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Merge pull request #12 from SABER-MOHAMED/docs/highlight-units-3-4-and-fixes
Highlight Units 3 and 4 in table of contents and fix typos
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README.md

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@@ -19,6 +19,8 @@ You can access the course here 👉 [Coming Soon]
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| 0 | Welcome to the Course | Welcome, guidelines, necessary tools, and course overview. |
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| 1 | Introduction to Model Context Protocol | Definition of MCP, key concepts, and its role in connecting AI models with external data and tools. |
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| 2 | Building with MCP: Practical Development | Learn to implement MCP clients and servers using available SDKs and frameworks. |
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| 3 | MCP Protocol Deep Dive | Explore advanced MCP features, architecture, and real-world integration patterns|
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| 4 | Bonus Units & Collaborations | Special topics, partner libraries, and community-driven projects.|
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## Prerequisites
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howpublished = {\url{https://github.com/yourusername/mcp-course}},
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note = {GitHub repository},
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}
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```
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```

units/en/unit0/introduction.mdx

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@@ -54,7 +54,7 @@ Here is the **general syllabus for the course**. A more detailed list of topics
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| 0 | Onboarding | Set you up with the tools and platforms that you will use. |
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| 1 | MCP Fundamentals, Architecture and Core Concepts | Explain core concepts, architecture, and components of Model Context Protocol. Show a simple use case using MCP. |
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| 2 | End-to-end Use case: MCP in Action | Build a simple end-to-end MCP application that you can share with the community. |
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| 3 | Deployed Use case: MCP in Action | Build a deployed MCP application using a the Hugging Face ecosystem and partners' services. |
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| 3 | Deployed Use case: MCP in Action | Build a deployed MCP application using the Hugging Face ecosystem and partners' services. |
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| 4 | Bonus Units | Bonus units to help you get more out of the course, working with partners' libraries and services. |
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## What are the prerequisites?
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### Ben Burtenshaw
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Ben is a Machine Learning Engineer at Hugging Face who focuses building LLM applications, with post training and agentic approaches.
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Ben is a Machine Learning Engineer at Hugging Face who focuses building LLM applications, with post-training and agentic approaches.
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<!-- ## Acknowledgments -->
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