Linear Models Course
This course equips you to master linear models from preparation to deployment. Build, diagnose, and interpret robust regressions, manage bias and uncertainty, and convert statistical results into actionable business insights for statistics professionals seeking real-world application.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain practical skills to create reliable predictive models using linear regression techniques. Explore data preparation, feature engineering, fitting simple and multiple regressions with regularization in Python or R. Master model validation, assumption checks, outlier and missing data handling, plus communicating results, uncertainty, and business impacts effectively for decisions.
Elevify advantages
Develop skills
- Build strong linear models quickly with OLS, regularization, and smart feature engineering.
- Diagnose problems like residuals, multicollinearity, outliers, and model robustness.
- Evaluate performance using R-squared, RMSE, AIC/BIC, cross-validation, and confidence intervals.
- Communicate findings by interpreting 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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