The Whole Pipeline
A model is built in four stages, always in the same order: gather the data, train on it, test on examples it never saw, then predict on real inputs. This lesson walks the whole pipeline end to end.
Kavi Builds a Berry-Sorter
Kavi the owl wants a machine that sorts ripe berries from unripe ones. She can't just switch it on. First she fills a basket and labels every berry ripe or unripe — that is the data. Then the machine studies them until it spots the pattern — train. But has it really learned? Kavi hides a handful of berries it never saw and checks its guesses — test. Only when it passes does she let it loose on today's fresh, unlabelled harvest — predict. "Four stages, always in order," hoots Kavi. "Data, train, test, predict — that's the whole pipeline!"
What your child will learn
A peek inside
Try this at home: What are the four stages of a model pipeline, in order?
Questions parents ask
+What are the four stages of a model pipeline?
In order: Data (collect and label the examples), Train (the model studies the examples and learns the pattern), Test (check it on new examples it never saw, to measure how well it really learned), and Predict (use the finished model on brand-new real inputs to do its job).
+Why does the order of the stages matter?
Each stage needs the one before it. You cannot train with no data, you cannot fairly test a model that has not trained, and you only predict once the model has been trained and tested. The order is always Data → Train → Test → Predict.
+Why must a model be tested on examples it has never seen?
Testing on the same examples it trained on is like letting a student study the exact exam answers — it looks perfect but proves nothing. A fair test uses held-back, unseen examples, so the score shows real learning instead of memorising.
+What does it mean if a model scores high in training but low on the test?
It usually means the model memorised the training examples instead of learning the real pattern. On new examples the memorising falls apart. The fix is to loop back: get more or better data, train again, and test again.
+What age is this 'Whole Pipeline' lesson for?
It is a Stage 6 lesson for roughly ages 11–12 in KAVI Academy's AI-literacy track — the top of primary, ready for secondary. It uses a story, ordering and sorting games, and light 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.
Part of AI Literacy · Stage 6 · S6 on KAVI Academy — a secular, whole-child learning platform for ages 5–12.