Udemy – Master RAG: Ultimate Retrieval-Augmented Generation Course 2024-7

Published on: 2024-08-15 20:17:14

Categories: 28

Description

Master RAG Course: Ultimate Retrieval-Augmented Generation Course. This course is an in-depth look into the world of Retrieval Content (RAG) systems. If your goal is to build powerful applications based on artificial intelligence and exploit language models, this course is suitable for you. This course is perfect for anyone who wants to acquire the skills necessary to develop smart applications based on information retrieval. This hands-on course walks you through the core concepts of the RAG architecture, explores various frameworks, and provides a thorough understanding and hands-on experience in building advanced RAG systems.

What you will learn

Developing applications based on large linguistic models (LLM): understanding the core concepts and capabilities of large linguistic models and exploring high-level frameworks that facilitate retrieval and production-based tasks.
Optimizing and Scaling RAG Pipelines: Learn best practices for optimizing and scaling RAG pipelines using LangChain, including indexing, partitioning, and retrieval optimization techniques.
Advanced RAG Techniques: Improving RAG systems with pre-retrieval and post-retrieval optimization techniques and learning to optimize retrieval by query transformation and decomposition.
Document Converters and Segmentation Strategies: Understanding strategies for intelligent text segmentation, handling big data, and improving document indexing and embedding.
Debugging, testing, and monitoring applications based on large language models: Using LangSmith to debug, test, and monitor applications based on large language models, evaluating each component of the RAG pipeline.
Building multi-agent applications based on large language models: developing complex state-based applications using LangGraph, enabling multi-agent collaboration in data retrieval and generation tasks.
RAG quality improvement: learning to process unstructured data, extract elements such as tables and images from PDF files, and integrate GPT-4 Vision to identify and describe elements within images.

This course is suitable for people who

Python developers who want to build AI-based applications using large language models using high-level libraries and APIs.
Machine learning engineers looking to improve their skills in RAG techniques.
Students and enthusiasts who are eager to enter the world of RAG systems and gain hands-on experience with practical examples.
Tech entrepreneurs and AI enthusiasts looking to build recovery-based smart applications and explore new business opportunities in AI.