Analyzing HR Attrition and Employee Turnover with R

Learn to import, clean, and analyze workforce data using R to identify key drivers of employee turnover and make data-driven HR decisions.

⏱ 58 min 📚 8 aralin 🎧 Audio version

Tungkol sa kursong ito

Understanding why employees leave is one of the most critical challenges in modern talent management. This text-based course introduces you to people analytics using R, enabling you to transform raw HR data into actionable retention strategies. You will progress from understanding basic HR metrics to writing clean, reproducible R code that uncovers the hidden patterns behind employee attrition. By working through realistic scenarios, you will gain the confidence to present data-backed insights to leadership. What you'll learn: Understand core HR attrition metrics and foundational people analytics concepts; Import and clean workforce datasets using modern R packages and tidyverse workflows; Analyze key drivers of employee turnover, such as compensation, tenure, and role satisfaction; Create clear, structured data summaries to isolate high-risk employee segments; Apply modern R programming practices, including clean piping and efficient data manipulation techniques. The course starts with foundational definitions of attrition and turnover metrics, then guides you step-by-step through setting up your R environment, cleaning messy HR data, and performing exploratory data analysis. You will wrap up by learning how to structure your findings for executive reporting. This course is designed for HR professionals, recruiters, and aspiring data analysts who are new to R programming. No prior coding experience or advanced statistical knowledge is required. Start reading today to unlock the power of data-driven decision-making in human resources.

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  • Maikli at focused
    58 min ng practical content

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