I want this course to take you through a particular HR problem: Can you tell me what factors influence an employee's decision to leave the company? Using the R language and a series of well explained and demonstrated techniques, we walk through solving the problem with real data and real code. To illustrate the results, we use Quarto, a modern publishing tool designed to create dynamic and interactive and repeatable reports, documents, and presentations. The each module covers topics specific to using data analytics to help predict employee attrition.
Course Modules:
- Data Cleaning and Exploration: Learn the fundamentals of data cleaning using advanced tools like OpenRefine and initial explorations with Excel. Understand the importance of quality data for meaningful analytics and get introduced to the basics of data exploration focusing on employee turnover.
- Exploratory Data Analysis with R: Dig into exploratory data analysis techniques using R. This module covers the identification and handling of outliers, univariate and multivariate analysis, and the preparation of data for predictive modeling.
- Multivariate Analysis in R: Focus on multivariate outlier analysis and normality tests to understand the complex interactions between variables. Learn about the practical application of these techniques in predicting employee behavior.
- Analyzing Turnover Factors: Explore the specific factors contributing to employee turnover, particularly among R&D lab technicians. Utilize correlation and regression analyses to identify key predictors and learn how to interpret these results within the HR context.
- Predictive Modeling with Decision Trees: Apply decision tree models to predict employee attrition. This module emphasizes the integration of numeric and non-numeric factors into the model, enhancing predictive accuracy and interpretability for HR decisions.
- Communicating Insights: Reporting with Quarto: Master the art of reporting and presenting data-driven insights using Quarto. Learn how to create a dynamic, reproducible report that updates automatically with new data, ensuring stakeholders are always informed with the latest analysis.
This program has been approved for 3.5 HR (General) recertification credit hours towards aPHR®, aPHRi™, PHR®, PHRca®, SPHR®, GPHR®, PHRi™, and SPHRi™ recertification through the HR Certification Institute.
schedule3.5 hours on-demand video
signal_cellular_altIntermediate level
task_altPreparation required
calendar_todayPublished At May 6, 2024
workspace_premiumCertificate of completion
errorI try to make courses about data that are for beginners. I think someone new to the R language, but committed to spend some to time, could understand everything I show in this course because I walk through the code in detail. But if you do have some experience with R, then all the better!
lock1 year access