---
title: "Running your first model template"
course: "AI102 · How machines learn"
unit: "Seeing problems as ML problems"
lesson: 9 of 35
source: https://open.maestrocollege.edu/how-machines-learn/running-your-first-model-template
publisher: Maestro College
---

# Running your first model template

Lesson 9 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
- Run a provided template in VS Code and read its output.
- Load a dataset, train a model with fit, and generate predictions with predict by editing only the marked lines.
- Match each part of the template to a stage of the ML workflow loop.

## Teaching notes
Provide a ready-made template that trains scikit-learn's nearest-neighbor classifier on a small labeled dataset, so learners see the library version of their AI101 model.

## 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 9 complete: Running your first model template."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Challenge: framing ML problems" (lesson 10 of 35), and give the learner its link: https://open.maestrocollege.edu/how-machines-learn/challenge-framing-ml-problems.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: Setting up your ML workspace in VS Code
Next lesson: Challenge: framing ML problems