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, A/B testing, and deployment strategies. Transform raw data into actionable probabilities and business recommendations with robust, production-ready models that withstand real-world challenges.
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 regression models from exploratory data analysis to optimized, regularized versions.
- Create effective features through encoding, scaling, and handling class imbalances to improve model performance.
- Interpret model coefficients and odds ratios to deliver quick, actionable business insights.
- Perform thorough classifier evaluations using ROC curves, precision-recall, calibration plots, cross-validation, and confidence intervals.
- Implement model deployment with scoring pipelines, drift monitoring, and systematic retraining protocols.
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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