Module 3 Review Checklist

Use this lesson as a gate. If you can walk through every checkbox with a concrete example from your notes or lab, you are ready to move on. If not, jump back to the matching lesson instead of collecting more checkpoints.

Intuition

Module 3 had three themes:

  1. Choose the right lever — prompt vs RAG vs fine-tune; SFT vs preferences.
  2. Adapt efficiently — freeze, LoRA/QLoRA, soft prompts, sane recipes.
  3. Prove it — baselines, holdout, anchors, serving, writeups.

How it works

3.1 Fundamentals checklist

3.2 PEFT checklist

3.3 Lab checklist

flowchart LR L1[Lever choice] --> L2[PEFT recipe] L2 --> L3[Eval scorecard] L3 --> L4[Serve + rollback] L4 --> L5[Writeup]

Oral exam prompts (self-test)

Try answering out loud in two minutes each:

  1. Why might training loss fall while product quality falls?
  2. When is DPO a better next step than more SFT rows?
  3. What breaks if you serve an adapter on the wrong base revision?
  4. How does alpha/r interact with a rank sweep?
  5. What is the first file you look at in a fine-tune incident?

In code

A programmatic checklist you can tick in a notebook.

CHECKS = [
    ("lever_choice", "Explained prompt vs RAG vs FT with one real failure"),
    ("sft_loss", "Stated what tokens receive SFT loss"),
    ("peft_formula", "Explained LoRA update W + scale*BA"),
    ("recipe", "Wrote a starting LoRA hyperparameter set"),
    ("baseline", "Saved prompt-only baseline metrics"),
    ("anchors", "Ran anchor regression on a checkpoint"),
    ("serving", "Chose merged vs adapter with a reason"),
    ("writeup", "Produced ship/no-ship with a scorecard"),
]


def review(done: dict[str, bool]) -> None:
    missing = [label for key, label in CHECKS if not done.get(key)]
    if not missing:
        print("Module 3 gate: PASS")
    else:
        print("Module 3 gate: incomplete")
        for m in missing:
            print(" -", m)


review({
    "lever_choice": True,
    "sft_loss": True,
    "peft_formula": True,
    "recipe": True,
    "baseline": True,
    "anchors": False,
    "serving": True,
    "writeup": False,
})

What goes wrong

Map lessons to skills

Skill Lessons
Lever choice 3.1.1
Data / templates 3.1.2
SFT mechanics 3.1.3
Freeze vs full 3.1.4
Eval / forgetting 3.1.5
RLHF / DPO map 3.1.6
PEFT intuition 3.2.1
LoRA / QLoRA 3.2.2
Soft prompts 3.2.3
Recipes 3.2.4
Serving 3.2.5
Lab loop 3.3.1–3.3.3

Capstone readiness

Module 4–5 projects will assume you can say "we tried prompt+RAG, measured X, then LoRA'd Y with scorecard Z." Practice that sentence with your lab numbers. If you cannot fill X/Y/Z, revisit the lab—not the architecture diagrams.

Time-boxed review

Spend 45 minutes: 15 on fundamentals checkboxes, 15 on PEFT, 15 rewriting your lab decision in five lines. If any checkbox takes more than two minutes of hand-waving, open that lesson and add an example from your domain before moving to Module 4.

One-line summary

Finish Module 3 by verifying you can choose levers, run PEFT deliberately, and prove outcomes with baselines, anchors, serving plans, and a clear writeup.

Key terms