LangChain 1.x : Agentic AI & RAG Made Clear

AI is everywhere right now. Some people are excited about it, some are tired of hearing about it—but one thing is clear: it’s becoming hard to ignore. New AI tools and applications are showing up all the time, and companies are increasingly looking for people who understand this space. But for many learners, the biggest challenge is knowing where to actually begin. Maybe you’ve used AI tools. Maybe you’ve watched videos. Maybe you understand some concepts. But building a real AI application can still feel overwhelming. That’s exactly why I created this course. This is a beginner-friendly, hands-on course designed to help you move from understanding concepts to actually building AI applications using LangChain. I’ve tried to keep explanations simple and practical, using visual illustrations wherever helpful, so complex topics feel easier to understand. And instead of just talking about concepts, we apply them step by step by building real projects. What makes this course different? Beginner-friendly explanations in simple language Visual, cartoon-style illustrations to make concepts easier to grasp Learn by building AI applications, not just watching theory What you’ll learn AI Foundations AI basics Models, prompting, agents OpenAI Python SDK Build your first chatbot Core LangChain Messages Chains Prompt templates Build an "Interview Preparation App" Runnables Build workflows using runnables Enhance the "Interview Preparation App" using Runnables Agentic AI Tools Agents Structured outputs Enhance the "Interview Preparation App" using Agents/Tools Advanced Features Streaming Middleware Guardrails RAG Documents → Embeddings → Vector stores → Retrieval Chain-based RAG vs Agentic RAG Build a "Chat with Your PDF" application By the end of this course You won’t just understand the concepts—you’ll be able to build AI applications with LangChain.