LangChain- Agentic AI Engineering with LangChain & LangGraph
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.
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
Download Links
11.64 GB Total Size