Exercise 3: Why Two Specific Things Are Out of Scope, and Where Each Is Deferred — Possible Solution ==================================================================== WHY "NO ML MODELING" IS LISTED, PER THE SCOPE NOTE ------------------------------ Per this chapter's own scope note, "this capstone forms real hypotheses about what predicts attrition — it never builds, trains, or tests a model that actually predicts it. That's ml1's entire job, and this course's own boundary, stated since ds1-1." This matches exactly what Step 7 of this same chapter actually did: it raised specific, testable questions ("does lower salary predict a higher likelihood of leaving?") without ever attempting to build a system that outputs an actual prediction. Listing this as out of scope isn't a late addition — it's the same boundary ds1-1's own workflow (Collect → Clean → Explore → Model → Communicate) drew from the very first chapter, with "Model" marked out of scope there too. WHERE "NO ML MODELING" IS DEFERRED ------------------------------ Per the scope note, this is explicitly deferred to ml1 — the Machine Learning Fundamentals course, the very next course in the Data Science & ML subject's own roadmap, whose entire job (per this chapter's own closing quick-reference) is "picking up exactly where this course's own Explore/Model boundary leaves off." WHY "NO LIVE WEB SCRAPING OR API-BASED DATA COLLECTION" IS LISTED ------------------------------ Per the scope note, "all three datasets in this course... were provided directly." Every dataset used across this entire course — the coffee- shop sales table, the used-car listings, and this chapter's own employee table — was handed to the reader ready-made, with the Collect stage of ds1-1's own workflow never actually demonstrated hands-on anywhere in this course. This is a real, separate gap from "no ML modeling" — it's about a different stage of the workflow entirely (the very first one, not the fourth), one this course chose not to cover in depth even though ds1-1 named it as part of the full workflow. WHERE "NO LIVE WEB SCRAPING" IS DEFERRED ------------------------------ Per the scope note, this is explicitly deferred to "dsproj1's own first project, chosen specifically because it doesn't need ML at all" — the web-scraping/document-collection project named back in the Data Science & ML subject's own roadmap, deliberately positioned as an early, ML-free project specifically because real data collection is a genuine, separate skill from everything covered in this Fundamentals course. WHY BOTH GAPS ARE NAMED EXPLICITLY RATHER THAN LEFT IMPLICIT ------------------------------ Naming both gaps directly, along with exactly which future course or project resolves each one, follows the same honest-scoping pattern used throughout this site's other capstones — an explicit acknowledgment of what wasn't covered is itself evidence the omission was a deliberate scoping decision, not an oversight, and gives a reader a concrete next step for each specific gap rather than leaving them to wonder where (or whether) it gets addressed at all. WHY THIS WORKS AS AN ANSWER ------------------------------ It identifies the specific reasoning behind each of the two named gaps (the Model stage vs. the Collect stage of ds1-1's own workflow), and identifies precisely which future course (ml1) and which future project (dsproj1) the scope note itself names as resolving each one.