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. Participants gain skills to create reliable models that deliver actionable business insights and robust predictions in real-world settings.
from 4 to 360h flexible workload
certificate valid 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 tuning with regularization, evaluation via ROC, AUC, and calibration plots. Learn to interpret coefficients for business value, set up A/B tests, detect model drift, and construct documented scoring systems for production use.
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, AUC, 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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