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Build an E-Learning Website with the MERN Stack

PROJECT

Build an E-Learning Website with the MERN Stack

In this project, we will build an e-learning course catalog website with search functionality. We’ll design the database, schema, and API. We’ll also build the frontend and integrate an LLM-based chatbot using RAG (retrieval-augmented generation) to answer user queries based on the course data.

You will learn to:

Use the functional components of React.

Use React-Bootstrap to design the layout.

Use MongoDB to store and retrieve data, using the Mongoose library.

Lift the state to share the data between multiple functional components.

Use the Axios library to connect React components to the Node.js server.

Connect the Node.js server to store and retrieve data from MongoDB.

Implemented a chatbot using LLM-based (RAG) to answer queries based on course data.

Skills

Web Frameworks

Web Development

Prerequisites

Basic understanding of React components and state

Basic understanding of React Hooks

Basic understanding of JavaScript

Basic understanding of Node.js

Basic understanding of MongoDB

Technologies

MERN

Gemini

Node.js

Express

JavaScript

Project Description

In this project, we’ll build a responsive and interactive e-learning course catalog website. The platform displays a list of available courses and allows users to search through them using a dynamic search bar. Users will be able to:

View a complete catalog of courses
Search for courses based on keywords, titles, or categories
Browse a clean, user-friendly interface designed for seamless navigation
Ask questions to an integrated LLM-powered chatbot about course details or project information

Technologies used

This application is built using a modern full stack architecture:

MongoDB: A NoSQL database for storing structured course data
Express.js: A backend web framework for creating RESTful APIs
React.js: A frontend library for building responsive user interfaces
Node.js: A runtime environment to serve backend logic and handle requests
LangChain and Google Gemini: To build an intelligent chatbot powered by large language models (LLMs) for answering user queries from embedded course data

Development workflow

Backend setup: Express.js connects with MongoDB and defines endpoints to retrieve course data.
Frontend implementation: React components dynamically render courses and connect with the backend.
Search functionality: A real-time search bar filters courses by user input.
LLM-based chatbot: A retrieval-augmented generation (RAG) chatbot answers user questions using relevant project data, offering contextual help and insights.

Project Tasks

Backend with Node.js

Task 0: Get Started

Task 1: Run the Application

Task 2: Define the Database Schema

Task 3: Set up Node.js Server and MongoDB Connection

Task 4: Get the API Key

Task 5: Create Courses Routes and Controllers

Task 6: Set Up the Vector Store for AI-Powered Chatbot Responses

Task 7: Create Routes and Controllers for the Chatbot

Task 8: Insert Data into the Database

Task 9: Connect the Backend to Different Routes

Frontend with React

Task 10: Develop the Frontend with React

Task 11: Develop a Component for Courses

Task 12: Develop the Component for Search

Task 13: Develop Component for the Chatbot

Task 14: Integrate Components

Task 15: Test the Components

Connect Frontend and Backend

Task 16: Connect the Frontend with the Backend

Task 17: Update the BaseComponent

Congratulations!

Hear what others have to say

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"Another great hands on project to apply your knowledge learned. Thank you Educative ❤️"

Atabek BEKENOV

Senior Software Engineer

"Super excited to learn E-commerce website for my own startup venture. Thanks for your great learning platform."

Pradip Pariyar

Senior Software Engineer

"This was an excellent lesson. I learned a lot working through the process. I enjoyed it so much that I rebuilt it my AWS account to see how hard it would be to deploy to a production environment."

Renzo Scriber

Senior Software Engineer

"It was my first proper data engineering project and it was amazing."

Vasiliki Nikolaidi

Senior Software Engineer

"It's a fantastic way to do hands-on practice; I enjoy this way of learning."

Juan Carlos Valerio Arrieta

Senior Software Engineer

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