Vector Databases Courses and Certifications

Learn RAG

Learn how to improve the accuracy and reliability of LLM-based apps by implementing Retrieval-augmented Generation (RAG) using embeddings and a vector database.

• Scrimba
• 1 hour 34 minutes
• Self-Paced
• Paid Course

Free Intro to Mistral AI Tutorial: Learn to build intelligent apps in this course by Mistral AI and Scrimba

1 rating

Learn how to use the Mistral AI to build intelligent apps, all the way from simple chat completions to advanced use-cases like RAG and function calling. Created

• Scrimba
• 1 hour 24 minutes
• Self-Paced
• Free Online Course

JetBrains

Build a Local AI Assistant with LLMs

8 ratings

Master building a local AI assistant using RAG pipelines, FastAPI, Ollama, and Qdrant — processing PDFs into vector embeddings and creating a browser-based Q&A interface, all running privately on your machine.

• Coursera
• 6 weeks, 4 hours a week
• Self-Paced
• Paid Course

Optimize RAG with AI Agents and Vector Databases

Discover how AI agent systems and vector databases optimize RAG pipelines, improving query accuracy and context retrieval for smarter AI solutions that tackle complex challenges.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Kode Kloud

AI Agents Fundamentals - LLMs, LangChain, RAG, and Vector Databases

Master AI agent fundamentals from LLMs to RAG systems through hands-on labs. Build production-ready AI workflows with LangChain, vector databases, and advanced prompt engineering techniques.

• YouTube
• 57 minutes
• Self-Paced
• Free Video

WeAreDevelopers

Machine Learning Day: From Generative AI to Vector Databases

Explore cutting-edge Machine Learning topics with expert talks on multimodal generative AI, OpenAI embeddings, vector databases, and building products in the GenAI era.

• YouTube
• 4 hours 7 minutes
• Self-Paced
• Free Video

Discover AI

Building a Multi-AI System: Upgrading Vector Databases with BERT and GPT-4

Master building a cost-effective multi-AI system by integrating GPT-4 and BERT, transforming vector databases into interactive AI components with or without LangChain framework.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

LLMOps Space

Advanced RAG: Chunking, Embeddings, and Vector Databases

Explore advanced RAG concepts: chunking for efficient retrieval, embeddings for text representation, and vector databases for optimized storage and retrieval in LLM applications.

• YouTube
• 50 minutes
• Self-Paced
• Free Video

AWS Events

Enhancing Search on AWS with AI, RAG, and Vector Databases - Level 300

Dive into advanced search enhancement techniques using AI, RAG, and vector databases on AWS, leveraging Amazon Bedrock, Aurora, and LangChain for improved user experiences and innovative solutions.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Career Certificate

Foundations of Retrieval Augmented Generation (RAG) Systems

266 ratings at CodeSignal

Master RAG systems fundamentals: vector databases, semantic retrieval with embeddings, and building complete pipelines to enhance text generation accuracy.

• CodeSignal
• 4 hours
• Self-Paced
• Free Certificate
• 4 courses

The AI Engineer Course 2026: Complete AI Engineer Bootcamp

18761 ratings at Udemy

Complete AI Engineer Training: Python, NLP, Transformers, LLMs, LangChain, Hugging Face, APIs

• Udemy
• 1 day 5 hours 41 minutes
• Self-Paced
• Paid Course

AWS Events

Build GPU-Boosted, Auto-Optimized, Billion-Scale Vector Databases in Hours - ANT213

Discover how to build billion-scale vector databases in under an hour using Amazon OpenSearch Service's GPU-acceleration and auto-optimization features for AI applications.

• YouTube
• 50 minutes
• Self-Paced
• Free Video

AWS Events

What's New in Search, Observability, and Vector Databases with OpenSearch - ANT201

Explore Amazon OpenSearch Service's latest launches for agentic AI applications, vector search, Amazon Q integrations, and cost optimization features.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

GeeCON Conference

From Words to Wisdom - How LLMs and Vector Databases Revolutionize Data

Explore how LLMs and vector databases work together through vectorization, semantic search, and real-time retrieval using Kotlin and LangChain4j in practical demonstrations.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Venelin Valkov

How RAG Finds Answers in Millions of Documents - Embeddings, Vector Databases, LangChain and Supabase

Master building semantic search systems that scale to millions of documents using embeddings, vector databases, and LangChain for powerful RAG applications.

• YouTube
• 21 minutes
• Self-Paced
• Free Video