🔥 LangChain From Zero to Hero | Complete Practical Guide with RAG, Chains, Tools & Agents

Description

Welcome to this complete LangChain tutorial from scratch to advanced, where I guide you through every component of LangChain — step-by-step with real-world examples and coding demonstrations. Whether you're a beginner exploring LLMs or a developer building intelligent AI systems, this video will help you master LangChain — the framework powering enterprise-level AI applications. 📚 What You’ll Learn: ✅ LangChain Core Concepts — Prompts, Chains, and Agents ✅ Working with OpenAI and Hugging Face Models ✅ Building RAG (Retrieval-Augmented Generation) Systems ✅ Using Vector Databases (FAISS, Pinecone) for Context Retrieval ✅ Implementing Tools, Memory, and Output Parsers ✅ Understanding LangGraph and LangSmith (Monitoring & Tracing) ✅ Designing Production-Ready AI Pipelines 🧰 Tech Stack: LangChain (latest version) Python FAISS / Pinecone OpenAI API Hugging Face models 💬 About This Channel: I’m Bilal Ahmed, an aspiring AI Engineer & ML Intern, passionate about building intelligent AI systems that connect LLMs, data, and reasoning. Follow my journey on: 🔗 GitHub: github.com/BilalAhmed7072 🔗 LinkedIn: linkedin.com/in/bilal-ahmed-392973268/ #LangChain #AIwithBilal #LLM #RAG #OpenAI #MachineLearning #AIEngineering #FAISS #LangGraph #LangSmith #aiapplications