This page provides AKTU (Dr. APJ Abdul Kalam Technical University) specific information for final year project requirements. Covers evaluation criteria, synopsis format, report format, popular topics, and submission tips for AKTU BTech CSE, MCA, BCA students.

AKTU final year projects with source code

AKTU (formerly UPTU) has specific project submission requirements including a prescribed synopsis format, project report structure, and evaluation criteria. Our projects are prepared to meet AKTU standards with proper documentation and formatting.

About AKTU project requirements

Dr. APJ Abdul Kalam Technical University (AKTU), formerly known as Uttar Pradesh Technical University (UPTU), is one of the largest technical universities in India. It affiliates over 700 engineering colleges across Uttar Pradesh. AKTU has well-defined project submission guidelines that students must follow for their final year projects.

The university conducts project evaluation in two phases: an internal evaluation by your college guide and an external evaluation by university-appointed examiners. Your project is evaluated based on the working demonstration, project report quality, presentation, and viva-voce performance.

AKTU project evaluation criteria

AKTU typically allocates project marks as follows for BTech CSE students:

  • Internal evaluation (40-50%) — assessed by your project guide throughout the semester. Includes regular progress reviews, mid-semester demonstrations, and weekly report submissions.
  • External evaluation (50-60%) — conducted by external examiners during the end-semester viva. Includes project demonstration, report review, PPT presentation, and Q&A session.

The total project marks for BTech students at AKTU are typically 100-150 marks, depending on the semester and whether it is a minor or major project.

AKTU synopsis requirements

Before starting your project, you must submit a synopsis in the format prescribed by AKTU. The synopsis should include:

  • Project title and abstract (200-300 words)
  • Student details with enrollment numbers
  • Guide details with employee code
  • Problem definition and objectives
  • Proposed methodology
  • Technology stack with justification
  • Expected timeline (Gantt chart format)
  • References in IEEE format

The synopsis must be approved by your project guide and head of department before you begin development. Some AKTU-affiliated colleges also require approval from the department's project committee.

AKTU project report format

AKTU prescribes a specific format for the final project report. Key specifications include:

  • A4 paper, Times New Roman 12pt, 1.5 line spacing
  • Left margin: 1.5 inches (for binding), other margins: 1 inch
  • Black hardbound cover with gold lettering
  • Two copies required — one for college library, one for student
  • Chapter structure following the standard format (Introduction, Literature Survey, System Design, Implementation, Testing, Results, Conclusion)
  • Minimum 50 pages for major projects, 30 pages for minor projects

Popular project topics for AKTU students

Based on recent AKTU submissions, these are the most popular and highest-scoring project domains:

  • AI and machine learning — disease prediction, sentiment analysis, recommendation systems. These score well because they demonstrate current industry relevance.
  • Web development — e-commerce platforms, social media applications, content management systems. Use Django or React for best results.
  • Mobile applications — Flutter or React Native based apps for healthcare, education, or e-commerce. Cross-platform projects are preferred over native.
  • IoT projects — smart home systems, health monitoring, agricultural automation. Require hardware components which impress evaluators.
  • Blockchain — supply chain management, voting systems, certificate verification. Emerging domain that scores high novelty marks.

How CodeAj projects meet AKTU standards

Our projects are designed with Indian university requirements in mind. When you purchase a project from CodeAj for your AKTU submission:

  • The project report follows the chapter structure expected by AKTU evaluators
  • Documentation includes DFDs, ER diagrams, and use case diagrams
  • Source code is clean, commented, and easy to explain during viva
  • We provide free setup support to ensure your project runs during demonstration
  • Viva preparation guide included with technology-specific questions

You will need to customize the cover page, certificate, and student details to match your college format. We provide guidance on this as well.

Tips for AKTU project submission

  • Start early — AKTU typically requires regular progress submissions throughout the 7th semester (BTech) or final semester (MCA/BCA). Do not wait until the last month.
  • Attend all review meetings — internal evaluation marks depend heavily on your attendance and participation in project reviews.
  • Practice your demo — the external examiner will ask you to demonstrate specific features. Your project must work on the demo day.
  • Keep backup copies — save your code on GitHub, Google Drive, and a USB drive. Hardware failures before submission are common.
  • Follow the prescribed format exactly — AKTU evaluators check formatting compliance. Deviation can cost marks.

Projects for your submission

AI LinkedIn Profile Analyser — Django & Groq Final Year Project
available
AI LinkedIn Profile Analyser — Django & Groq Final Year Project

Paste your LinkedIn profile, get an AI-generated score, section-wise breakdown, and rewrite suggestions in under a minute.

Rs.499.00

Rs.1999

Smart Employee Attendance & Payroll Management System with Leave Tracking - Flutter Source Code
available
Smart Employee Attendance & Payroll Management System with Leave Tracking - Flutter Source Code

Complete Flutter-based employee management solution with automated attendance tracking, leave management, and payroll generation. Perfect final year project with Material 3 UI, SQLite database, and PDF salary slip generation.

Rs.499.00

Rs.1999

Advanced Image Steganography System - LSB Algorithm for Secure Data Hiding
available
Advanced Image Steganography System - LSB Algorithm for Secure Data Hiding

A sophisticated web-based steganography application that uses LSB algorithm to hide confidential text messages within PNG and BMP images. Perfect for final year projects in cryptography, information security, and image processing domains.

Rs.499.00

Rs.1999

JumpQuest - 2D Platformer Game with Phaser 3 | Final Year Project with Source Code
available
JumpQuest - 2D Platformer Game with Phaser 3 | Final Year Project with Source Code

Complete 2D platformer game built with JavaScript & Phaser 3 featuring smooth physics, enemy AI, particle effects, and polished UI - Perfect final year project with full source code and documentation.​

Rs.399.00

Rs.1999

AI-Powered Brain Tumor Detection System with Multi-Model Deep Learning Analysis for Medical Diagnosis
available
AI-Powered Brain Tumor Detection System with Multi-Model Deep Learning Analysis for Medical Diagnosis

Advanced deep learning web application with 84% accuracy using VGG16, ResNet50, and MobileNetV2 models for instant brain tumor detection from MRI scans with comprehensive visualizations and confidence scoring.

Rs.7999.00

Rs.1999

India Air Quality Index (AQI) Prediction System with PM2.5 Forecasting | Best Python Final Year Project 2025
available
India Air Quality Index (AQI) Prediction System with PM2.5 Forecasting | Best Python Final Year Project 2025

Advanced machine learning-based air quality prediction system that forecasts PM2.5 levels and AQI for Indian cities using Random Forest algorithm with interactive visualizations and real-time predictions.

Rs.499.00

Rs.1999

QuishGuard – QR Code Scam Detection App | Cyber Security Final Year Project with Source Code
available
QuishGuard – QR Code Scam Detection App | Cyber Security Final Year Project with Source Code

A Flutter app that scans a QR code and tells you in seconds whether it's safe, suspicious, or a scam backed by a Django risk-scoring engine. Full source code, report, and setup support included.

Rs.599.00

Rs.1999

PromptSense - AI Prompt Recommendation & Semantic Search System | Python Final Year Project with Source Code
available
PromptSense - AI Prompt Recommendation & Semantic Search System | Python Final Year Project with Source Code

A Sentence-BERT search engine that understands what you mean, not what you typed. Search 2,152 LLM prompts by meaning, with a Flask UI, charts, and a REST API. Full source code included.

Rs.499.00

Rs.1999

CropVision AI Crop Identification System using CNN and Flask | Final Year Project with Source Code
available
CropVision AI Crop Identification System using CNN and Flask | Final Year Project with Source Code

Upload one photo of a crop, get the name back in under a second — plus a heat map showing exactly which pixels the CNN looked at. Complete Python final year project with training notebook, Flask app and source code.

Rs.499.00

Rs.1999

Indian Railway Network Coverage Analysis and Station Site Planning
available
Indian Railway Network Coverage Analysis and Station Site Planning

8,801 railway stations, three trained ML models, and a live map that tells you where India actually needs new stations. Full Python source code plus a Flask dashboard you can run tonight.

Rs.499.00

Rs.1999

MoodLens AI Emotion Detection from Text | Flask Machine Learning Final Year Project with Source Code
available
MoodLens AI Emotion Detection from Text | Flask Machine Learning Final Year Project with Source Code

Paste any sentence, get the emotion behind it with a confidence score. A Flask + scikit-learn final year project with a cross-domain Transfer Lab your examiner has definitely never seen before.

Rs.599.00

Rs.1999

ExamPilot AI RAG Exam Prep Assistant That Cites Your Own Notes | Django Final Year Project with Source Code
available
ExamPilot AI RAG Exam Prep Assistant That Cites Your Own Notes | Django Final Year Project with Source Code

Upload your notes and PYQ papers, get page-cited answers, spot which topics repeat every year, and auto-generate a predicted model paper. A Django RAG final year project with full source code.

Rs.499.00

Rs.1999

Browse projects for AKTU submission

We have 200+ projects across Python, Java, AI/ML, web development, and mobile apps that are suitable for AKTU BTech CSE, MCA, and BCA submissions. Each project comes with complete source code, documentation, and free setup support. Browse our collection and find the right project for your submission.

Frequently asked questions

AKTU evaluates your understanding of the project, not whether you built it from scratch. What matters is that you can explain the code, demonstrate the working, and answer viva questions confidently. Many students use reference projects and customize them.

For BTech CSE, internal evaluation is typically 40-50% and external evaluation is 50-60%. Total project marks range from 100-150 depending on the semester and project type (minor vs major).

AKTU typically requires two copies — one for the college department library and one for the student. Some colleges may ask for a third copy for the guide.

Some AKTU-affiliated colleges still require a CD/DVD with the source code attached to the back cover of the black book. Check with your specific college.

Yes, AKTU allows group projects of 2-4 students for BTech CSE. Each member must clearly define their contribution and be prepared to explain their part during viva.

Python (Django, Flask, ML libraries) and Java (Spring Boot) are the most popular. React and Node.js for web projects. Flutter for mobile apps. Choose based on your project domain.

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