Logistic Regression Course
This course provides comprehensive training in logistic regression, from initial data preparation and feature engineering to model tuning, evaluation with metrics like ROC and AUC, calibration, and A/B testing. Participants will develop skills to interpret model outputs for business decisions, deploy scoring pipelines, monitor drift, and ensure production-ready models that deliver statistically robust recommendations.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in logistic regression through this practical course, progressing from data preparation to deploying reliable models. Cover preprocessing, feature engineering, model building, regularization techniques, and evaluation using ROC, AUC, and calibration metrics. Learn to interpret coefficients for business insights, conduct A/B tests, detect model drift, and create transparent scoring pipelines.
Elevify advantages
Develop skills
- Build strong logistic models from exploratory data analysis to tuned, regularized versions.
- Create effective features through encoding, scaling, and handling class imbalance to improve AUC.
- Interpret odds ratios and coefficients to quickly derive actionable business insights.
- Rigorous evaluation of classifiers using ROC, PR curves, calibration, cross-validation, and confidence intervals.
- Deploy models with scoring pipelines, implement drift detection, and plan for retraining.
Suggested summary
Before starting, you can change the chapters and 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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