Assess learners' ability to apply linear regression to professional datasets by building and validating predictive models, selecting and transforming features, checking core assumptions (linearity, homoscedasticity, normality, multicollinearity), estimating and testing coefficients with confidence intervals, interpreting R^2/adjusted R^2 and RMSE, using diagnostic plots, and communicating actionable insights and limitations to stakeholders.