docs: highlight units 3 and 4 in table of contents and fix typos

README.md

@@ -19,6 +19,8 @@ You can access the course here 👉 [Coming Soon]
 | 0       | Welcome to the Course                               | Welcome, guidelines, necessary tools, and course overview.                                              |
 | 1       | Introduction to Model Context Protocol              | Definition of MCP, key concepts, and its role in connecting AI models with external data and tools.     |
 | 2       | Building with MCP: Practical Development            | Learn to implement MCP clients and servers using available SDKs and frameworks.                         |
+| 3       | MCP Protocol Deep Dive                            | Explore advanced MCP features, architecture, and real-world integration patterns|
+| 4       | Bonus Units & Collaborations                    | Special topics, partner libraries, and community-driven projects.|
 
 ## Prerequisites
 
@@ -50,4 +52,4 @@ To cite this repository in publications:
   howpublished = {\url{https://github.com/yourusername/mcp-course}},
   note = {GitHub repository},
 }
-``` 
+```

units/en/unit0/introduction.mdx

@@ -54,7 +54,7 @@ Here is the **general syllabus for the course**. A more detailed list of topics
 | 0       | Onboarding                                  | Set you up with the tools and platforms that you will use.                                                             |
 | 1       | MCP Fundamentals, Architecture and Core Concepts | Explain core concepts, architecture, and components of Model Context Protocol. Show a simple use case using MCP.       |
 | 2       | End-to-end Use case: MCP in Action              | Build a simple end-to-end MCP application that you can share with the community. |
-| 3       | Deployed Use case: MCP in Action               | Build a deployed MCP application using a the Hugging Face ecosystem and partners' services.                                        |
+| 3       | Deployed Use case: MCP in Action               | Build a deployed MCP application using the Hugging Face ecosystem and partners' services.                                        |
 | 4       | Bonus Units                                  | Bonus units to help you get more out of the course, working with partners' libraries and services.                                        |
 
 ## What are the prerequisites?
@@ -116,7 +116,7 @@ About the authors:
 
 ### Ben Burtenshaw
 
-Ben is a Machine Learning Engineer at Hugging Face who focuses building LLM applications, with post training and agentic approaches.
+Ben is a Machine Learning Engineer at Hugging Face who focuses building LLM applications, with post-training and agentic approaches.
 
 <!-- ## Acknowledgments -->