Advanced LLMs with Retrieval Augmented Generation (RAG): Practical Projects for AI Applications

سرفصل های دوره

Are you an engineer, solutions architect, or software developer tasked with building enterprise applications? It’s time to get up to speed with the latest AI-powered tools and techniques—in this case, retrieval-augmented generation (RAG). In this course, designed by leading technology educator Pragmatic AI Labs, join instructor Guy Ernest as he outlines the foundational and advanced concepts required to leverage RAG for large language models, including text encoding using embedded vectors, document chunking with enrichment strategies, improving document retrieval, and more. By the end of this course, you’ll be equipped with the skills you need to take advantage of the power of RAG.

01 - Introduction

01 - Course introductions

02 - Understanding the basics of RAG

03 - Building a simple RAG example

04 - Issues with simple RAG

02 - 1. Text Encoding Using Embedding Vectors

01 - Embedding introduction

02 - Hands-on lab Embedding tokenization

03 - Hands-on lab Embedding vocabulary

04 - Hands-on lab Sentence embedding

05 - Hands-on lab Content embedding

06 - Embedding notebook summary

03 - 2. Document Chunking and Enrichment Strategies

01 - Chunking introduction

02 - Hands-on lab Semantic chunking

03 - Chunking overview

04 - Hands-on lab Contextual retrieval

05 - Query document alignment

06 - Hands-on lab Reverse HyDE

04 - 3. Improving Document Retrieval

01 - Hybrid search introduction

02 - Hands-on lab Hybrid search

03 - Hands-on lab Reranking

04 - Multimodal retrieval introduction

05 - Hands-on lab Multimodal PDF retrieval

139,000 تومان

افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: LinkedIn Learning (Lynda)