Complete RAG Crash Course With Langchain In 2 Hours

Learn how Retrieval-Augmented Generation (RAG) lets you boost any large language model by plugging in an external knowledge base—no retraining required. In this two-hour crash course (including hands-on code from the GitHub repo), you’ll see how RAG keeps your model’s answers accurate, up-to-date, and grounded in your own data.

Whether you’re building domain-specific bots or just want more reliable AI output, this tutorial shows you how to tap into internal docs or specialized datasets using LangChain. It’s a cost-effective way to supercharge your LLM for real-world applications.

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