Course
Agentic Systems with LangGraph
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Prerequisites
LLM Application Fundamentals with LangChainLLM Application Evaluation with LangSmithLLM Tool Use with LangChainAgentic Systems
Autonomous Agents
You will learn to understand AI agents — from their defining characteristics, key components, and operational patterns — enabling you to recognize when agentic systems are the right approach and understand how they differ from traditional chatbots.
Agency vs Reliability
You will learn to evaluate the tradeoff between agent autonomy and system reliability — understanding why pure ReAct agents fail on complex tasks, how task decomposition improves reliability, and how to identify the right balance point for your application.
Agentic Workflows
You will learn to design and implement reliable agentic workflows using task decomposition patterns — mastering chaining, routing, parallelization, reflection, and code delegation — to build production-ready systems that balance autonomy with predictable performance.
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FAQs
What are the prerequisites for this LangGraph course?
You need Intermediate Python for Developers, Introduction to Python for Developers, plus three LangChain courses covering fundamentals, tool use, and evaluation with LangSmith.
How long is this course and how is it structured?
It has 4 chapters with 20 exercises and an estimated 180 minutes of content. Each chapter builds toward designing agentic systems using the LangGraph framework.
What is LangGraph and why would I learn it?
LangGraph is a framework for building agentic AI systems on top of LangChain. It lets you design workflows where language models act as autonomous agents that plan and execute tasks.
Does this course require prior experience with LangChain?
Yes. Three LangChain prerequisite courses are listed, covering application fundamentals, tool use, and evaluation. Familiarity with those concepts is expected before starting.
What programming language is used throughout the course?
The course uses Python. All exercises and examples are written in Python, building on intermediate-level Python development skills.
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