Predict Turnover with Spark ML
Master employee attrition prediction using Apache Spark MLlib in this hands-on Udemy course. Learn to build scalable machine learning models to identify turnover risks, optimize HR strategies, and improve organizational retention. Whether you’re a data scientist, HR professional, or developer, this project-based training offers practical skills for real-world workforce analytics.
- Preprocess HR data using Spark DataFrames and SQL
- Build ML pipelines with Logistic Regression and Random Forest
- Evaluate model performance using AUC-ROC and metrics
- Deploy solutions on distributed Spark clusters
This Udemy course includes a free Udemy course resource pack with datasets, code templates, and Spark configuration guides. Perfect for professionals seeking to enhance their ML engineering skills, leverage Spark’s distributed computing power, and add a market-ready project to their portfolio.
- Optimize feature engineering for employee data
- Compare traditional ML vs. SparkML workflows
- Interpret model results for actionable HR insights
- Access a Udemy coupon for advanced Spark courses
Enroll now to access exclusive Udemy coupon discounts and join a community of 5,000+ learners. Limited-time free Udemy course materials include bonus modules on hyperparameter tuning and production deployment. No prior Spark experience needed—start predicting attrition like a pro today!
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