Udemy - Vector Databases for Developers - ChromaDB, Pinecone and ...

Vector Databases for Developers: ChromaDB, Pinecone & RAG

https://WebToolTip.com

Published 8/2026
Created by Sudip Bhattacharyya
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 18 Lectures ( 9h 54m ) | Size: 3.6 GB

Learn Embeddings, Semantic Search, ChromaDB, Pinecone, LangChain & build production-ready RAG applications with Python.

What you'll learn
⚡ Build AI-powered Semantic Search applications using Python, OpenAI Embeddings, ChromaDB, and Pinecone.
⚡ Understand Embeddings, Vector Databases, Cosine Similarity, Chunking, and Semantic Search from scratch.
⚡ Build production-ready Retrieval-Augmented Generation (RAG) applications using LangChain and modern AI workflows.
⚡ Create an AI-powered Semantic PDF Search Engine that searches documents using natural language.
⚡ Develop a complete RAG Chatbot with conversation history, source citations, and intelligent document retrieval.
⚡ Learn how to migrate from ChromaDB to Pinecone for scalable cloud-based vector search applications.
⚡ Optimize vector search systems using better chunking strategies, metadata filtering, Top-K retrieval, and hybrid search concepts.
⚡ Apply production best practices for building scalable AI applications with Vector Databases and Retrieval-Augmented Generation (RAG).

Requirements
❗ Basic Python programming knowledge.
❗ A Windows, macOS, or Linux computer.
❗ Visual Studio Code installed.
❗ An internet connection.
❗ An OpenAI API key (created during the course).
❗ No prior knowledge of AI, Vector Databases, Pinecone, ChromaDB, or LangChain is required.
❗ A willingness to learn by building real-world projects.