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AI Agents in LangGraphvsMulti AI Agent Systems with crewAI

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.

DL.AI
DeepLearning.AI

Multi AI Agent Systems with crewAI

The right course if you're committing to a multi-agent architecture. crewAI's role-based pattern (each agent has a job title + goal + tools) reads cleanly and is faster to ship than LangGraph for orchestration-heavy use cases. Free, taught by the founder. Caveat: in 2026, LangGraph has more momentum for production-grade agents; crewAI shines for fast iteration and demo-grade apps. Pick by your priority.

Side-by-side

DimensionAI Agents in LangGraphMulti AI Agent Systems with crewAI
ProviderDeepLearning.AIDeepLearning.AI
Editorial tierHands-on reviewedHands-on reviewed
LevelIntermediateIntermediate
Formatself pacedself paced
Duration~1.5 hours (4 lessons)~1.5 hours (6 lessons)
PricingFreeFree
InstructorHarrison Chase — Founder, LangChainJoão Moura — Founder, crewAI
RatingNo public ratingNo public rating
Topicsbuild ai agents, langchain, langgraphbuild ai agents, ai engineering
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
Multi AI Agent Systems with crewAI
Pros
  • +Founder-taught, role-based pattern is intuitive
  • +Free, 90 minutes, immediate hands-on labs
  • +Fastest path from idea to working multi-agent demo
Cons
  • −crewAI has less production-grade tooling than LangGraph (eval, tracing)
  • −Single-vendor lens — the patterns are crewAI-specific

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
Multi AI Agent Systems with crewAI
Best for
  • · Engineers prototyping multi-agent workflows
  • · Anyone evaluating multi-agent frameworks
Not ideal for
  • · Production-first engineers — LangGraph is the better commitment

Editor's short verdict

Take AI Agents in LangGraph first — it's the editor's pick on this topic. Multi AI Agent Systems with crewAI is a solid alternative; pick it if the format, instructor or price fit you better.

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 Multi AI Agent Systems with crewAI (2026): which course wins? · AI Agent Rank