5 Free AI Courses from Hugging Face – KDnuggets

Hands-on, community driven courses on LLMs, AI agents, MCPs, diffusion models, and reinforcement learning.

Image by Author
 
 
Hugging Face has become the go-to hub for discovering AI models, datasets, and demos. Beyond that, it has also evolved into an educational platform where you can learn through blogs, articles, tutorials, and courses. The community is highly active and interactive, making it a great place to grow your AI knowledge.
In this article, we’ll review some of the most popular and essential free courses offered on Hugging Face. These courses cover topics such as AI agents, Model Context Protocols (MCPs), large language models (LLMs), diffusion models, and reinforcement learning, all of which are at the core of today’s rapidly evolving AI landscape.
 
 
The AI Agents Course is a community-driven program that takes you from theory to practice. You will learn core concepts, build with smol-agents, LlamaIndex, and LangGraph, experiment in preconfigured Hugging Face Spaces, share on the Hub, and compete on a public leaderboard.
 
The AI Agents course landing page | Image by Author
 
Engage with the community via GitHub and Discord, and earn free certificates by completing units and challenges. Sign up to get unit links and updates; your email is used only for course communications.
 
 
The Model Context Protocol (MCP) Course is designed to take you from the basics of AI to advanced mastery of the Model Context Protocol. Throughout the course, you will learn about MCP in theory, design, and practice. Additionally, you can share your projects and explore applications created by the community.
 
The Model Context Protocol (MCP) course landing page | Image by Author
 
The course combines foundational units on MCP concepts, architecture, and core components with hands-on building sessions and real-world assignments that you can choose.
 
 
The Hugging Face LLM Course bridges foundational natural language processing (NLP) and the latest advancements in large language models (LLMs), guiding you from essential NLP concepts to hands-on experience with powerful models like those in the Transformers library.
 
The Large Language Model (LLM) course landing page | Image by Author
 
You will learn to use, fine-tune, and deploy LLMs, tackle classic and advanced NLP tasks, and showcase your work — all while building practical skills that prepare you to excel in the rapidly evolving field of AI.
 
 
The Hugging Face Diffusion Course is a hands-on program that guides you through the theory and practical applications of diffusion models, including generating images and audio with the Diffusers library, training your own models from scratch, fine-tuning existing models on new datasets, and exploring advanced techniques like conditional generation and custom pipelines.
 
The Diffusion Models course landing page | Image by Author
 
The course is structured into four units covering everything from basic introductions to advanced topics like Stable Diffusion and creative model applications.
 
 
The Hugging Face Deep RL Course offers a comprehensive, hands-on journey through both the theory and practice of deep reinforcement learning (Deep RL), guiding you from foundational concepts to state-of-the-art methods.
 
The Deep Reinforcement Learning course landing page | Image by Author
 
You will learn to use popular libraries like Stable Baselines3 and CleanRL, train agents in unique and classic environments such as SnowballFight, Huggy the Doggo, VizDoom, and Space Invaders, and share your results with the community — all within an engaging, challenge-based format.
 
 
Hugging Face offers a collection of free, community-driven courses designed to take you from theory to hands-on practice in today’s most important AI domains.
 
 
Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in technology management and a bachelor’s degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.
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