Learn LangChain and LangGraph by building real world AI Agents (Python, Latest Version 0.3.0+)

What you'll learn
Become proficient in LangChain
Have 3 end to end working LangChain based generative AI applications
Prompt Engineering Theory: Chain of Thought, ReAct, Few Shot prompting and understand how LangChain is build under the hood
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 Databasrs (Pinecone, FAISS)
Model Context Protocol
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
COURSE WAS RE-RECORDED and supports- LangChain Version 0.3+**Ideal students are software developers / data scientists / AI/ML Engineers**Welcome to the AI Agents with LangChain and LangGraph Udemy course - Unleashing the Power of LLM!This course is designed to teach you how to QUICKLY harness the power the LangChain library for LLM applications. This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM solutions for a diverse range of topics.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 .What You'll Build: No fluff. No toy examples. You'll build:Ice Breaker Agent – An AI agent that searches Google, finds LinkedIn and Twitter profiles, scrapes public info, and generates personalized icebreakers.Documentation Helper – A chatbot over Python package docs (and any data you choose), using advanced retrieval and RAG.Slim ChatGPT Code Interpreter – A lightweight code execution assistant.Prompt Engineering Theory SectionIntroduction to LangGraph Introduction to Model Context Protocol (MCP)The topics covered in this course include:AI AgentsLangChain, LangGraphLLM + GenAI HistoryLLMs: Few shots prompting, Chain of Thought, ReAct promptingChat ModelsOpen Source ModelsPrompts, PromptTemplates, langchainubOutput Parsers, Pydantic Output ParsersChains: create_retrieval_chain, create_stuff_documents_chainAgents, Custom Agents, Python Agents, CSV Agents, Agent RoutersOpenAI Functions, Tool CallingTools, ToolkitsMemoryVectorstores (Pinecone, FAISS, Chroma)RAG (Retrieval Augmentation Generation)DocumentLoaders, TextSplittersStreamlit (for UI), CopilotkitLCELLangSmithLangGraphFireCrawlGIST of Cursor IDE Cursor ComposterCurser ChatMCP - Model Context Protocol & LangChain Ecosystem Introduction To LangGraphContext EngineeringThroughout 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 v0.3+ 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).DISCLAIMERSPlease 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.The Ice-Breaker project requires usage of 3rd party APIs-Scrapin, Tavily, Twitter API which are generally paid services.All of those 3rd parties have a free tier we will use to create stub responses development and testing.

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

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