LangChain & LangGraph
Master the most widely-used AI orchestration frameworks. Build production chains, agents, RAG pipelines, and complex stateful workflows with LangGraph.
About This Course
LangChain and LangGraph are the backbone of the majority of production AI applications. This course goes deep — not just the happy path but the debugging, optimization, and advanced patterns that senior AI engineers use. You'll build production-grade pipelines, complex multi-step agents with LangGraph state machines, and learn the framework internals well enough to debug anything. New to LangChain? This course starts from first principles — you don't need prior LangChain experience, only the prerequisites below. LCEL (LangChain Expression Language) is the declarative syntax for composing AI pipelines and is introduced and explained from scratch in module 2.
What You'll Learn
- Build complex LangChain chains and pipelines with LCEL
- Debug LangChain applications with LangSmith tracing
- Design LangGraph state machines for complex agent workflows
- Implement production RAG pipelines using LangChain components
- Build multi-agent systems with LangGraph supervisor patterns
- Optimize LangChain performance with caching and async
- Test and evaluate LangChain applications systematically
- Migrate existing AI code to LangChain patterns
Who Is This For?
Using LangChain in production and want to master it instead of fighting it
Setting up AI infrastructure and choosing the right frameworks for their team
Completed agent and RAG courses and want the framework expertise to build faster
Prerequisites
- Building AI-Powered Applications with APIs
- RAG: Build Knowledge-Powered AI
- AI Agents: Building Autonomous Systems