June 2, 2026

Langchain- Agentic Ai Engineering With Langchain & Langgraph

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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

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

Tags:Agentic, AI, Engineering, LangChain, Langgraph

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Langchain- Agentic Ai Engineering With Langchain & Langgraph

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