courseraПрограммирование

Introduction to Retrieval Augmented Generation (RAG)

Курс от Duke University

Средний≈ 5.2 чАнглийский

О курсе

In this 2-hour project-based course, you will learn how to import data into Pandas, create embeddings with SentenceTransformers, and build a retrieval augmented generation (RAG) system with your data, Qdrant, and an LLM like Llamafile or OpenAI. This hands-on course will teach you to build an end-to-end RAG system with your own data using open source tools for a powerful generative AI application.

Навыки, которые вы освоите

Retrieval-Augmented Generation Vector Databases Large Language Modeling Pandas (Python Package)Data Processing Machine Learning Embeddings Data Management OpenAI API Application Programming Interface (API)Generative AI Data Import/Export Python Programming

Программа курса

1 модулей · 10 учебных материалов

01Project Overview10 материалов

Retrieval Augmented Generation

Project OverviewЧтение Key TermsЧтение Manage Data for embeddingsВидео Verifying embeddings and searchВидео

Учитесь у экспертов

Alfredo Deza

Adjunct Assistant Professor in the Pratt School of Engineering