Module 3 Overview#
Theme#
Linear and tree-based baselines
Essential Question#
Why do strong baselines matter before complex models?
Module Components#
Book prose: conceptual framing, domain scenario, methods, and failure modesAssignment: evidence-backed production of a specific artifactSlides: presentation sequence for seminar or lecture deliveryNarration: spoken version of the slide flowInstructor notes: facilitation plan, discussion prompts, and grading cuesRubric: criteria for evaluating the module artifactNotebook: executable lab aligned with the module theme using synthetic tabular observations with features, labels, train/test split, baseline score, and error slices
Module Artifact#
predictive modeling report with baseline comparison, validation evidence, and model card focused on linear and tree-based baselines: Compare logistic regression or linear regression with a tree model.
Professional Setting#
Students work as if advising an analytics team choosing a predictive model for an operational decision. Their work must be intelligible to analytics lead, domain owner, operations manager, and model risk reviewer.