How will this course help me with AI system testing and debugging?

The course includes practical modules on testing and debugging Agentic AI systems, including how to test your RAG engine, query optimization, and advanced prompt engineering.You'llgain hands-on experience in troubleshooting common issues, ensuring your AI systemoperatessmoothly in real-world environments.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Agentic AI Systems with Vector DBs & RAG

Agentic AI Systems with Vector DBs & RAG

This course is part of Agentic AI Engineering: RAG, MCP & MERN Specialization

Instructors: LearnKartS

Included with

Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Advanced level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Dive intoRAG (Retrieval-Augmented Generation)and understand how to build smarter, context-aware AI systems with real-time data retrieval.
MasterAgentic AIconcepts, enabling systems to evolve, learn, and adapt autonomously in real-time based on dynamic data.
Learn how to implementpgVectorandChromaDB, integrating vector databases for efficient AI memory and fast data retrieval.
Gain hands-on experience building scalable, adaptive AI solutions that can continuously improve with every interaction and data input.

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

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Build your subject-matter expertise

This course is part of the Agentic AI Engineering: RAG, MCP & MERN Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

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!

Explore the fundamentals of agentic systems, decision loops, and AI memory, and understand why vector databases are essential for advanced AI. Set up ChromaDB and pgVector to build a RAG-powered knowledge base for your AI agents.

What's included

23 videos8 assignments

23 videosTotal 93 minutes

Course Introduction1 minute
What is an Agentic System?2 minutes
The "Why" - Beyond Simple Chatbots (Why Agentic)1 minute
The Decision Loop - Why Hard-Coded Logic Fails6 minutes
The Agentic Design Pattern - Passing RAG as a Tool5 minutes
Architecture Battle: RAG vs. MCP vs. Agents4 minutes
The Ecosystem: Apps that Support MCP2 minutes
The Memory Problem: Why AI Needs Vector Databases?2 minutes
What Vector Databases Do?1 minute
What is ChromaDB?4 minutes
What is pgVector?2 minutes
ChromaDB vs pgVector - When to Choose?4 minutes
Preparing File Structure and Data Assets (PDFs/Docs) for RAG8 minutes
Configuring ChromaDB in Local Environment7 minutes
Setting up ChromaDB in NodeJS & Environment Configuration4 minutes
Creating Vector Store & Upsert Function6 minutes
Search Function & Data Preparation6 minutes
Vector Store Backend Selection & Final Setup3 minutes
Introduction to Static RAG and Creating the Knowledge Base6 minutes
Creating rag.js and Reading the Knowledge Base File5 minutes
Preparing Context from JSON Data (Mapping Questions & Answers)5 minutes
Building the Prompt with Context and User Query6 minutes
Integrating RAG in Chat Router and Testing the Q&A Bot5 minutes

8 assignmentsTotal 193 minutes

Proficiency Quiz20 minutes
Proficiency Quiz30 minutes
Proficiency Quiz25 minutes
Proficiency Quiz30 minutes
Checkpoint Quiz16 minutes
Checkpoint Quiz24 minutes
Checkpoint Quiz24 minutes
Checkpoint Quiz24 minutes

Learn to connect PostgreSQL and PGVector to your Node.js app and implement vector ingestion, search, and RAG engine logic. Test and integrate RAG tools with MCP and GPT models for real-world AI workflows.

What's included

21 videos8 assignments

21 videosTotal 93 minutes

Installing PostgreSQL, PG, and PGVector5 minutes
Configuring PG Admin, Servers, and Query Tool5 minutes
Configuring PostgreSQL & pgVector for Windows2 minutes
Enabling the pgVector Extension for Database Configuration3 minutes
Connecting NodeJS App to pgVector2 minutes
Setting Up PostgreSQL Pool and PGVector Connection5 minutes
Creating the VectorStorePG Class and Initialization Logic5 minutes
Building the Upsert Function for Insert and Update Operations4 minutes
Implementing the Vector Search Query Using SQL5 minutes
Testing PGVector Ingestion and Verifying Data in PGAdmin5 minutes
Preparing the RAG Engine Interface & Class5 minutes
Generating Query Embeddings & Validating Dimensions5 minutes
Searching Vector DB, Building Context & Prompt7 minutes
Creating and Configuring the RAG Tool in MCP6 minutes
Registering the RAG Tool and Updating the AI System Prompt 3 minutes
Environment Setup and Starting Services for System Testing2 minutes
Testing Tools and Queries in the Agentic Workflow1 minute
RAG Testing with PGVector and Debugging ChromaDB6 minutes
Prompt Engineering and Advanced Query Testing8 minutes
Configuring OpenAI Testing and Updating RAG Prompt Logic3 minutes
Testing Agentic AI with GPT, Tool Calls, and Vector Database Switching6 minutes

8 assignmentsTotal 180 minutes

Proficiency Quiz25 minutes
Proficiency Quiz20 minutes
Proficiency Quiz25 minutes
Proficiency Quiz30 minutes
Checkpoint Quiz20 minutes
Checkpoint Quiz16 minutes
Checkpoint Quiz20 minutes
Checkpoint Quiz24 minutes

Integrate MongoDB with MCP, define schemas, and handle data transformations for customers and orders. Optimize your AI system for scalability, error handling, and production-ready performance.

What's included

21 videos8 assignments

21 videosTotal 97 minutes

MongoDB Architecture Overview and Integration Strategy1 minute
Installing and Configuring MongoDB Locally on macOS9 minutes
Installing and Configuring MongoDB Locally on Windows7 minutes
Configuring MongoDB Environment and Installing Mongoose4 minutes
Implementing MongoDB Connection and Starting the Server7 minutes
Schema & Customer Interface5 minutes
Schema Constraints & Model Setup4 minutes
Insert Data via MCP7 minutes
Error Handling & Future Steps3 minutes
Refactoring Customer Services: Mock Data → MongoDB & Fetching Latest Customers2 minutes
Fetching Customers by ID & Understanding MongoDB Schemas3 minutes
Refactoring Orders: Populating Customer Data & Preparing Order Insertion6 minutes
Creating & Testing Orders in MCP Server and Chat Application4 minutes
MongoDB Data Issue: Understanding _id vs id and Why Fetching Fails5 minutes
Creating Global Schema Options and Removing __v from MongoDB Documents4 minutes
Implementing Transform Function to Clean API Response4 minutes
Using Getters to Format Dates and Improve Schema Data Handling4 minutes
Applying Global Schema Options to Customer Model and Testing Results4 minutes
Optimizing Order Schema with ObjectId References and Populate6 minutes
Fixing Tool Output Types and Fetching Orders with Customer Details7 minutes
Course Summary1 minute

8 assignmentsTotal 175 minutes

Proficiency Quiz20 minutes
Proficiency Quiz25 minutes
Proficiency Quiz25 minutes
Proficiency Quiz25 minutes
Checkpoint Quiz16 minutes
Checkpoint Quiz24 minutes
Checkpoint Quiz20 minutes
Checkpoint Quiz20 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

LearnKartS

157 Courses191,032 learners

Offered by

LearnKartS

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Frequently asked questions

This course is ideal for developers and AI enthusiasts with a basic understanding of AI, databases (especially PostgreSQL and MongoDB), and programming languages likeNode.js. Familiarity with AI concepts and machine learning will help, but the course is beginner-friendly for those new to Agentic AI.

This course is designed for developers, AI enthusiasts, and data engineers who want to build intelligent systems using Agentic AI principles and vector databases. It is ideal for individuals looking to integrate advanced AI capabilities like dynamic decision-making and context-aware responses into their applications.

In thisAI Agents Developmentcourse,you'llwork with tools likepgVector,ChromaDB, PostgreSQL, and MongoDB.You'llalso learn to configure these systems withinNode.js, integrate RAG for dynamic response generation, andoptimizeyour database schemas for efficient data handling.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

Agentic AI Systems with Vector DBs & RAG

Agentic AI Systems with Vector DBs & RAG

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

There are 3 modules in this course

Agentic Systems and AI Memory

What's included

23 videosTotal 93 minutes

8 assignmentsTotal 193 minutes

PGVector and RAG Engine Development

What's included

21 videosTotal 93 minutes

8 assignmentsTotal 180 minutes

MongoDB Integration and Schema Optimization

What's included

21 videosTotal 97 minutes

8 assignmentsTotal 175 minutes

Earn a career certificate

Instructors

Offered by

Explore more from Software Development

Agentic AI Foundations with MERN, RAG & MCP

Build Production AI Agents with RAG & MCP

Advanced MCP & Tool Calling for AI Agents

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

More questions

Agentic AI Systems with Vector DBs & RAG

Agentic AI Systems with Vector DBs & RAG

What you'll learn

Details to know

See how employees at top companies are mastering in-demand skills

Build your subject-matter expertise

There are 3 modules in this course

Agentic Systems and AI Memory

What's included

PGVector and RAG Engine Development

What's included

MongoDB Integration and Schema Optimization

What's included

Earn a career certificate

Instructors

Offered by

Explore more from Software Development

Agentic AI Foundations with MERN, RAG & MCP

Build Production AI Agents with RAG & MCP

Advanced MCP & Tool Calling for AI Agents

Why people choose Coursera for their career

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Open new doors with Coursera Plus

Advance your career with an online degree

Join over 3,400 global companies that choose Coursera for Business

Frequently asked questions

What are the prerequisites for taking this course?

Who is this Agentic AI Engineering course for?

What tools and frameworks are used in the course for building Agentic AI systems?

More questions