AI Resume Screener with NLP | Final Year Project with Source Code & Report

Overview

The AI Resume Screener is an intelligent recruitment automation system designed specifically as a comprehensive final year project for Computer Science and IT students. This advanced application leverages Natural Language Processing (NLP) and Machine Learning algorithms to transform the hiring process by automatically analyzing, scoring, and ranking resumes based on job requirements. Built with Django and powered by spaCy, this project demonstrates real-world application of AI in Human Resources, making it an ideal choice for students seeking impactful final year projects with source code.

This ready-to-deploy final year project eliminates manual resume screening bottlenecks, reducing recruitment time by 80% while removing unconscious bias from the hiring process. Perfect for students pursuing final year projects in machine learning, artificial intelligence, or web development, this system showcases advanced skills in NLP, semantic analysis, and full-stack development.

Key Features

• Intelligent Resume Parsing: Automatically extracts text from PDF and DOCX formats using PyPDF2 and python-docx, identifying candidate name, email, phone, skills, experience, and education
• NLP-Powered Analysis: Utilizes spaCy's en_core_web_sm model for advanced text processing and information extraction
• Multi-Dimensional Scoring Algorithm: Evaluates candidates using TF-IDF vectorization and cosine similarity across four dimensions - overall match (30%), skills match (40%), experience match (20%), and education match (10%)
• Automated Ranking System: Candidates are automatically ranked by match score with auto-shortlisting for 70%+ matches
• Responsive Dashboard: Beautiful Bootstrap 5 interface with analytics, detailed candidate profiles, and bulk upload capabilities
• Bias-Free Screening: Removes human bias from initial recruitment stages using data-driven decision making
• Batch Processing: Handle 50+ resumes in under 5 minutes with 85%+ accuracy in skill extraction

Technology Stack

This final year project demonstrates proficiency in modern technology stacks:

• Backend: Django 4.2 framework with Python 3.8+, SQLite for development, PostgreSQL-ready for production
• Machine Learning & NLP: spaCy, NLTK, scikit-learn, TF-IDF Vectorizer, sentence-transformers for semantic analysis
• Document Processing: PyPDF2 for PDF parsing, python-docx for Word documents
• Frontend: Bootstrap 5.3, Font Awesome 6.4, custom gradient CSS styling

Real-World Applications

• Corporate Recruitment: HR departments can process high volumes of applications efficiently, reducing time-to-hire by 80%
• Recruitment Agencies: Handle multiple clients and job postings simultaneously with automated candidate matching
• Startup Hiring: Small teams can screen candidates professionally without dedicated recruitment staff
• Campus Placements: Universities can streamline placement processes for multiple companies
• Freelance Platforms: Match freelancers with projects based on skill requirements

Benefits for Students

• Industry-Relevant Project: Addresses the real-world problem of resume screening that 43% of organizations now use AI for in 2025
• Advanced Technical Skills: Demonstrates expertise in Django, NLP, Machine Learning, and full-stack development
• Complete Documentation: Includes detailed project report, research paper format content, and PowerPoint presentation
• Easy Deployment: Step-by-step installation guide with all dependencies listed
• Scalable Architecture: Can be extended with BERT embeddings, multi-language support, or REST API integration
• High Academic Value: Perfect for IEEE paper submissions and technical presentations
• Portfolio-Ready: Impressive project for resumes and interviews with measurable performance metrics

Project Deliverables

When you purchase this final year project from CodeAj Marketplace, you receive:

• Complete source code with detailed comments
• Comprehensive project report (50+ pages)
• Installation and setup documentation
• PowerPoint presentation for project defense
• Database schema and architecture diagrams
• Testing documentation and test cases
• Future enhancement roadmap

Why Choose This Project?

This AI Resume Screener project stands out as one of the most practical and implementable final year projects available. With the recruitment industry increasingly adopting AI (43% adoption in 2025, up from 26% in 2024), this project demonstrates your understanding of market trends and real-world problem-solving. The system achieves 85%+ accuracy in skill extraction and processes resumes in 2-3 seconds each, making it a technically impressive and commercially viable solution.

Whether you're looking for Python final year projects, machine learning final year projects, Django projects with source code, or AI-based final year projects, this comprehensive system delivers on all fronts. The project includes everything needed for successful academic submission and can be customized for specific requirements or extended with additional features.