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AI Agents in LangGraphvsIntroduction to LangGraph (LangChain Academy)

Side-by-side comparison on level, duration, pricing, instructor, tier. Editor verdict on which course wins for which buyer.

DL.AI
DeepLearning.AI

AI Agents in LangGraph

The shortest path from 'I read about agents' to 'I built one that works.' Harrison Chase walks through LangGraph's state machine model end-to-end — agentic loop, tool use, persistent state, human-in-the-loop. Free, ~90 minutes, and the only short course we recommend ahead of a longer specialization. Limitation: it assumes Python comfort and skips over LLM fundamentals. Pair it with the LLM Fundamentals course below if you're new to the field.

LC
LangChain Academy

Introduction to LangGraph (LangChain Academy)

The official deeper-dive into LangGraph from LangChain Academy. Where the DeepLearning.AI short covers basics in 90 minutes, this one goes 6-8 hours into state, persistence, human-in-the-loop, streaming, and the LangGraph Cloud deployment story. Free, taught by LangChain engineering. The canonical follow-up after the DL.AI short course if you're committing to LangGraph for production.

Side-by-side

DimensionAI Agents in LangGraphIntroduction to LangGraph (LangChain Academy)
ProviderDeepLearning.AILangChain Academy
Editorial tierHands-on reviewedHands-on reviewed
LevelIntermediateIntermediate
Formatself pacedself paced
Duration~1.5 hours (4 lessons)~6-8 hours (8 modules)
PricingFreeFree
InstructorHarrison Chase — Founder, LangChainLance Martin — LangChain Engineering
RatingNo public ratingNo public rating
Topicsbuild ai agents, langchain, langgraphlangchain, langgraph, build ai agents
Last verified2026-05-232026-05-24

Pros & cons

AI Agents in LangGraph
Pros
  • +Built and taught by LangChain founder — most authoritative source possible
  • +Free, ~90 minutes, immediate hands-on labs
  • +Covers state, tools, HITL, persistence — the actual building blocks
Cons
  • −Skips LLM basics — assumes you know what a token / context window is
  • −No certificate — bad for resume-padding, fine for actual learning
Introduction to LangGraph (LangChain Academy)
Pros
  • +Official deep-dive from LangChain Academy
  • +Free, 6-8 hours of structured content
  • +Covers production patterns (persistence, HITL, streaming, LangGraph Cloud)
Cons
  • −LangGraph-only — no comparison to crewAI / AutoGen alternatives
  • −Pre-reqs: comfortable with LangChain basics

Which course is for whom?

AI Agents in LangGraph
Best for
  • · Engineers who have used the OpenAI API but never built an agent loop
  • · PMs who want to understand how agents actually work under the hood
Not ideal for
  • · Complete beginners — start with LLM Fundamentals first
  • · People who need a certificate — this course doesn't issue one
Introduction to LangGraph (LangChain Academy)
Best for
  • · Engineers committed to LangGraph for production agents
  • · Anyone past the DL.AI short course wanting production depth
Not ideal for
  • · Beginners evaluating frameworks — take the DL.AI short course first

Editor's short verdict

These cover different primary topics — AI Agents in LangGraph focuses on build ai agents while Introduction to LangGraph (LangChain Academy) focuses on langchain. Take the one matching your current goal first; the other can come later if your interests expand.

DL.AIHands-on reviewedEditor's pick
DeepLearning.AI

AI Agents in LangGraph

For: Engineers who have used the OpenAI API but never built an agent loop

Intermediate · ~1.5 hours (4 lessons) · Free
ReviewOpen free →

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AI Agents in LangGraph vs Introduction to LangGraph (LangChain Academy) (2026): which course wins? · AI Agent Rank