Quantium is a lightweight Python library for mathematical and scientific computations with units. It enables dimensional analysis and unit-safe calculations through a simple, dependency-minimal design. NumPy integration is planned for future releases.
Data_Analytics_Virtual_Experience_Program
Quantium Data Analytics virtual internship program
🎯 This repo contains the work completed during the Quantium Data Analytics Job Simulation on Forage. The focus was to analyze customer transaction data, provide insights, and recommend data-driven strategies. Key areas include data preparation, customer segmentation, uplift testing, and reporting for decision-making.✨
Customer segmentation & retail trial analysis using Python — Quantium Virtual Internship project
End-to-end Python data analysis of chip purchasing behaviour, customer segments, product performance, and sales trends, with actionable business recommendations.
Experimentation and Uplift Testing using Python | Quantium Data Analytics Virtual Internship | Trial vs Control Store Analysis | Statistical Testing | Data Visualization | Business Insights
This repository serves as the central hub for the Quantium Software Engineering Program. As a graduate of this program, I've gathered and curated a collection of resources, including program modules, assignments, projects, and supplementary materials, all designed to support your learning journey in the field of software engineering.
Analytics and commercial application project completed as part of the Quantium Data Analytics Virtual Experience Program on Forage using Python, customer analytics, trial store analysis, and business storytelling.
Analyzed real-world retail data from Quantium to uncover chip-buying behavior by customer segments. Used R, tidyverse, dplyr, and ggplot2 for data cleaning, visualization, and insight generation. Identified top segments, popular pack sizes, and premium brand opportunities.
The project entails in-depth exploration of customer purchasing behavior, sales trends, and commercial insights within a supermarket chain, specifically targeting the chips category. Leveraging data analytics techniques, the repository showcases the identification of key metrics, data preparation, customer segmentation, and the evaluation.
Completed Quantium's Data Analytics Virtual Experience Program on Forage, focusing on customer analytics, commercial insights, uplift testing, and data-driven business recommendations.
Customer Analytics and Data Preparation project completed using Python for the Quantium Virtual Experience Program. Includes data cleaning, customer segmentation, sales analysis, visualizations, and business recommendations.
End-to-end retail analytics project — customer segmentation, A/B trial testing and strategic recommendation using Python and Tableau
A Python/Dash web app built for the Quantium Virtual Job Simulation on Forage. Includes interactive Plotly sales visualisations, automated UI testing (Pytest/Selenium), and a Bash script for CI/CD pipeline integration.
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