LangChain & LangGraph AI Engineer: Agents, Agentic RAG & MCP (Udemy)

Our take

LangChain- Agentic AI Engineering with LangChain & LangGraph is a beginner LangChain course from Eden Marco on Udemy. It runs about 9.5h, was last updated in 10/2026, and holds 4★ from 1,102 students — one of the stronger Udemy course reviews entries in LangChain.

Best for: beginner learners who want one guided path through LangChain. Skip it if: You already work professionally in LangChain and need advanced architecture patterns.

📘 What you will learn

• Build LLM chains, agents and RAG pipelines with LangChain
• Master LangGraph for stateful, multi-step agent workflows
• Connect models, tools, vector stores and memory correctly
• Ship a portfolio project with evaluation and guardrails

📑 Course content

6 sections · 37 lectures · 9.5h of video · updated 10/2026

1. Introduction & environment setup — 4 lectures · 0.7h
2. Prompting, models and chains — 7 lectures · 1.5h
3. Memory, tools and retrieval (RAG) — 8 lectures · 2.0h
4. Agents with LangGraph — 9 lectures · 2.4h
5. Evaluation, debugging and cost control — 5 lectures · 1.2h
6. Capstone project & deployment — 4 lectures · 1.7h

🎯 Who it is for

Suits: Complete beginners, career switchers, and self-taught devs who want structure.

Needs: A computer with internet. No prior experience needed.

📊 Quality score

Content ⭐ 3.8 · Video ⭐ 4.2 · Instructor ⭐ 4.2 · Pace ⭐ 4.1 · Depth ⭐ 4.2

Overall: 82 / 100 — based on student ratings and review depth.

👤 Instructor

Eden Marco — Eden Marco teaches LangChain on Udemy with a practical, project-first style. Their courses are consistently among the highest rated in our Udemy course reviews for LangChain.

❓ FAQ

Worth it

Clear explanations and plenty of exercises. The LangChain update feels fresh, and the pace is manageable even with a full-time job.

Solid course

Well-structured content with real examples. I applied it at work the same week and it immediately paid for itself.