Linear Models Course
This course equips you with essential skills to build, diagnose, and deploy linear models effectively. From data preparation to interpreting coefficients for business insights, handle real-world challenges like bias, uncertainty, multicollinearity, and outliers to deliver actionable predictions using Python or R.

flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
Gain practical skills to create reliable predictive models using linear regression techniques. Learn data exploration, feature engineering, fitting simple, multiple, and regularized models with Python or R. Master model validation, assumption checks, outlier and missing data handling, and communicating results with uncertainty for business decisions.
Elevify advantages
Develop skills
- Build strong linear models using OLS, regularization, and smart feature engineering.
- Diagnose problems like residuals, multicollinearity, outliers, and model robustness.
- Evaluate performance with R-squared, RMSE, AIC/BIC, cross-validation, and confidence intervals.
- Communicate findings by explaining coefficients, uncertainty, and business implications.
- Adopt deployment practices including monitoring, 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.What our students say
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