Linear Models Course
Master linear models from data preparation to deployment in this comprehensive course. It equips statistics professionals to construct, diagnose, and interpret robust regression models, manage bias and uncertainty, and convert statistical coefficients into actionable business insights for informed decision-making.
4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Linear Models Course offers a swift, practical route to developing dependable predictive models. Participants will analyse data, engineer features, and apply simple, multiple, and regularised regression using Python or R. The course covers model validation, assumption testing, outlier and missing data management, plus effective communication of results, uncertainty, and business implications for practical decision-making.
Elevify advantages
Develop skills
- Build robust linear models through OLS, regularisation, and feature engineering.
- Diagnose model issues including residuals, multicollinearity, outliers, and robustness.
- Evaluate models using R-squared, RMSE, AIC/BIC, cross-validation, and interval estimation.
- Communicate results by interpreting coefficients, uncertainty, and business impact.
- Adopt a deployment-ready approach with 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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