Logistic Regression Course
This course teaches logistic regression comprehensively, covering data preparation, feature engineering, model building, evaluation metrics like ROC and AUC, interpretation of results, A/B testing, and deployment strategies including drift monitoring and scoring pipelines. Students gain skills to create reliable models that deliver actionable business insights and sound statistical recommendations.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in logistic regression through practical steps from data cleaning to deployable models. Cover preprocessing, feature creation, model building with regularization, evaluation using ROC, AUC, and calibration plots, interpreting coefficients for business value, A/B testing design, drift detection, and transparent 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 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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