LangChain's Role in the LLM App Stack
Help learners understand this topic clearly, practice it on a small example, and produce reviewable evidence before moving to the next module.
LangChain for LLM Applications and RAG
A traceable RAG assistant with source citations, structured answers, retrieval evaluation cases, and debugging notes.
Models, Messages, Prompts, and Provider Configuration
Help learners understand this topic clearly, practice it on a small example, and produce reviewable evidence before moving to the next module.
Structured Output and Parsers
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Document Loading, Splitting, and Embeddings
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Vector Stores and Retrievers
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Retrieval Chains with Grounded Responses
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Tools and Simple Agents
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Memory and Session State Boundaries
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Streaming and Callbacks
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Tracing and Debugging with LangSmith
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Testing and Evaluating LangChain Components
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Capstone: Traceable RAG Assistant
Help learners understand this topic clearly, practice it on a small example, and produce reviewable evidence before moving to the next module.
First-release boundary
This is a text-first course shell. Leonardo/image creation, image QC, dependency-heavy runtime QA, external review, and learner pilot evidence remain separate later quality steps.