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Entry-Level Full Stack Developer with strong front-end and Python/Django backend skills.
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Full stack developer with strong front-end experience in modern UI frameworks and styling systems, and backend development using Python and Django. Skilled in creating responsive, user-focused web applications, with experience in API integration and database operations. Adept at translating design requirements into functional interfaces. Motivated to learn continuously and contribute effectively to development teams.
Mashup Stack
FullStack Development · Python Django React
May 1, 2025 – Present
APJ Abdul Kalam Technological University
B.Tech · Computer Science & Engineering
January 1, 2021 – January 1, 2025
SNDPHSS Chennerkara
Plus Two · Biology Science
September 1, 2020 – March 1, 2021
SNDPHSS Chennerkara
10th
June 1, 2018 – March 1, 2019
Personal Bookmark Manager
June 27, 2026 – Present
Created a web application using React to save and manage website bookmarks. Users can add new bookmarks, view saved links, and delete unwanted ones. The application uses simple components and stores data in the browser using local storage. This project helped me understand how a real web application works from user input to data display.
Online Concert Booking System
June 27, 2026 – Present
Developed a full-stack web application using React.js for the frontend and Django REST Framework for the backend. The application allows users to register, log in, browse concerts, book tickets, and view their booking history. Implemented RESTful APIs, token-based authentication, and CRUD operations to manage concert and booking data. Used Axios for frontend-backend communication and MySQL with Django ORM for database management, following a client-server architecture.
AI-Based Mock Interview Evaluator and Emotion Classifier Model
June 27, 2026 – Present
Developed an AI-powered mock interview evaluation system capable of analyzing candidates' facial expressions, speech tone, and behavioral cues to assess their emotional state and confidence level during interviews. The model uses machine learning and computer vision techniques to classify emotions and confidence scores, providing constructive feedback to help candidates improve performance. Implemented using Python, OpenCV etc..
Cultural Fit Analysis
The candidate's projects demonstrate a mix of web development and AI/ML interests, indicating a curious and learning-oriented mindset. The academic nature of all projects suggests a foundational understanding but lacks real-world team collaboration or industry best practices exposure. The 'Online Concert Booking System' and 'AI-Based Mock Interview Evaluator' show initiative in building complex systems. However, the overall breadth of experience is limited to academic and personal projects, which might require more mentorship in a professional team environment.
Soft Skills & Operational Fit
The candidate lists 'Problem-Solving' and 'Communication' as soft skills. The project descriptions are clear and demonstrate an understanding of the systems built. The academic projects show an ability to work on structured tasks. However, without direct work experience or psychometric test results, it's difficult to fully assess operational fit, stress handling, or team collaboration in a professional setting.