Similarity Search Courses and Certifications

Coursera Credential

Vector DB Foundations, Embeddings & Search Algorithms

Master vector databases, embeddings, and semantic search algorithms to build advanced retrieval systems and multimodal search applications with hands-on Python projects.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course

Coursera

Grasp Vector DB Basics

Discover how vector databases enable semantic search and AI applications through embeddings, similarity-based retrieval, and strategic decision-making for modern data solutions.

• Coursera
• 1 hour 43 minutes
• Self-Paced
• Paid Course

Programming Generative AI: Unit 3

Master multimodal AI by exploring contrastive language-image pre-training, latent diffusion models, and text-to-image generation with hands-on fine-tuning techniques.

• Coursera
• 8 hours 17 minutes
• Self-Paced
• Paid Course

Coursera Credential

Chroma, Weaviate & Production RAG Deployment

Master vector databases and RAG deployment with Chroma and Weaviate, building production-ready search systems with advanced patterns, security, and optimization techniques.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses

LearnKartS

Build Production AI Agents with RAG & MCP

Master building production-ready AI agents using RAG & MCP, integrating Gemini and OpenAI with Node.js backends, embeddings, semantic search, and scalable architectures for real-world applications.

• Coursera
• 11 hours 31 minutes
• Self-Paced
• Paid Course

Coursera Credential

Vector Databases for Machine Learning: A Comprehensive Guide

Master vector databases, build semantic search and RAG systems, and implement Chroma & Weaviate to advance careers in ML engineering, AI infrastructure, and data science.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 5 courses

Coursera

Vector Database Foundations and Core Concepts

Master vector database technologies, from generating embeddings and similarity metrics to implementing ANN search and HNSW optimization for semantic search and RAG systems.

• Coursera
• 12 hours
• Self-Paced
• Paid Course

Packt

Getting Started with Vector Databases and AI Embeddings

Unlock vector databases and AI embeddings to build smarter AI systems with semantic search, recommendation engines, and RAG applications through hands-on practice.

• Coursera
• 4 hours 24 minutes
• Self-Paced
• Paid Course

RAG: Vector Databases and Retrievers

Master advanced RAG techniques using FAISS, ChromaDB, and modern retrievers while building high-performance search applications with LangChain and LlamaIndex, and Gradio.

• edX
• 5 hours
• Self-Paced
• Free Online Course (Audit)

Board Infinity

RAG Systems & Agentic Workflows with Pinecone and LangGraph

Master RAG pipelines, vector databases, and agentic workflows using Pinecone, LangChain, and LangGraph to build production-ready AI systems with memory, semantic search, and observability.

• Coursera
• 19 hours 21 minutes
• Self-Paced
• Paid Course

LearnKartS

Advanced Agentic AI: Production Data Architecture

Master building production-ready Agentic AI systems with RAG pipelines, pgVector, PostgreSQL, and MongoDB—creating scalable, end-to-end architectures for real customer and order workflows.

• Coursera
• 8 hours 9 minutes
• Self-Paced
• Paid Course

Packt

Harnessing LLMs & Text-Embeddings API with Google Vertex AI

Master Google Vertex AI's LLMs and Text-Embeddings API for building intelligent applications with semantic search, classification, and RAG systems through hands-on projects and real-world use cases.

• Coursera
• 4 hours 16 minutes
• Self-Paced
• Paid Course

Board Infinity

Advance Multi-Agent Systems & Production AI with LangSmith

Master multi-agent AI systems using LangSmith, LangChain, and ChromaDB. Build RAG pipelines, vector databases, conversational agents, and production-ready workflows with observability and optimization tools.

• Coursera
• 15 hours 43 minutes
• Self-Paced
• Paid Course

RAG: Vector Databases with ChromaDB

Learn vector databases, similarity search, and ChromaDB operations to build recommendation systems, and improve AI retrieval performance in GenAI applications using embeddings.

• edX
• 18 hours
• Self-Paced
• Free Online Course (Audit)

Configuring Vector Search in AlloyDB

Discover how to set up and implement vector search capabilities in AlloyDB through hands-on practice in the Google Cloud console.

• Coursera
• 1 hour
• Self-Paced
• Paid Course