Linear Models Course
This comprehensive Linear Models Mastery Course equips statistics professionals with hands-on expertise to build, diagnose, validate, and deploy robust linear regression models. From initial data preparation through feature engineering and regularization, to interpreting coefficients, managing uncertainty, and delivering actionable business insights, you'll transform raw data into powerful predictive tools ready for real-world applications.
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. Delve into data exploration, feature engineering, and fitting simple, multiple, and regularized models with Python or R. Master model validation, assumption checks, outlier and missing data handling, plus effective communication of results, uncertainty, and business implications for informed decisions.
Elevify advantages
Develop skills
- Build strong linear models quickly using OLS, regularization techniques, and smart feature engineering.
- Identify and fix 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 key business impacts.
- Adopt a deployment-focused approach including model 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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