Build an AI Chatbot with Python Using RAG, LangChain, Ollama

Partner: Udemy
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Description: Course Description:Welcome to "Building a RAG Application with Ollama, LangChain, and Vector Embeddings in Python"! This hands-on course is designed for Python developers, data scientists, and AI enthusiasts looking to dive into the world of Retrieval-Augmented Generation (RAG) and learn how to build intelligent document-based applications.In this course, you will learn how to create a powerful PDF Q&A chatbot using state-of-the-art AI tools like Ollama, LangChain, and Vector Embeddings. You'll gain practical experience in processing PDF documents, extracting and generating meaningful information, and integrating a local Large Language Model (LLM) to provide context-aware responses to user queries.What you will learn:What is RAG (Retrieval-Augmented Generation) and how it enhances the power of LLMsHow to process PDF documents using LangChainExtracting text from PDFs and splitting it into chunks for efficient retrievalGenerating vector embeddings using semantic search for better accuracyHow to query and retrieve relevant information from documents using Vector DBIntegrating a local LLM with Ollama to generate context-aware responsesPractical tips for fine-tuning and improving AI model responsesCourse Highlights:Step-by-step guidance on setting up your development environment with VS Code, Python, and necessary libraries.Practical projects where you’ll build a fully functional PDF Q&A chatbot from scratch.Hands-on experience with Ollama (a powerful tool for running local LLMs) a
Category: IT & Software > Other IT & Software > Retrieval Augmented Generation (RAG)
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Price: 44.99
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Source: Impact
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