Linear Models Course
This course equips statistics professionals with essential skills to build, diagnose, and deploy robust linear models. From data preparation to interpreting coefficients for business insights, learn to handle bias, uncertainty, and real-world challenges while ensuring models are reliable and actionable in professional settings.
from 4 to 360h flexible workload
certificate valid in your country
What will I learn?
Gain practical skills to create reliable predictive models using linear regression techniques. Explore data analysis, feature engineering, and fitting simple, multiple, and regularized models with Python or R. Master model validation, assumption checks, outlier management, missing data handling, and effective communication of results, uncertainty, and business implications for informed decisions.
Elevify advantages
Develop skills
- Build strong linear models using OLS, regularization, and smart feature engineering.
- Diagnose problems like residuals, multicollinearity, outliers, and model robustness.
- Evaluate performance with R-squared, RMSE, AIC/BIC, cross-validation, and confidence intervals.
- Communicate findings by explaining coefficients, uncertainty, and business value clearly.
- 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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