Name: HR Essentials: Predicting and Managing Employee Turnover
Price: 82 GBP
Rating: 4.5 (121 reviews)

What You'll Learn

check_circleMaster Data Cleaning and Preparation Techniques: Participants will learn to use advanced data cleaning tools like OpenRefine and understand the importance of accurate data preparation. This includes handling missing data, correcting inconsistencies, and preparing datasets for analysis, which are critical skills for ensuring the reliability of any HR analytics project.

check_circleDevelop Skills in Data Analysis with R: Learners will gain proficiency in using R for data analysis, covering techniques from exploratory data analysis to more complex multivariate analyses. This includes learning to identify and handle outliers, performing correlations, and understanding multivariate normality, all of which are essential for extracting meaningful insights from HR data.

check_circleApply Predictive Modeling Techniques to Solve HR Issues: The course will teach participants how to apply predictive modeling techniques, such as decision trees, to forecast employee behavior such as turnover. This objective focuses on integrating both numeric and non-numeric data into models, enhancing their ability to predict outcomes and make informed HR decisions.

check_circleCommunicate Insights Effectively Through Dynamic Reporting: Participants will learn to use Quarto to create dynamic, reproducible reports that integrate analysis directly from R. This skill is vital for HR professionals who need to communicate complex data and insights in a clear and accessible manner to stakeholders who may not have a technical background.

check_circleInterpret and Implement Data-Driven HR Strategies: By the end of the course, learners will be equipped to interpret complex data analyses and apply these insights to real-world HR challenges. This includes understanding the drivers behind employee turnover, identifying factors that influence employee satisfaction, and using data to inform recruitment strategies and policy changes.

About This Course

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.

Your Instructor

Ken Dafoe

College Teacher in HR and People Analytics

menu_book5 courses

star307 reviews

I have always woven teaching into my professional journey, starting with consulting engagements across Canada and the United States before moving into academia. With a combined 40 years of experience in teaching data and analytics, my career has been rich and varied. At CPA Canada, I created IT course materials and devised several hundred multiple-choice questions for exams, in addition to publishing numerous articles on data in business IT publications. The advent of AI and machine learning, alongside the development of environments like RStudio, marked a pivotal moment in data analysis, transitioning from merely descriptive to advanced predictive analytics. This shift transformed the role of data in business and ignited my interest in how data can enhance human resources practices. At the college level, I developed two courses for HR graduate certificate students, focusing on leveraging people data to gain deeper insights into employee dynamics. Throughout my academic career, I have co-authored four papers, contributing the data analysis and interpretation sections. I am thrilled to share my insights and techniques with HR and other interested professionals on this platform. Whether you're new to working with people data or looking to enhance your existing skills, I hope to guide you through the fascinating world of data analytics in HR.

Frequently Asked Questions

We are a registered provider with 327+ associations and regulatory bodies worldwide. We operate across 29 global markets including Canada, the US, Australia, and the UK. Every course page clearly displays its specific accreditations. Upon completion, you receive a professional certificate that can be validated online. Our certificates include all necessary accreditation details, credit hours, and completion dates, and are formatted specifically to meet the submission requirements of most global regulatory bodies.

HR Essentials: Predicting and Managing Employee Turnover

What You'll Learn

About This Course

Your Instructor

Credit Information

What Students Are Saying

Frequently Asked Questions