Parth Sabhaya

About

Computer Science student at Amity University with a focus on data analytics, machine learning, and software development. Experience leading technical operations for a university club and building analytics and AI-based projects using Python and related tools.

Experience

• Technical Head
  SnapSquad
  Aug 2025 – May 2026

Education

• Bachelor of Technology in Computer Science with Minor in Business Management
  Amity University
  Computer Science · Aug 2024 – May 2028

Skills

• SQL
• C
• Git
• GitHub
• HTML
• WordPress
• Python
• Jupyter Notebook
• Power BI
• Linux
• Tableau
• MySQL
• VS Code
• JavaScript
• Data Cleaning
• Model Evaluation
• NumPy
• Pandas
• scikit-learn
• Flask
• Microsoft Azure
• Jenkins
• Excel
• Statistical Analysis
• Google Cloud Platform
• REST APIs
• Predictive Modeling
• JUnit
• Data Wrangling
• Android Studio
• Eda
• Classification models
• Eclipse
• Linear Regression
• Time-Series Analysis

Projects

• Adidas Retail Revenue Forecasting & Sales Analytics
  Python, Pandas, NumPy, Scikit-Learn, Matplotlib

  Analyzed 9,000+ retail sales records using Python, Pandas, SQL, and Excel to identify revenue trends across products and regions. Built and compared forecasting models using Linear Regression, Moving Average, and Prophet. Evaluated model performance using RMSE, MAE, and MAPE metrics and generated business recommendations for inventory planning and revenue growth.

• AI Embroidery Design Generator
  Python, OpenCV, Machine Learning

  Developing an AI-based system to convert images into embroidery machine-compatible design files. Implementing image processing techniques to analyze patterns and recognize stitch structures from input images. Designing backend workflow to generate structured embroidery instructions for automated machine execution. Building dataset pipeline using existing embroidery designs to enable future stitch recognition and training.

• News Urgency Analytics Dashboard
  Python, Flask, HTML, CSS, Data Processing

  Built a web-based dashboard to analyze news headlines and evaluate urgency based on user input. Developed backend using Flask to process text input and generate analytical output dynamically. Implemented input handling and data processing logic to prepare the system for future integration with machine learning models.

• MoodShelf
  Python, Flask, HTML, CSS, JavaScript

  Developed a software application that recommends music based on the user’s current mood. Implemented backend logic using Flask to process mood input and return relevant music suggestions. Designed responsive frontend interface for smooth user interaction and structured the project for future integration with music APIs such as Spotify or YouTube.

Courses & certifications

• Data Structures & Algorithms · Amity University
• Database Management · Amity University
• Data Analytics · Amity University
• Machine Learning with Scikit-Learn · Amity University
• Artificial Intelligence · Amity University
• Software Engineering · Amity University
• Power BI · Amity University
• Microsoft Azure Fundamentals · Amity University
• Object Oriented Programming · Amity University

🗣️ Languages

• English · Fluent
• Hindi · Native
• Spanish · Intermediate
• Gujarati · Native