Hugging Face Model Context Protocol (MCP) Course Details

Course Overview

The Hugging Face MCP Course is a free course designed to help learners grow from beginners into practitioners who understand, use, and build Model Context Protocol (MCP) applications. This course focuses on one of the most exciting topics in the current AI field: Model Context Protocol (MCP).

What is Model Context Protocol (MCP)

Model Context Protocol is an open standard that enables developers to establish secure, bidirectional connections between their data sources and AI-powered tools. MCP is like the USB-C port for AI applications; just as USB-C provides a standardized way to connect devices to various peripherals and accessories, MCP provides a standardized way to connect AI models.

Course Objectives

Upon completing this course, you will be able to:

• 📖 Learn Model Context Protocol from theoretical, design, and practical perspectives
• 🧑‍💻 Learn to use established MCP SDKs and frameworks
• 💾 Share your projects and explore community-created applications
• 🏆 Participate in challenges to compare and evaluate your MCP implementations against other students
• 🎓 Earn a Certificate of Completion by finishing assignments

Course Structure

The course consists of the following parts:

Foundational Units

In these units, you will learn MCP concepts from a theoretical perspective.

Hands-on

Learn to build applications using established MCP SDKs. These hands-on sections will provide pre-configured environments.

Use Case Assignments

Apply the concepts learned to solve real-world problems of your choice.

Collaborations

Collaborate with Hugging Face partners to provide you with the latest MCP implementations and tools.

Course Syllabus

Chapter	Topic	Description
0	Getting Started	Set up the tools and platforms you will use
1	MCP Fundamentals, Architecture, and Core Concepts	Explain the core concepts, architecture, and components of Model Context Protocol, demonstrating simple use cases with MCP
2	End-to-End Use Case: MCP in Practice	Build a simple end-to-end MCP application that can be shared with the community
3	Deployment Use Case: MCP in Practice	Build a deployed MCP application using the Hugging Face ecosystem and partner services
4	Additional Units	Extra units to help you make better use of the course, working with partner libraries and services

Learning Prerequisites

To be able to follow this course, you should have:

• A basic understanding of AI and LLM concepts
• Familiarity with software development principles and API concepts
• Experience with at least one programming language (Python or TypeScript examples will be shown)

If you lack this background, it is recommended to first study:

• LLM Course - Guides you through the basics of using and building LLMs
• Agents Course - Guides you through building AI agents with LLMs

Required Tools

You only need two things:

• A computer with an internet connection
• A Hugging Face account (free to create)

Certification Process

The course offers a completely free certification process:

Basic Certification

• Requires completion of Unit 1 of the course
• Suitable for students who want to understand the latest MCP trends but do not need to build full applications

Certificate of Completion

• Requires completion of the use case units (Units 2 and 3)
• Suitable for students who want to build complete applications and share them with the community

Recommended Learning Pace

• Each chapter is designed to be completed in 1 week
• Approximately 3-4 hours of study time per week
• Due to deadlines, it is recommended to follow the suggested learning pace

How to Make the Most of the Course

• Join a Discord study group: Learning in a group is always easier
• Complete quizzes and assignments: Practice and self-assessment are the best ways to learn
• Create a study plan to stay on track: You can use the recommended schedule or create your own

Course Features

• Community-Driven: This is an active project that will continuously evolve based on your feedback and contributions
• Open-Source Collaboration: Issues and Pull Requests are welcome on GitHub
• Real-time Support: Interact with classmates and instructors via the Discord server

Course Author

Ben Burtenshaw Machine Learning Engineer at Hugging Face, focused on building LLM applications with extensive experience in post-training and agentic approaches.

Course Value

This course represents the cutting edge of AI application development, helping you build advanced AI applications that can leverage external data and tools. You will learn to create powerful, scalable MCP applications, preparing you for real-world deployment.

By studying MCP, you will master how to enable AI models to better access and utilize external data sources, a critical skill in current AI application development.