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Course 2: Basic Agentic AI Concepts
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What you will learn
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(a) Design an agent from its core components
(b) Connect tools through the Model Context Protocol (MCP)
(c) Add short-term and long-term memory that persists across sessions
(d) Ground answers in your own documents with RAG, reranking, and citations
(e) Engineer the context window so the right information arrives at the right time
Why take it
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(a) Turns a chat model into a working agent, one layer at a time
(b) Teaches you which layer is broken when an agent misbehaves
What makes it unique
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(a) One running example, an investment assistant, built across all five modules
(b) Labs run against real APIs and a real vector database, so you see failures before fixes
