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Logistic Regression Course

Logistic Regression Course
flexible workload of 4 to 360h
valid certificate in your country

What will I learn?

Gain expertise in logistic regression through this practical course, covering data 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, monitor model drift, and create transparent scoring pipelines for production use.

Elevify advantages

Develop skills

  • Develop strong logistic models from exploratory data analysis to tuned and regularized versions.
  • Create effective features through encoding, scaling, and handling class imbalance to improve model performance.
  • Interpret model coefficients and odds ratios to derive actionable business insights quickly.
  • Perform thorough model evaluation using ROC curves, precision-recall, calibration, cross-validation, and confidence intervals.
  • Implement model deployment with scoring pipelines, drift detection, and retraining strategies.

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.
Workload: between 4 and 360 hours

What our students say

Your classes are perfect. I got the one-year package and finally have the chance to follow several topics I'm interested in without having to switch platforms... I appreciate everything you do, I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can switch chapters and skip content I don't need.
Mariana Ferres
Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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