
EDUCBA
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.
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
EDUCBA