Shaikh Arfat

B.Tech IT student · Aspiring Software and Data Developer

Pune, Maharashtra, India

@shaikh_arfat

0 followers

🎓 B.Tech. in Information Technology at G H Raisoni College of Engineering and Management · Graduating 2027

About

Final-year B.Tech Information Technology student with hands-on experience in Python, C++, Java, SQL, MySQL, data analytics and machine learning. Built end-to-end projects involving data cleaning, EDA, predictive modeling, REST APIs and deployment.

Education

B.Tech.

G H Raisoni College of Engineering and Management

Information Technology · 2023 – 2027

Skills

<3 months

C SQL CSS3 Java NumPy React HTML5 Python Pandas Node.js Leaflet Express.js JavaScript scikit-learn Data Cleaning CRUD Operations Model Evaluation Data Preprocessing Data Visualization Feature Engineering Supervised Learning Relational Databases API Integration Understanding Data Structures and Algorithms Logistic Regression ( in progress )

Tools / apps / platforms

<3 months

Git NPM MySQL XAMPP GitHub Postman VS Code Microsoft Excel MySQL Workbench Microsoft Power BI

Projects

Hospital Management System

PHP, MySQL, JavaScript

Developed a database-driven application supporting patient, doctor, appointment and billing workflows. Implemented MySQL-backed CRUD operations and authentication to manage and organize healthcare records.
Real-Time Public Transport Tracking System

React.js, Node.js, Express.js, MySQL, Leaflet

Built a data-driven public transport tracking application using a React.js frontend, Node.js/Express backend and MySQL relational database. Designed and integrated REST APIs for bus records and location updates, including an administrative interface for managing transport data. Connected database-backed transport records with Leaflet-based geospatial visualization to display vehicle locations through the tracking interface.
Telco Customer Churn Prediction

Python, Pandas, NumPy, Scikit-learn, Streamlit

Developed an end-to-end customer churn prediction pipeline covering data cleaning, EDA, preprocessing, feature transformation and supervised learning. Applied one-hot encoding to categorical features and trained a Logistic Regression classifier, achieving approximately 80% accuracy. Evaluated performance using F1-score and recall, serialized the model with Joblib, and deployed an interactive prediction application using Streamlit.

Courses & certifications

Power BI for Beginners · 2026
Introduction to Data Science · 2026
Introduction to Data Analytics · 2026
Machine Learning using Python · Simplilearn · 2025

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