All assignments must be completed before July 1, 2025

👥 Course Team

Main Instructors

• Joffrey Thomas: Machine Learning Engineer at Hugging Face, building and deploying AI agents in production environments
• Ben Burtenshaw: Machine Learning Engineer at Hugging Face, experienced in multi-platform course delivery
• Thomas Simonini: Machine Learning Engineer at Hugging Face, creator of Deep RL and ML for games courses
• Sergio Paniego: Machine Learning Engineer at Hugging Face, contributed content to multiple units

🌟 Project Highlights

Open-Source Community Driven

• Open-source GitHub project, contributions welcome
• Discord community support and discussion
• Continuously improved based on feedback

Practice-Oriented

• Pre-configured Hugging Face Spaces environment
• Real-world use cases
• Agent performance leaderboard

Interactive Learning

• Quizzes and assignments
• Community study groups
• Live sessions and interactive content

📊 Tech Stack

Main Frameworks and Libraries

# Main AI agent libraries used
- smolagents
- LangGraph
- LlamaIndex

Platform Support

• Hugging Face Hub
• Hugging Face Spaces
• GitHub collaboration
• Discord community

🎮 Featured Content

Pokemon Agent Game

In Bonus Unit 3, learners can build agents to battle Pokemon, a fun and practical project.

Production-Grade Agents

The course not only teaches theory but also includes agent observability and evaluation, preparing you for production environments.

Summary

The Hugging Face AI Agents Course is a comprehensive, practice-oriented AI agent learning platform that combines theoretical learning, hands-on practice, community interaction, and a certification system. It is an active project that evolves with your feedback and contributions. The course is suitable for learners with basic Python knowledge, benefiting both beginners and expert-level AI agent developers.