This repository contains a collection of R-based data analysis projects designed to enhance analytical and visualization skills. Each project has been crafted with specific tools and learning outcomes in mind, catering to different levels of expertise.
- Difficulty level: Beginner
- Tools used: R, ggplot2, dplyr
- Expected learning outcome: Understand customer churn and provide actionable insights.
- Difficulty level: Beginner
- Tools used: R, tidyr, dplyr
- Expected learning outcome: Explore job market data and identify in-demand skills.
- Difficulty level: Beginner
- Tools used: R, ggplot2, data.table
- Expected learning outcome: Analyze HR data to understand employee performance and attrition.
- Difficulty level: Intermediate
- Tools used: R, dplyr, lubridate
- Expected learning outcome: Improve inventory management and purchasing strategies.
- Difficulty level: Intermediate
- Tools used: R, ggplot2, reshape2
- Expected learning outcome: Develop make vs. buy analysis and cost scenario analysis.
- Difficulty level: Intermediate
- Tools used: R, shiny, ggplot2
- Expected learning outcome: Uncover insights in hospital efficiency and make recommendations.
- Difficulty level: Intermediate
- Tools used: R, ggplot2, randomForest
- Expected learning outcome: Assess company product performance against competitors.
- Difficulty level: Intermediate
- Tools used: R, caret, data.table
- Expected learning outcome: Analyze mortgage data and execute trade decisions.
- Difficulty level: Intermediate
- Tools used: R, ggplot2, dplyr
- Expected learning outcome: Explore sales and customer data to provide insightful visualizations.
The purpose of this repository is to provide structured learning opportunities for aspiring and experienced data analysts. Each project focuses on a specific domain, allowing for targeted skill enhancement.