Vector Databases Courses and Certifications

Scrimba

Build an AI Personal Assistant with a Vector Database

Build "AI-SH", a personal assistant chatbot with HTML, CSS and JavaScript that answers from your own data in a Supabase vector database, plus capture mode and voice interaction.

• Coursera
• 4 hours 29 minutes
• Self-Paced
• Paid Course

Scrimba

Build a Movie Recommendation App with OpenAI

Build Pop Choice, a movie recommendation app that turns user answers into embeddings via the OpenAI API and queries a Supabase vector database for personalized picks.

• Coursera
• 4 hours 35 minutes
• Self-Paced
• Paid Course

Packt

Gen AI - RAG Application Development using LlamaIndex

Build RAG applications with LlamaIndex: craft conversational prompts, store embeddings in Chroma DB, and construct sequential and DAG query pipelines with ReAct and document agents.

• Coursera
• 2 weeks, 5 hours a week
• Self-Paced
• Paid Course

Fractal Analytics

Advanced Data Techniques for Enterprise AI Systems

Design data foundations for generative AI: apply taxonomies, metadata tagging, vector databases, lakehouse architectures, and governance frameworks like DAMA-DMBOK to reduce hallucinations and enforce compliance.

• Coursera
• 6 weeks, 3 hours a week
• Self-Paced
• Paid Course

LearnKartS

MCP Servers & Agentic AI Architecture

Build MCP servers and agentic workflows: define tools, resources, and prompts, wire function calling with Gemini and OpenAI, and add retrieval using ChromaDB and pgVector.

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

Packt

Applied Generative AI & NLP with Python

Build NLP and generative AI applications in Python: GloVe embeddings, sentiment analysis, Hugging Face pipelines, fine-tuning, OpenAI API, prompt engineering, and a RAG chatbot.

• Coursera
• 14 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Understand RAG Basics

Build a minimal RAG pipeline in Python: diagram the retriever, generator, and vector database, embed text, create a local vector store, and ground an LLM with external facts.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

Packt

Preprocessing Unstructured Data for LLMs and RAG Systems

Preprocess HTML, PDF, and PPTX documents with the Unstructured framework: normalize and chunk content, extract metadata, load a vector database, and build a working RAG system.

• Coursera
• 8 weeks, 1 hour a week
• Self-Paced
• Paid Course

Packt

Generative AI with Python

Build generative AI applications in Python: train and fine-tune LLMs with LoRA, code RAG pipelines and vector databases, and orchestrate agents with crewAI, AG2, and Google ADK.

• Coursera
• 15 weeks, 1 hour a week
• Self-Paced
• Paid Course

Starweaver

GenAI for Data Engineers: Build RAG Systems

Build enterprise RAG systems: engineer pipelines that turn raw documents into AI-ready data, architect vector databases for semantic search, and tune retrieval with reranking and metadata filtering.

• Coursera
• 3 weeks, 2 hours a week
• Self-Paced
• Paid Course

LearnKartS

Agentic AI Systems with Vector DBs & RAG

Build agentic AI systems with RAG: set up ChromaDB and pgVector, implement vector ingestion and search in Node.js, and integrate MongoDB schemas via MCP.

• Coursera
• 3 weeks, 5 hours a week
• Self-Paced
• Paid Course

Packt

Gen AI - RAG Application Development using LangChain

Build RAG applications with LangChain: prompt templates, agents, document loaders, vector databases and LCEL, plus projects for SQL data, chatbots and invoice extraction.

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

Board Infinity

RAG from Scratch: Build a Knowledge-Powered Chatbot

Build a production RAG chatbot: generate OpenAI embeddings, chunk PDFs and HTML, compare ChromaDB, FAISS and Pinecone, add hybrid search, reranking, RAGAS evaluation and deployment.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Packt

Building AI Intensive Python Applications

Build generative AI applications in Python: implement LLMs, embedding models, vector databases, RAG with vector search, and evaluation techniques that curb hallucinations and improve reliability.

• Coursera
• 12 weeks, 2 hours a week
• Self-Paced
• Paid Course

Packt

RAG-Driven Generative AI

Build RAG pipelines with LlamaIndex, Deep Lake, Pinecone, and Chroma, adding index-based retrieval, knowledge graphs, multimodal drone data, human feedback loops, and fine-tuning to reduce hallucinations.

• Coursera
• 10 weeks, 2 hours a week
• Self-Paced
• Paid Course