LangChain Masterclass: Build Production-Ready LLM Apps, RAG & Agents

Complete hands-on guide to LangChain – the most popular framework for building LLM-powered applications, RAG systems, chatbots, and AI agents. Whether you're a data scientist, ML engineer, full-stack developer, or AI enthusiast, this playlist takes you from zero to production: What you'll build and master: Core LangChain concepts: Chains, prompts, tools, memory, retrievers RAG pipelines: Document indexing, vector stores (FAISS, Pinecone, Qdrant), semantic search AI Agents: Tool-using agents, multi-tool assistants, agentic workflows Production skills: Tracing, evaluation, deployment, cost optimization ?? Phase 1: Foundations (Setup, Chains, Tools) ?? Phase 2: RAG Masterclass (Retrieval-Augmented Generation) ?? Phase 3: Agents & Tool Use ?? Phase 4: Observability & Production ?? Phase 5: LangChain Ecosystem (LangGraph, LangSmith) ?? Phase 6: Real-World Projects Perfect for: ? Building internal tools and AI copilots ? Creating chatbots with long-term memory ? Implementing semantic search over documents ? Launching production AI apps (not just demos) Why this playlist? Code-first approach with real-world examples Step-by-step projects you can deploy Production patterns (monitoring, evaluation, cost) Latest tools & integrations (2025+ stack) Tech Stack Covered: ??? LangChain + LangGraph + LangSmith ?? Vector DBs: FAISS, Pinecone, Qdrant, Milvus ?? LLMs: OpenAI, Anthropic, local models ?? Deployment: FastAPI, Docker, cloud Subscribe & turn on notifications for bonus content and updates! #LangChain #RAG #AIAgents #LLMApps #MachineLearning