Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Building a Scalable AI Chatbot with Wikipedia Data - Semantic Search and RAG

Kunal Kushwaha via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Learn how to build a scalable AI-powered chatbot using Wikipedia video game data in this comprehensive tutorial. Explore the implementation of semantic search and Retrieval-Augmented Generation (RAG) with SingleStore, optimize performance using vector indexes, and integrate OpenAI's GPT models to create an interactive, data-driven chat experience. Follow along as the instructor guides you through database setup, mock vector generation, data retrieval from Wikipedia, vector index construction, index testing, hybrid search implementation, and the final chatbot integration. Gain practical insights into building advanced AI applications with real-world data sources and cutting-edge technologies.

Syllabus

Introduction
Database setup
Generating the mock vectors
Getting the Wikipedia video game data
Building the vector indexes
Testing our indexes
Hybrid search in SingleStore
Chatting with the video game data
Closing remarks

Taught by

Kunal Kushwaha

Reviews

Start your review of Building a Scalable AI Chatbot with Wikipedia Data - Semantic Search and RAG

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.