By the end of this course, learners will be able to analyze HR attrition data, evaluate key workforce factors, apply statistical techniques, select significant features, and build a predictive attrition model using R.

This course provides a practical, end-to-end approach to HR analytics with a strong focus on employee attrition. Learners begin by preparing and validating real-world HR data, followed by in-depth exploratory data analysis to understand workforce demographics, job-related factors, and attrition patterns. The course then progresses to statistical analysis using correlation and Chi-Square tests, helping learners identify meaningful relationships between employee attributes and attrition outcomes. What makes this course unique is its structured, project-driven methodology that mirrors real HR analytics workflows. Learners apply Information Value (IV) techniques for feature selection, create a final modeling dataset, and build an attrition prediction model in R, concluding with performance evaluation on unseen data. By completing this course, learners gain hands-on experience in HR data analysis, develop job-ready analytical thinking, and build confidence in using R for data-driven HR decision-making, making it ideal for aspiring data analysts, HR professionals, and analytics learners seeking practical industry skills.