Top 5 Full-Stack Projects for Final Year Students

For final year students, working on full-stack projects is a great way to gain hands-on experience and showcase skills that cover both front-end and back-end development. These projects help you master multiple technologies and give you practical knowledge that employers highly value. Below, we explore five full-stack project ideas that are ideal for final year students, combining machine learning, blockchain, cybersecurity, and healthcare applications.

1. Credit Card Fraud Detection Using Machine Learning (Full Stack)

The Credit Card Fraud Detection project addresses the critical problem of identifying fraudulent transactions in real-time. By using machine learning models, this project helps financial institutions prevent loss caused by fraudulent activities. Students can develop a web application where users upload transaction data, and the system flags suspicious activities using algorithms like Random Forest or Logistic Regression. This full-stack project integrates Python-based back-end services with a modern front-end framework, storing data securely in databases such as MongoDB or MySQL. Working on this project strengthens your understanding of data science, API integration, and responsive UI design.

2. Full Stack Fake News Detection Using Machine Learning

With misinformation spreading rapidly online, the Fake News Detection project is essential for creating trustworthy digital environments. This project leverages natural language processing and machine learning models to classify news articles as genuine or fake. Building it as a full-stack application involves setting up user authentication, article submission, and real-time classification results presented on a clean front-end interface. The back-end handles text preprocessing and machine learning inference, supported by databases that store user data and news articles. This project helps students gain experience in text analytics, model deployment, and secure web application development.

3. Full Stack Heart Disease Prediction Using Machine Learning

Healthcare innovations benefit greatly from predictive analytics, and the Heart Disease Prediction project is a prime example. This project allows users to input personal medical details to predict the risk of heart disease using trained machine learning models such as Decision Trees or Logistic Regression. The system is designed as a full-stack web app where the front-end collects user input and displays predictions, while the back-end manages model operations and stores sensitive health information securely. This project teaches students how to handle medical data responsibly and build full-stack applications that deliver real-time AI-powered insights.

4. Network Intrusion Detection Using Machine Learning Project Full Stack

In the cybersecurity domain, detecting unauthorized access is paramount. The Network Intrusion Detection project focuses on identifying malicious network traffic using machine learning classification techniques. This full-stack project involves capturing and analyzing network packets, running machine learning models to detect intrusions, and visualizing alerts on a real-time dashboard. Students implement user roles to restrict access and secure sensitive information. This project helps learners build skills in network security, machine learning deployment, and developing robust web interfaces for monitoring and management.

5. Full Stack Blockchain Voting System Project

The Blockchain Voting System project utilizes the immutability and transparency of blockchain to create secure and tamper-proof voting platforms. Students develop a decentralized application where votes are recorded on a blockchain ledger through smart contracts, ensuring each vote’s integrity. The front-end interacts with the blockchain using libraries like web3.js, while the back-end handles user authentication and vote counting. This project exposes students to blockchain fundamentals, smart contract programming, and full-stack development with decentralized technologies, making it highly relevant for emerging fintech and secure application markets.

Project Includes:

• PPT
  
• Synopsis
• Report
• Project Source Code
• Base Research Paper
• Video Tutorials
  

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