Introduction to Building AI RAGs with Python and LangChain
Learn Building AI RAG Systems with Python & LangChain
Created by PythonHow, Ardit Sulce
Discover how to build AI-powered Retrieval Augmented Generation systems using Python and LangChain. You will learn to connect language models with your own data, making them smarter and more accurate for real-world applications. Gain practical experience designing systems that answer questions using your documents.
Packt | Apr 2026 | 84 min
What You Will Learn
You will start by building foundational components like document loaders and embedding generators. Step by step, you will combine these elements to create a complete RAG pipeline. Each topic is taught through practical, hands-on projects so you can directly apply what you learn to your own data and use cases.
Key Features
- Build RAG pipelines that connect language models to your own document data
- Integrate embeddings and vector stores for precise document retrieval
- Design AI systems that generate accurate, source-grounded answers
Target Audience
Perfect for Python developers, data scientists, and AI enthusiasts who want to create smarter AI applications using private or specialized data. If you have a working knowledge of Python and some familiarity with machine learning, you will quickly pick up the skills needed to build and deploy your own RAG systems.
