Sridhar R
Aspiring Data Scientist & Software Developer
Data Science student passionate about machine learning, analytics, and building real-world software solutions with practical impact.
Technical Skills
- Java
- JavaScript
- PHP
- HTML5
- Python
- C
- R
- CSS3
- Tailwind CSS
- Android Studio
- MySQL
- TableauTableau
- PowerBIPowerBI
- Apache Cordova
- Figma
- Machine LearningMachine Learning
- Data Structures & AlgorithmsData Structures & Algorithms
- Data AnalyticsData Analytics
- NumPy
- Node.js
- MongoDB
Professional Summary
Application Developer with hands-on experience in designing and developing cross-platform mobile applications, desktop applications, machine learning solutions, and interactive business intelligence dashboards. Proficient in Java, Python, SQL, and Object-Oriented Programming with strong knowledge of Data Structures & Algorithms, Database Management Systems (DBMS), and the Software Development Life Cycle (SDLC). Experienced in developing scalable, user-centric applications and solving real-world problems through end-to-end software development.
Education
2023 - 2027
B.Tech Computer Science and Engineering (Data Science)
Kalasalingam Academy of Research and Education
02/2025 - 06/2025
Taiwan Semester Exchange Program – Computer Science and Information Engineering
Tamkang University
Projects
Plate2Purpose
Developed a cross-platform mobile application using Apache Cordova to connect food donors, NGOs, and administrators, enabling efficient redistribution of surplus food.
Implemented role-based authentication, secure donation management, and QR code-based verification to improve transparency and traceability throughout the donation process.
Integrated Google Maps API and geolocation services to identify nearby NGOs, optimize food pickup routes, and enable location-aware donation tracking.
Designed and developed a PHP-MySQL backend for managing donor registrations, food requests, user records, and real-time donation workflows.
Built an intuitive mobile interface to streamline food donation, request management, and communication between donors and NGOs.
Heart Disease Prediction System
Developed a machine learning-based web application to predict heart disease risk using patient health parameters.
Performed data preprocessing, feature engineering, exploratory data analysis (EDA), and model evaluation using Scikit-learn.
Implemented Logistic Regression and Random Forest algorithms, achieving over 85% prediction accuracy.
Developed a Flask-based web interface for real-time prediction and result visualization.
Amazon Sales Analytics Dashboard
Developed an interactive Tableau dashboard to analyze sales performance, profitability, and customer trends using business intelligence techniques.
Performed data cleaning, transformation, and SQL-based data preparation to improve reporting accuracy.
Designed KPI-driven dashboards with interactive filters, charts, and drill-down visualizations for data-driven decision-making.
Generated actionable insights into regional sales, product categories, and revenue trends.