LangChain- Agentic AI Engineering with LangChain & LangGraph

voska89 · 2026-06-03T04:37:16+0100

LangChain- Agentic AI Engineering with LangChain & LangGraph
Last updated 4/2026
Created by Eden Marco
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 179 Lectures ( 19h 8m ) | Size: 16.8 GB

Build AI Agents with LangChain and LangGraph RAG, Tools, MCP and Production-Ready Agentic AI Systems (Python)
What you'll learn

Become proficient in LangChain

Have end to end working LangChain based generative AI agents

Prompt Engineering Theory: Chain of Thought, ReAct, Few Shot prompting and understand how LangChain is build under the hood

Context Engineering

Understand how to navigate inside the LangChain opensource codebase

Large Language Models theory for software engineers

LangChain: Lots of chains Chains, Agents, DocumentLoader, TextSplitter, OutputParser, Memory

RAG, Vectorestores/ Vector Databases (Pinecone, FAISS)

Model Context Protocol (MCP)

LangGraph
Requirements

This is not a beginner course. Basic software engineering concepts are needed

I assume students will be familiar software engineering subjects such as: git, python, pipenv, environment variables, classes, testing and debugging

No Machine Learning experience is needed.
Description
This course contains the use of artificial intelligence
2026- COURSE WAS RE-RECORDED and supports- LangChain Version 1.2+**Ideal students are software developers / data scientists / AI/ML Engineers**
Welcome to theAgentic AI Engineering with LangChain and LangGraph course.
In this course you will learn how to design and buildAI agents and agentic AI systems using LangChain and LangGraph, the most powerful frameworks for developing modern LLM applications.
Agentic AI Engineering focuses on buildingAI systems that can reason, plan, use tools, and autonomously complete tasks. WithLangChain and LangGraph, you will build production-readyAI agents, RAG systems, and advanced LLM applications.
What is LangChain?
LangChain isan open-source development framework designed to simplify creating applications powered by large language models (LLMs).
UsingLangChain, LangGraph, MCP, and modern LLM frameworks, you will buildproduction-ready AI agents, multi-agent systems, and advanced RAG applications.
Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python. I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts .
You will buildreal-world Agentic AI systems using LangChain and LangGraph

Search Agent

Documentation Helper - A chatbot over Python package docs (and any data you choose), using advanced retrieval and RAG.

Prompt Engineering Theory

Context Engineering Theory

Introduction to LangGraph

Model Context Protocol (MCP)

Deep Agents
Agentic AI Engineering Topics Covered
Agentic AI Fundamentals

AI Agents

Agentic AI architectures

Multi-agent systems

AI engineering principles
LLM and Prompt Engineering

Prompt Engineering

Few-Shot Prompting

Chain of Thought

ReAct prompting

Context Engineering
Agent Frameworks

LangChain

LangGraph

Model Context Protocol (MCP)

Tool Calling
AI Agent Infrastructure

Vector databases (Pinecone, FAISS, Chroma)

Retrieval Augmented Generation (RAG)

Memory systems

LangSmith tracing
Throughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LangChain to create powerful, efficient, and versatile LLM applications for a wide array of usages.
Why This Course?

Up-to-date: Covers LangChain V.1+ and the latest LangGraph ecosystem.

Practical: Real projects, real APIs, real-world skills.

Career-boosting: Stay ahead in the LLM and GenAI job market.

Step-by-step guidance: Clear, concise, no wasted time.

Flexible: Use any Python IDE (Pycharm shown, but not required).
This course is ideal for developers who want to learnAgentic AI Engineering,AI agents with Python, andLLM application development.
You will learn how to designagent architectures, implementtool-using agents, and buildscalable agentic AI systems using LangChain and LangGraph.
DISCLAIMERS

Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python.
I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts.
Who this course is for

Software Engineers that want to learn how to build Generative AI based applications with LangChain and LangGraph

Developers that want to learn how to build Generative AI based applications with LangChain and LangGraph

Engineers that want to learn how to build Generative AI based applications with LangChain and LangGraph
Homepage

Code:

https://www.udemy.com/course/langchain

LangChain- Agentic AI Engineering with LangChain & LangGraph

voska89

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