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 outputs into actionable business insights for statistics professionals seeking real-world impact.

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 methods. Explore data analysis, feature engineering, and fitting simple, multiple, and regularized regressions with Python or R. Master model validation, assumption checks, outlier and missing data handling, plus communicating results, uncertainty, and business value for informed 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 explaining coefficients, uncertainty levels, and business implications.
- Adopt deployment practices including monitoring, drift detection, retraining, and ethical considerations.
Suggested summary
Before starting, you can change the chapters and 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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