Logistic Regression Course
This course teaches logistic regression comprehensively, from initial data preparation through to full deployment. Participants will master feature engineering, model tuning, calibration techniques, and A/B testing methods to convert probability outputs into actionable business decisions and reliable statistical recommendations, ensuring models perform well in real-world scenarios.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain expertise in logistic regression through this practical course, moving from data cleaning to deployable models. Cover preprocessing, feature creation, model building, regularization, and evaluation using ROC, AUC, and calibration. Interpret results for business value, set up A/B tests, track model drift, and create documented scoring systems.
Elevify advantages
Develop skills
- Build strong logistic models: starting with exploratory data analysis up to regularized and optimized versions.
- Create effective features: through encoding, scaling, and handling imbalances to improve AUC performance.
- Interpret odds ratios and coefficients: quickly transforming model results into valuable business insights.
- Evaluate models thoroughly: using ROC, PR curves, calibration, cross-validation, and confidence intervals.
- Deploy and track models: developing scoring pipelines, monitoring for drift, and planning retraining strategies.
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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