Udemy – Build Your Own RAG System with Python, Streamlit & OpenAI

Build your own fully working  AI system that can read your documents and answer questions with accuracy. In this step-by-step project-based course, you will learn how to use Retrieval-Augmented Generation (RAG) to overcome the limitations of traditional AI models. Instead of relying on the model’s memory, you will connect GPT to your own knowledge sources such as PDFs, policies, reports, and business documentation.

You will learn the complete pipeline: document ingestion, chunking, embeddings, vector search, and contextual answer generation. We will combine all of this into a clean, user-friendly Streamlit application that you can run locally or deploy to the cloud. Throughout the course, you will gain hands-on skills in Python, the OpenAI API, semantic search, creating embeddings, designing a chat interface, and deploying applications online.

By the end of the course, you will have built and shipped a working RAG system that you can personalize, extend, and showcase in your portfolio. Whether your goal is automating customer support, improving document access, or creating new AI-powered products, this project gives you a strong foundation for building real-world AI solutions. This course is accessible to beginners, while still offering depth for intermediate learners who want to advance their AI engineering skills.

Enroll today and start building smarter AI that truly understands your documents.

DOWNLOAD LINK: Build Your Own RAG System with Python, Streamlit & OpenAI

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