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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, moving from data preparation to deployable models. Cover preprocessing, feature creation, model building, regularization techniques, and evaluation using ROC, AUC, and calibration metrics. Interpret results for business value, set up A/B tests, track model drift, and develop clear scoring systems.

Elevify advantages

Develop skills

  • Build strong logistic models: starting with data exploration up to tuned and regularized versions.
  • Create effective features: through encoding, scaling, and handling imbalances to improve AUC scores.
  • Interpret model coefficients and odds: quickly transforming outputs into valuable business insights.
  • Rigorous evaluation of classifiers: using ROC, PR curves, calibration, cross-validation, and confidence intervals.
  • Deploy and oversee models: with scoring pipelines, drift detection, and strategies for retraining.

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 lessons 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, and I've already recommended you to others...
Giulio Carlo
Giulio CarloDigital Marketing Student
I like how the lessons get 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 extra videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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