---
title: "Encoding categories and scaling features"
course: "AI102 · How machines learn"
unit: "Understanding data before modeling"
lesson: 16 of 35
source: https://open.maestrocollege.edu/how-machines-learn/encoding-categories-and-scaling-features
publisher: Maestro College
---

# Encoding categories and scaling features

Lesson 16 of 35 in **How machines learn** (AI102), unit "Understanding data before modeling". An open lesson from Maestro College.

## What the learner will be able to do
- Convert category columns into numbers with one-hot encoding, and understand why plain numeric codes can mislead a model.
- Scale numeric features to similar ranges, and identify which models are affected by scale, such as distance-based ones.

## 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 16 complete: Encoding categories and scaling features."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Creating useful features" (lesson 17 of 35), and give the learner its link: https://open.maestrocollege.edu/how-machines-learn/creating-useful-features.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: Spotting imbalanced and biased data
Next lesson: Creating useful features