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Introduction to Retrieval Augmented Generation (RAG)
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.
Duration
5 Months
Institution
Duke University
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Duke University.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$123
Total Est. Investment
$123
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the Introduction to Retrieval Augmented Generation (RAG) program at Duke University are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.