Employee Attrition Prediction Using Machine Learning
A brief overview of the material covered in this course is that it teaches students how to use logistic regression and the XG-Boost algorithm in machine learning to forecast employee turnover.
Description for Employee Attrition Prediction Using Machine Learning
Features of the Course:
Development of an Attrition Prediction Model: Develop a machine learning model to forecast employee turnover based on variables such as job satisfaction, commuting distance, remuneration, and performance metrics.
Exploration of Machine Learning Algorithms: Acquire proficiency in two machine learning algorithms: logistic regression classifier and Extreme Gradient Boosted Trees (XGBoost).
Human Resources Software: Acquire the ability to implement predictive models in Human Resources to identify personnel at risk of attrition.
Hands-On Project-Based Learning: Participate in hands-on experience by constructing, training, and evaluating the model using real-world data attributes.
Level: Beginner/Intermediate/ Advanced
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Coursera Project Network
Duration: 2 hours
Schedule: Hands-on learning
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