Logistic Regression Course
This course delivers comprehensive training in logistic regression, guiding you from initial data cleaning and exploratory analysis to developing tuned, regularised models ready for production. Master feature engineering techniques like encoding and scaling to handle imbalances, interpret model outputs for actionable business decisions, rigorously evaluate performance with metrics including ROC curves, precision-recall, calibration plots, and cross-validation, and learn to deploy models with scoring pipelines, drift detection, and retraining strategies. Ideal for turning probabilistic predictions into reliable, statistically robust recommendations via A/B testing.
4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
Gain expertise in logistic regression through a practical course covering data preparation, feature engineering, model building with regularization, evaluation using ROC, AUC, and calibration, interpreting coefficients for business insights, A/B testing design, drift monitoring, and creating transparent scoring pipelines.
Elevify advantages
Develop skills
- Build robust logistic models from exploratory data analysis to regularised, optimised specifications.
- Engineer effective features through encoding, scaling, and addressing class imbalances to improve AUC.
- Interpret odds ratios and coefficients to quickly derive valuable business insights.
- Conduct thorough classifier evaluations using ROC, precision-recall, calibration, cross-validation, and confidence intervals.
- Deploy and monitor models with scoring pipelines, drift detection, and retraining protocols.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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