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Linear Models Course

Linear Models Course
4 to 360h flexible workload
certificate valid in your country

What will I learn?

Gain practical skills to construct reliable predictive models using linear regression techniques. Delve into data exploration, feature engineering, and fitting simple, multiple, and regularized models with Python or R. Master model validation, assumption checks, outlier and missing data management, plus effective communication of results, uncertainty, and business implications for informed decisions.

Elevify advantages

Develop skills

  • Develop robust linear models using OLS, regularization, and feature engineering techniques.
  • Diagnose model problems including residuals, multicollinearity, outliers, and robustness checks.
  • Evaluate model performance with metrics like R-squared, RMSE, AIC/BIC, cross-validation, and confidence intervals.
  • Communicate findings by interpreting coefficients, quantifying uncertainty, and linking to business outcomes.
  • Adopt a deployment-focused approach covering monitoring, data drift detection, retraining, and ethical considerations.

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 are saying

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Giulio CarloDigital Marketing Student
I like how the lessons are straight to the point and how I can change chapters and skip content I don't need.
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