Agentic AI Systems with Vector DBs & RAG

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Agentic AI Systems with Vector DBs & RAG

Coursera · Intermediate ·🔍 RAG & Vector Search ·3mo ago

Skills: RAG Basics90%Vector Stores80%AI Systems Design70%

Key Takeaways

Builds Agentic AI systems using RAG and vector databases like pgVector

Original Description

Want to build AI that learns, adapts, and evolves in real-time? The future of AI is Agentic AI. While traditional models are built on static logic, Agentic AI enables systems to learn, think, and make autonomous decisions, evolving with each interaction and adapting to new data. In this Agentic AI course, you’ll master RAG (Retrieval-Augmented Generation) and vector databases like pgVector and ChromaDB, unlocking the ability to build AI systems that dynamically retrieve data, learn from context, and make smarter decisions. You’ll gain hands-on experience creating scalable, real-time adaptive AI—critical for industries looking to stay ahead. What makes this course unique? Unlike others, it combines cutting-edge RAG tools with practical applications of pgVector and ChromaDB, giving you the power to create AI that evolves with every interaction. Perfect for AI developers, engineers, and innovators eager to shape the future of AI. Don’t just follow trends—lead them. Enroll now and start building the future of AI today!

Watch on External: Coursera ↗ (saves to browser)

Sign in to unlock AI tutor explanation · ⚡30

More on: RAG Basics

View skill →

High Performance (Realtime) RAG Chains: From Basic to Advanced

High Performance (Realtime) RAG Chains: From Basic to Advanced

Coding the Ultimate RAG Engine from Zero

Coding the Ultimate RAG Engine from Zero

Building Agentic RAG From Scratch in Pure Python

Building Agentic RAG From Scratch in Pure Python

Build an LLM and RAG-based Chat Application using AlloyDB and LangChain

I Built a RAG App to Decode Airline Bureaucracy (So You Don't Have To)

I Built a RAG App to Decode Airline Bureaucracy (So You Don't Have To)

Akamai Developers

RAG Demo for Beginners: Full Hands-On Tutorial in Tamil | Build Your Own RAG AI | Karthik's Show

RAG Demo for Beginners: Full Hands-On Tutorial in Tamil | Build Your Own RAG AI | Karthik's Show

Related Reads

Why Your Chatbot Feels Dumb — And How RAG Fixes It

Learn how RAG technology can improve your chatbot's performance by addressing its limitations, making it more informative and user-friendly

5 RAG Optimization Techniques Every AI Engineer Should Know In 2026

Optimize Retrieval-Augmented Generation (RAG) systems using 5 techniques: metadata filtering, ANN search, embedding caching, async retrieval, and quantization, to improve performance and accuracy

5 RAG Optimization Techniques Every AI Engineer Should Know In 2026

Optimize RAG models using 5 key techniques for improved performance and efficiency, essential for AI engineers working with Retrieval-Augmented Generation

Medium · Machine Learning

Let’s talk about RAG: Why it exists, how it works and lot more about it.

Learn about RAG, its purpose, and how it works, to improve your understanding of this technology

LLM Wiki vs RAG Explained | Complete LLM Wiki Implementation Guide

Pavithra’s Podcast