Hello! I'm Shubham

A recent Big Data Analytics graduate passionate about turning data into impactful solutions. Skilled in data analytics, data visualization, and web development, with a proven ability to develop predictive models and drive business insights.

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Skills

Python

SQL

HTML5

CSS3

Javascript

Looker

Power BI

Tableau

Google Cloud

GitHub

MS Office Suite

Advanced Excel

Firebase

Matplotlib

Work Experience

Data Science Intern

EI System technologies
Jun 2024-Aug 2024

Data Science Intern

Plasmid Innovations
Jun 2024-Aug 2024

Web Developer Intern

OctaNet Services pvt ltd
Feb 2024-Mar 2024

Front-end developer

Shree Vitthal Sweets & Snacks
Oct 2022-Dec 2022

Projects

SugarCrush : Coffee & Restaurant Sales Data Analysis

Krushak-setu : A digital scheme recommendation portal

Citi-Shield : A crime rate analysis and prediction model

Cartoon Preference Survey Looker dashboard

Talk-to-Me
Arduino based project

Certifications

DATA SCIENCE AND ANALYTICS

HP Life & HP foundation - Forage
2025

Certificate

Google Analytics GA4 Certification

Google
2025

Certificate

Data Visualization: Empowering business with effective insights

TATA - Forage
2025

Certificate

Python (Basic)

Hackerrank
2023

Certificate

Microsoft Excel - Basic Excel/ Advanced Excel Fromulas

Udemy
2022

Duet AI

Google Developer Groups Kochi
2025

Publications

Krushak-Setu: A Digital Scheme Recommendation System for Farmers of Maharashtra

Authors - Shubham Atugade, Gargee Sonar, Simantini Kotalwar, Prof. Indu Kumari

To address the challenge that many farmers in Maharashtra face with limited awareness and language barriers when accessing government welfare schemes, this paper presents a study of a potential solution. The research details a bilingual digital portal designed to provide personalized schemes with a high accuracy rate of 90-95% by filtering opportunities based on individual farmer profiles. The proposed solution also integrates an AI-powered chatbot for instant assistance, alongside live weather, market, and crop data to support informed decision-making. This study concludes that such a user-friendly and accessible platform, optimized for rural areas, can effectively bridge the information gap and empower farmers.

Available on: IJIRCCE Scilit ResearchGate Philpapers IvySci Discovery

Crime Rate Analysis and Prediction Model Using Machine Learning

Authors - Shubham Atugade, Rahul Kale, Ankita Bedkute, Prof. Vivek More

To address the significant challenge law enforcement faces in accurately predicting crime, this research investigates a data-driven solution for forecasting crime trends in Indian metropolitan cities. The paper details a system that analyzes historical crime data from the National Crime Rate Bureau (NCRB) to identify potential high-crime areas and predict future trends. The study evaluated several predictive modeling techniques, identifying an approach that can forecast crime rates with an impressive accuracy of 93.20%. The research concludes that such a highly accurate predictive model serves as a powerful tool for law enforcement, enabling proactive crime prevention and more effective resource allocation to enhance public safety.

Available on: IJIRCCE

Articles

From Nostalgia to Numbers: Unveiling Cartoon Preferences Through Data Visualization

View Article

Understanding Decorators and Generators in Python

View Article

Illuminating Futures: The EDUCATION FOR ALL Campaign by Hamari Pahchan NGO

View Article

Educational Qualifications

Bachelor of Computer Applications
(Big Data Analytics)

Ajeenkya DY Patil University, Pune
Sep 2022 - Jun 2025

GPA: 9.5/10

Higher Scondary Education
(PCM with Computer Science)

Smt. Sushiladevi Deshmukh Vidyalaya & Jr.College, Navi Mumbai
Jun 2020-May 2021

Percentage: 85.83%

Contact me

Get in touch

Reach out, and letโ€™s create a universe of possibilities together!