Master the art of predictive modeling with confidence and precision.

This Short Course was created to help data analysis professionals accomplish robust model development and evaluation for business-critical decisions. By completing this course, you'll be able to build sophisticated regression models that meet statistical assumptions, apply cutting-edge classification techniques, and make data-driven model selection decisions that directly impact business outcomes. By the end of this course, you will be able to: Build and diagnose multiple linear regression models with proper statistical validation Apply advanced classification methods including gradient boosting for optimal performance Evaluate and remediate model assumption violations using systematic approaches Handle class imbalance effectively using SMOTE and other proven techniques This course is unique because it bridges statistical rigor with modern machine learning, emphasizing both model accuracy and business applicability. To be successful in this project, you should have a background in statistics, Python programming, and basic machine learning concepts.