Linear Models Course
This comprehensive Linear Models Course equips statistics professionals with essential techniques to prepare data, construct and diagnose reliable regression models, address bias and uncertainty, and transform statistical outputs into actionable business insights, covering everything from initial setup to practical deployment strategies.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
Gain practical skills in constructing dependable predictive models through this Linear Models Course. Delve into data exploration, feature engineering, and applying simple, multiple, and regularised regression using 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 strong linear models using efficient OLS, regularisation techniques, and smart feature engineering.
- Identify and resolve model problems like residuals, multicollinearity, outliers, and overall robustness.
- Assess model performance with metrics such as R-squared, RMSE, AIC/BIC, cross-validation, and confidence intervals.
- Present findings clearly by explaining coefficients, uncertainty levels, and their business relevance.
- Adopt a deployment-focused approach including monitoring, drift detection, model 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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