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AI Literacy · Stage 5

Data → Train → Predict

Every learning machine follows the same three steps, always in order: first gather the DATA, then TRAIN to find the pattern, then PREDICT on something new.

✦ AI Literacy📘 Stage 5 · S5⏱ ~9 min🧒 Ages 9–10★ Free to start
I can describe data, training, then prediction.
Start the free lesson →⬇ Printable PDF
Kavi the owl for AI Literacy
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Kavi Teaches a Machine to Spot Cats

Kavi the owl wants to teach a little machine to spot cats 🐱. "First," she hoots, "I show it a big pile of cat photos — that pile is the DATA." The machine studies them and slowly works out what all cats have in common. "That part is TRAINING!" Then Kavi holds up a brand-new photo it has never seen before. The machine thinks, then guesses: "Cat!" "And THAT," cheers Kavi, "is PREDICTING. Data first, then training, then prediction — always in that order. You can never skip a step!"

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What your child will learn

1Data → Train → PredictEvery learning machine follows the SAME three steps, always in this order. Tap each one to hear it!
2Sort each job into its stepHere are jobs a machine does while it learns. Which step does each one belong to — Data, Train, or Predict? Tap a bin for each one!
3What comes next?You know the order now: data → train → predict. Pick what happens next, then tap to check. Tap Next test for more.
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A peek inside

Put these three steps in order: train, predict, data. Which comes first, which second, which last?
Nothing can happen without examples, so DATA comes first. Next the machine studies those examples to find the pattern — that is TRAIN. Only after it is trained can it guess on something new — that is PREDICT. So the order is data, then train, then predict.

Try this at home: What are the three steps, in order, for a machine to learn?

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Questions parents ask

+What are the three steps a machine follows to learn?

Data, then training, then prediction. First you gather lots of examples (the DATA). Then the machine studies them and finds the pattern inside (TRAINING). Only then can it make a guess about something new it has never seen (PREDICTION). The order never changes: data → train → predict.

+What is training data?

Training data is the pile of examples you give a machine so it can learn — like hundreds of photos labelled 'cat' or 'not cat'. In the training step, the machine looks through this data and finds what the examples have in common.

+Why can't an AI predict before it is trained?

Before training, the machine has not found any pattern yet, so it has nothing to base a guess on. It has to gather data and train first. Each step depends on the one before it — no data means no training, and no training means no good prediction.

+What is the difference between training and predicting?

Training is the learning step: the machine studies the data you already have and finds the pattern. Predicting is the using step: the trained machine makes a guess about a brand-new thing it has never seen. You train once on old examples, then predict many times on new ones.

+What happens if the data is bad?

Then the training and the predictions can go wrong too. A machine only learns from the examples it is shown, so if the data is one-sided or full of mistakes, the pattern it finds will be off and its guesses will be off as well. Good data in, good guesses out.

+What age is this 'Data, Train, Predict' lesson for?

It is a Stage 5 lesson for roughly ages 10–11 in KAVI Academy's AI-literacy track. It uses a story, a step-by-step flow, sorting and ordering games, with reading.

+Is the lesson free?

Yes — this overview and the printable PDF handout are free. The full interactive lesson and the endless practice are part of KAVI Academy.

Ready to play and learn?

Start the free interactive lesson, or print the handout for screen-free play.

Start the free lesson →⬇ Download PDF

Part of AI Literacy · Stage 5 · S5 on KAVI Academy — a secular, whole-child learning platform for ages 5–12.