Overview
Curriculum
In this module, we’ll explore key features together, including the LangChain Expression Language (LCEL), Runnables, memory, RAG, prompt templates, and agents. We’ll also get hands-on with LangGraph to build stateful workflows and use callbacks to track execution. By working through real-world examples like document processing and decision-making, we’ll learn how to create efficient, scalable, and context-aware AI solutions.
What You'll Learn
- Understand workflows for LLM-powered applications using LangChain’s orchestration framework
- Build and combine components like prompt templates, output parsers, memory, and retrieval to create dynamic chains
- Implement agentic behavior and decision-making using LangChain agents and LangGraph
- Use LCEL and callbacks to design, debug, and optimize modular and stateful LLM applications
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