Vector Databases Courses and Certifications

LearnKartS

Agentic AI Systems with Vector DBs & RAG

Master building Agentic AI systems using RAG, pgVector, and ChromaDB to create adaptive, real-time AI that retrieves data dynamically and makes autonomous decisions for production-ready applications.

• Coursera
• 13 hours 51 minutes
• Self-Paced
• Paid Course

Packt

RAG-Driven Generative AI

Master RAG pipelines using LlamaIndex, Deep Lake, and Pinecone to build scalable, context-aware AI systems that minimize hallucinations and optimize performance for real-world applications.

• Coursera
• 15 hours 59 minutes
• Self-Paced
• Paid Course

Packt

Building AI Intensive Python Applications

Master generative AI application development with Python, covering LLMs, vector databases, and frameworks to build intelligent, reliable AI-powered solutions.

• Coursera
• 1 day 1 hour 51 minutes
• Self-Paced
• Paid Course

Coursera

Document and Evaluate LLM Prompting Success

Discover how to transform LLM prototypes into reliable production systems through operational documentation, systematic prompt evaluation, and data-driven optimization strategies.

• Coursera
• 1 hour 52 minutes
• Self-Paced
• Paid Course

Coursera

Evaluating LLM Performance and Efficiency

Discover how to transform LLM prototypes into cost-effective production services through systematic evaluation, optimization, and operational excellence frameworks.

• Coursera
• 8 hours 32 minutes
• Self-Paced
• Paid Course

Coursera

RAG Systems and Production Operations

Master RAG systems from foundational architecture to production-grade deployment, implementing Self-RAG, Corrective RAG, secure vector DBs, and optimized pipelines for enterprise AI applications.

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

Coursera

Boost RAG with Chroma

Master RAG implementation with Chroma to reduce LLM hallucinations through hands-on pipeline building, vector databases, and systematic evaluation of factual improvements.

• Coursera
• 3 hours 42 minutes
• Self-Paced
• Paid Course

Coursera

Weaviate Database Mastery

Master Weaviate's vector database with Docker deployment, schema design, hybrid search, multimodal pipelines, and enterprise-scale tuning to build production-ready AI search systems.

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

Packt

Generative AI for Cloud Solutions

Explore how Generative AI transforms cloud solutions through LLMs, fine-tuning, RAG, prompt engineering, and scalable deployment architectures for real-world applications.

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

Coursera

Launching Your Vector Database Career

Unlock strategies to translate vector database and RAG skills into career opportunities, craft compelling resumes, and ace ML engineering interviews at the skilled professional level.

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

Coursera

Build Chroma Search

Master semantic search by building a real-world Chroma-powered search engine, deploying a Flask API, and evaluating performance using MRR and precision@5 metrics.

• Coursera
• 2 hours 46 minutes
• Self-Paced
• Paid Course

Coursera

Unlock Multimodal Search

Explore how to build AI-powered multimodal search using Weaviate, enabling cross-modal queries across images and text, while measuring accuracy with precision metrics.

• Coursera
• 1 hour 16 minutes
• Self-Paced
• Paid Course

Packt

Context Engineering for Multi-Agent Systems

Master context engineering for multi-agent AI systems, replacing fragile prompts with structured, scalable architectures using RAG, MCP, and Context Engines for reliable, production-ready solutions.

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

Packt

Unlocking Data with Generative AI and RAG

Master Retrieval-Augmented Generation (RAG) to build intelligent AI pipelines, enhance data retrieval, and apply advanced techniques using LangChain, vector stores, and prompt engineering.

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

Coursera

Model Data in Weaviate

Unlock advanced vector search by designing sophisticated schemas with multi-class relationships and relational links, then benchmark performance to optimize data architecture.

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