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Module Checkpoints

Guide Fit

flowchart TD
  family["Reproducible Research"] --> program["Deep Dive DVC"]
  program --> pressure["A concrete learner or reviewer question"]
  pressure --> guide["Module Checkpoints"]
  guide --> next["Modules, capstone, and reference surfaces"]
flowchart TD
  question["Name the exact question you need answered"] --> skim["Skim only the sections that match that pressure"]
  skim --> crosscheck["Open the linked module, proof surface, or capstone route"]
  crosscheck --> next_move["Leave with one next decision, page, or command"]

Read the first diagram as a timing map: this guide is for a named pressure, not for wandering the whole course-book. Read the second diagram as the guide loop: arrive with a concrete question, use only the matching sections, then leave with one smaller and more honest next move.

This page is the missing study contract at the end of each module. It gives a human bar for readiness instead of assuming that reading the prose once means the concept is stable.

Use it when you are about to move on and want to know whether you are ready, what you are still fuzzy on, and which proof route should settle the question.

How To Use The Checkpoints

For each module:

  1. read the module overview and main lessons
  2. answer the checkpoint questions without looking at the text
  3. run the smallest honest proof route
  4. only advance when the concept feels explainable, not merely recognizable

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Checkpoint Table

Module You are ready when you can explain You should be able to do Useful proof route
01 why reruns and saved files are weaker than explicit state contracts name the missing trust question in a weak reproducibility story capstone-tour
02 why content identity is not the same thing as file location distinguish workspace, cache, remote, and lockfile roles capstone-verify
03 why environments belong in the state model explain why the runtime boundary affects reproducibility truth capstone-verify
04 how dvc.yaml and dvc.lock should tell one consistent story review whether a pipeline edge is really declared capstone-repro
05 what a metric or parameter comparison is allowed to mean explain which controls must stay semantically stable capstone-verify
06 how experiments can vary state without mutating the baseline contract compare runs without muddying baseline truth capstone-experiment-review
07 what another person should be able to rerun and review explain which collaboration boundary protects trust capstone-confirm
08 what survives cache loss and what only looked durable describe the recovery story without hand-waving capstone-recovery-review
09 what makes a promoted state surface small enough to trust review whether downstream trust is smaller than repo complexity capstone-release-review
10 when DVC should stop owning the problem review a repository as a long-lived product with migration judgment capstone-confirm

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Failure Signals

Do not advance yet if any of these are still true:

  • you recognize the term but cannot explain the trust question it settles
  • you know the strongest proof command but not the smallest honest one
  • you can follow the capstone mechanically but cannot name the authoritative layer
  • you can repeat the repair pattern but cannot say what failure it prevents

These are not small study gaps. They are signals that the next module will feel more administrative than it should.

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Best Companion Pages

Use these with the checkpoints:

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