Logistic Regression Course
This course teaches logistic regression comprehensively, covering data preparation, feature engineering, model building with regularization, evaluation metrics like ROC and AUC, interpretation of coefficients for business decisions, A/B testing design, model monitoring for drift, and creating transparent scoring pipelines for production use. Students gain practical skills to develop reliable classifiers from clean data to deployment.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in logistic regression through hands-on practice, starting with data preprocessing and feature engineering, moving to model building, regularization techniques, and thorough evaluation using ROC, AUC, and calibration methods. Learn to interpret coefficients for actionable business insights, set up A/B tests, detect model drift, and construct well-documented, production-ready scoring pipelines.
Elevify advantages
Develop skills
- Build strong logistic models from data exploration to tuned specifications.
- Create effective features through encoding, scaling, and handling imbalances.
- Interpret model coefficients and odds ratios for business insights.
- Evaluate models using ROC, PR curves, calibration, and cross-validation.
- Deploy models with pipelines, monitor drift, and plan retraining.
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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