Will this course help me in Agentic AI engineering or developer roles?

Yes, it builds practical skills in RAG, LLM integration, APIs, and AI system design—skills highly relevant for AI engineer and developer roles.

Can I build real-world AI applications after this course?

Yes, you’ll gain hands-on experience building a production-ready AI chatbot with retrieval, reasoning, and tool integration capabilities.

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 Foundations: Build RAG & MCP Chatbots

Agentic AI Foundations: Build RAG & MCP Chatbots

This course is part of Full Stack Agentic AI Specialization

Instructors: LearnKartS

Included with

Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Build real-world AI agents using RAG + MCP that think, retrieve data, and take actions—beyond basic chatbots
Create high-accuracy AI with embeddings, similarity search, and ranking for smarter, context-aware responses
Develop a complete AI product with Angular frontend, Node.js backend, and OpenAI + Gemini integration
Enabletool-callingAI systems that automate workflows and solve real problems like modern AI applications

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

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the Full Stack Agentic AI 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 4 modules in this course

The next wave of AI isn’t about better prompts—it’s about building systems that think, retrieve, and act on their own.

Most AI applications today stop at generating responses. But real-world systems need more they must access the right data, make decisions, and execute tasks seamlessly. This course is your gateway into Agentic AI, where RAG and MCP come together to create truly intelligent applications. You’ll build a full-stack AI system from the ground up designing retrieval pipelines, implementing embeddings and ranking, and enabling tool-driven workflows. Develop a modern Angular chat interface, power it with a Node.js backend, and integrate leading models like OpenAI and Gemini to create dynamic, context-aware experiences. This Agentic AI course is not about theory or isolated demos you’ll engineer a complete, production-ready AI chatbot that mirrors real industry use cases. Built for developers ready to move beyond experimentation and create meaningful AI solutions. Do not just deploy AI create systems that think, adapt, and deliver. Enroll now and start your journey into the future of AI engineering.

Learn why traditional AI models fall short and explore RAG, MCP, and agentic AI systems. Understand architectures, workflows, and the foundation of real-world AI agents.

What's included

13 videos6 assignments

13 videosTotal 55 minutes

Course Introduction1 minute
The Problem with Standard AI Models: Why ChatGPT/Gemini/Claude isn't enough4 minutes
What is RAG? Understanding Retrieval Augmented Generation6 minutes
Introduction to MCP and How It Complements RAG5 minutes
How MCP Works: Tools, APIs, and Real-World Examples5 minutes
MCP Architecture: Frontend, Backend, LLM and MCP Layer5 minutes
How MCP Server Actually Works: Architecture Deep Dive4 minutes
How RAG + MCP Work Together: The Power of Combined Systems2 minutes
Is RAG Alone Sufficient? Limitations of Simple Retrieval! RAG Only vs RAG + MCP7 minutes
The Evolution: From Chatbots to Agentic Systems4 minutes
What You'll Build in This Course2 minutes
Career Prep: RAG & Agent Architecture Questions8 minutes
Agentic AI Full-Stack Project Demo2 minutes

6 assignmentsTotal 162 minutes

Checkpoint Quiz20 minutes
Checkpoint Quiz16 minutes
Checkpoint Quiz66 minutes
Proficiency Quiz25 minutes
Proficiency Quiz20 minutes
Proficiency Quiz15 minutes

Set up your Node.js, Angular, and AI API environment, and understand RAG, embeddings, and retrieval workflows. Build the foundation for your chat application UI.

What's included

13 videos6 assignments

13 videosTotal 62 minutes

Development Environment - Install Node.js & VS Code Setup9 minutes
Create Gemini-AI API Key1 minute
Create OpenAI (ChatGPT) API Key5 minutes
Understanding RAG Architecture7 minutes
How RAG Actually Works Behind the Scenes4 minutes
Understanding Embeddings, Retrieval and Augmentation3 minutes
Installing Gemini Code Assistant and Setting Up AI Coding Support5 minutes
Getting Gemini API Key and Understanding Free Access Options4 minutes
Creating a New Angular Chat Application with Angular CLI4 minutes
Opening the Angular Project in VS Code and Preparing the Basic Structure4 minutes
Integrating Tailwind CSS and Bootstrap Icons in Angular4 minutes
Generating the Chat UI Using Gemini Prompting (Vibe Coding)5 minutes
Final UI Refinements: Message Interface, Styling, and Responsive Design6 minutes

6 assignmentsTotal 117 minutes

Checkpoint Quiz12 minutes
Checkpoint Quiz20 minutes
Checkpoint Quiz20 minutes
Proficiency Quiz15 minutes
Proficiency Quiz25 minutes
Proficiency Quiz25 minutes

Develop a functional Angular chat interface, handle API calls, integrate LLMs, and connect frontend and backend for real AI interactions.

What's included

15 videos6 assignments

15 videosTotal 69 minutes

Organizing Frontend Code & Creating Message Interface5 minutes
Optimizing sendMessage() Logic and Creating askLLM() Function5 minutes
Creating Angular Chat Service and Implementing HTTP POST API Call5 minutes
Handling Bot Responses, Error Handling, and UI Testing5 minutes
Implementing Auto Scroll, Environment Variables, and Final Frontend Setup6 minutes
Creating Backend Folder and Initializing Node.js Project4 minutes
Installing Packages and Creating Basic Express Server3 minutes
Configuring Environment Variables (.env) and Running Node Server4 minutes
Using Node Watch Mode and NPM Scripts for Development4 minutes
Understanding Gemini API Documentation and LLM Integration Basics5 minutes
Getting Gemini API Key and Configuring .env for Model & API Key4 minutes
Creating Gemini Provider Class and Implementing generateResponse()4 minutes
Building Express Chat Router and Connecting Gemini Provider5 minutes
Testing Gemini API with CURL and Handling Model Responses6 minutes
Testing NodeJS API in Angular Chat App - Chat with AI5 minutes

6 assignmentsTotal 135 minutes

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

Implement RAG pipelines, embeddings, and AI model integration to build a fully functional, context-aware chatbot ready for real-world applications.

What's included

26 videos10 assignments

26 videosTotal 126 minutes

Creating Local Knowledge Base and Understanding Basic RAG Concept4 minutes
Implementing RAG Service and Preparing Context & Prompt5 minutes
Integrating RAG with Chat Router and Testing the Q&A Bot4 minutes
Introduction to RAG for Static Q&A Bot & Overview of Embeddings4 minutes
Exploring Gemini Embedding API Documentation & Task Types4 minutes
Implementing generateEmbedding() in Gemini Provider4 minutes
Installing Cosine Similarity Package & Preparing Document Loader4 minutes
Generating Query Vector and FAQ Embeddings for RAG4 minutes
Ranking Results Using Cosine Similarity and Preparing Context5 minutes
Testing the RAG Q&A Bot and Improving Prompts for Better Responses6 minutes
Setting Up OpenAI API Key and Selecting the Model4 minutes
Creating the OpenAI Provider and Installing the SDK4 minutes
Implementing OpenAI Embeddings Functionality4 minutes
Integrating OpenAI with the Chat Router and Testing6 minutes
Testing Q&A Bot with OpenAI for Answers4 minutes
Interview Prep: RAG & Similarity Questions6 minutes
Initializing Node.js TypeScript Project & Installing Dependencies5 minutes
Configuring TypeScript (tsconfig) and Project Structure6 minutes
Creating Express Server, Environment Setup & Running the Project6 minutes
Integrating AI Model (Gemini) in NodeJS10 minutes
Project Refactoring: Routes and Controllers Setup4 minutes
Implementing Chat Controller and Route Integration3 minutes
Creating Mock Data and Building Customer & Order Controllers4 minutes
Creating API Routes and Testing Orders & Customers Endpoints5 minutes
Preparing a Weather API - Real-World Tool8 minutes
Summary1 minute

10 assignmentsTotal 229 minutes

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

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LearnKartS

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Frequently asked questions

Yes, this course is designed for developers who want to build production-ready AI systems using LLMs, APIs, embeddings, and modern AI architectures.

You will build a full-stack AI chatbot using Angular and Node.js, powered by RAG pipelines, embeddings, and an MCP-based tool calling for real-world AI workflows.

Most courses focus on prompts or theory. This course focuses on building production-ready AI systems using RAG + MCP with full-stack implementation.

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 Foundations: Build RAG & MCP Chatbots

Agentic AI Foundations: Build RAG & MCP Chatbots

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 4 modules in this course

Agentic AI Fundamentals

What's included

13 videosTotal 55 minutes

6 assignmentsTotal 162 minutes

Environment Setup & RAG Foundations

What's included

13 videosTotal 62 minutes

6 assignmentsTotal 117 minutes

Angular Frontend Development

What's included

15 videosTotal 69 minutes

6 assignmentsTotal 135 minutes

Building RAG Chatbots

What's included

26 videosTotal 126 minutes

10 assignmentsTotal 229 minutes

Earn a career certificate

Instructors

Offered by

Explore more from Software Development

MCP Servers & Agentic AI Architecture

Advanced Agentic AI: Production Data Architecture

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 Foundations: Build RAG & MCP Chatbots

Agentic AI Foundations: Build RAG & MCP Chatbots

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 4 modules in this course

Agentic AI Fundamentals

What's included

Environment Setup & RAG Foundations

What's included

Angular Frontend Development

What's included

Building RAG Chatbots

What's included

Earn a career certificate

Instructors

Offered by

Explore more from Software Development

MCP Servers & Agentic AI Architecture

Advanced Agentic AI: Production Data Architecture

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

Is this course suitable for AI developers and engineers?

What will I build in this Agentic AI course?

How is this course different from other AI Agents Development courses?

More questions