---
title: "The ML workflow loop"
course: "AI102 · How machines learn"
unit: "Seeing problems as ML problems"
lesson: 7 of 35
source: https://open.maestrocollege.edu/how-machines-learn/the-ml-workflow-loop
publisher: Maestro College
---

# The ML workflow loop

Lesson 7 of 35 in **How machines learn** (AI102), unit "Seeing problems as ML problems". An open lesson from Maestro College.

## What the learner will be able to do
- Put the workflow stages in order: frame, explore, split, prepare using training data only, train, evaluate against a baseline, diagnose, and decide.
- Understand why the loop repeats until the result is good enough, and identify which stage a described mistake belongs to.

## Teaching notes
Create an illustration that shows the workflow stages as a loop with an arrow back from decide to frame.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 7 complete: The ML workflow loop."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Setting up your ML workspace in VS Code" (lesson 8 of 35), and give the learner its link: https://open.maestrocollege.edu/how-machines-learn/setting-up-your-ml-workspace-in-vs-code.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: Regression, classification, and clustering
Next lesson: Setting up your ML workspace in VS Code