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AI 201CoreL1 + L2 Certificates

Model Context Protocol: Connecting AI to Tools & Trusted Data

From using AI to letting AI use tools and trusted data safely: understand MCP architecture, trace a tool call, compare MCP, APIs and RAG, and design an implementable MCP Tool Canvas.

7 hours5 modules中文 / EnglishLast verified

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AI 201 · Module 1: Why MCP?

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Curriculum

  1. Module 1Why MCP?AI is already capable, so why does it need a standard way to reach tools?Not started0 / 5 · about 60 min
  2. Module 2MCP ArchitectureHow Host, Client, Server, Tool and the trusted data source fit together.Not started0 / 5 · about 60 min
  3. Module 3Tool Discovery & Tool CallsTrace how AI discovers a tool, prepares arguments, gets a result and answers.Not started0 / 6 · about 60 min
  4. Module 4MCP vs API vs RAGPick the right pattern for the scenario, and stop treating MCP as an API replacement.Not started0 / 5 · about 60 min
  5. Module 5Security, Grounding & ProvenancePermission, risk, source tracing and human confirmation: the core module of the course.Not started0 / 6 · about 60 min

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Practice and assessment

About this course

Outcomes

  • Explain what MCP is for and the roles of Host, Client, Server and Tool
  • Trace a full tool call, from the request to a human-verified answer
  • Choose between prompt-only, RAG, API and MCP tool for a given scenario
  • Check a tool output for source, freshness and provenance
  • Complete an MCP Tool Canvas covering schema, permission, risk and provenance

We suggest finishing AI 101 first. This is a suggestion only and never blocks you from starting.

Certificate

Earns a course completion certificate (L1); a capability certificate (L2) is also available through additional artifact review.

Requirements to earn it

  • Complete all 5 course modules
  • Pass the post-test assessment at 80% or higher
  • Submit a project artifact and pass review

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