LESSON 2

Machine Learning Basics

Learning objective: Understand how machines learn from data.

Understand

Machine learning is the engine behind most AI.

In machine learning, a model is trained on examples so it can make predictions on new data. Give it labelled photos of cats and dogs, and it learns to tell them apart. More and better data usually means better results.

Analogy: Training a model is like teaching a child with flashcards until they recognize the pattern.

See It in Action

The core training loop:

Data -> Train model -> Test -> Improve -> Predict
How it works: The model learns from data, is tested, improved, and then used to predict on new inputs.

Try It Yourself

  1. Think of a prediction you would want an AI to make.
  2. List what data it would need.
  3. Decide how you would know it works.

Quick Quiz

What does a machine learning model learn from?

Challenge

Pick a prediction task and describe the data needed to train a model for it.

Success condition: You can outline how a model would be trained for a task.