Learn Langchain Architectural components step-by-step and build an AI app from scratch using embeddings, vector stores, retrieval, agents, and LLMs. This video follows the complete LangChain architecture diagram, explaining each component sequentially as data flows through your app. This tutorial covering RAG architecture, vector stores, semantic search, AI agents, LLM integration & tools. Learn to build production-ready AI apps from scratch. 🔗 Related Playlists : Langchain Full Course: Generative AI Full Course : Official Data Scientist Roadmap : Crack Data Science Interview: how to build an app with ai how to make app with ai in mobile how to build software with ai build app with ai tutorial build generative ai applications how to make web app using ai how to make ai app using python how to build ai agents using langchain how to make an ai app like chatgpt how to create android app using ai how to make app with ai and earn money how to make a app without coding with ai langchain explained what is langchain langchain crash course ⏰ Timestamps: 00:00 - How to build AI application from scratch ? 00:40 - 5 Step AI pipeline 00:48 - Processing Raw Input - Foundation 03:08 - Creating Embedding & Storing 05:18 - Retrieving Relevant Context 07:38 - Orchestrating via Agents & Memory 09:25 - Generating Responses from LLM 10:39 - Langchain Component Architecture #langchain #generativeai #datascience #skdneuron #aiagents #rag 👉 Don’t forget to like, share & subscribe 🔔 SKD Neuron that breakdown to help others avoid the same pitfalls!