What should the best AI classes in Townsville teach?
How models are trained, tested and stopped, using real data a learner can check, rather than only how to call an AI tool. The Townsville urban area counted 179,011 people at the 2021 Census. We teach AI and programming live online, one to one or in small groups at the same level, and the first lesson is free.
Ask a model to predict how many minutes a Townsville bus takes between two stops, given only the distance between them. The open timetable gives us 719 such stop-to-stop segments to learn from. Train a deliberately flexible model on 60 of them and something strange happens. Its error on those 60 keeps falling for as long as you let it run. Its error on 240 segments it has never seen falls too, for a while, and then rises, and keeps rising until the model is useless. The right moment to stop was epoch 400. Our Townsville learners watch this happen, write the rule that stops training at the right time, and learn why "more training" is not the same as "a better model".
Facts last verified 7 October 2026. Teaching is online; no Townsville branch is claimed.
Matched to your goal first, then to your level during the trial lesson. Payment details are never collected up front.

Machine learning built up from simple models, with training curves drawn and read by the learner.
See the syllabus
Training, validation, overfitting and regularisation, implemented by hand before any library is used.
See the syllabus
Working with real timetables and datasets, the part of AI that decides whether models can learn anything at all.
See the syllabus
How large models are trained and used, with the same habits of testing and checking applied to them.
See the syllabusBrowse the course atlas for more than one hundred options and use the coding roadmap to check prerequisites.
The four we are known for
These run underneath everything above. Every one is live and online, placed by ability rather than by age, and the first class is free.

Python, web and AI projects where the learner still owns the thinking.
See the syllabus
Automate the work you already do, then let AI carry part of it.
See the syllabus
Train a model, read what it learned, and be able to say why it is wrong.
See the syllabus
Run AI coding agents on real work without losing control of the codebase.
See the syllabusCensus 2021 QuickStats for the Townsville Significant Urban Area, with the Queensland and Australian figures the bureau shows alongside.
| Measure | Townsville | Queensland share | Australian share |
|---|---|---|---|
| People | 179,011 | Not shown | Not shown |
| Median age | 35 | Not shown | Not shown |
| Families | 45,989 | Not shown | Not shown |
| Private dwellings | 75,844 | Not shown | Not shown |
| Separate houses among occupied dwellings | 51,876, or 80.1% | 74.8% | Not shown |
| Professional workers | 17,600, or 20.0% | 21.4% | 24.0% |
| Bachelor degree or above, aged 15 and over | 26,584, or 18.4% | 21.9% | 26.3% |
Half of Townsville's residents were 35 or younger in 2021, a year below the median of 36 for Greater Brisbane.
The Census counted 14,528 residents aged 20 to 24, 8.1% of the population, and 12,203 aged 15 to 19.
Technicians and trades workers number 12,628, or 14.4% of employed residents, against 13.7% across Queensland.
About these numbers: small census cells are randomly adjusted by the ABS for privacy, so parts of a table may not match the total. We repeat the bureau's totals and shares without adding rows together.
All 719 stop-to-stop segments in Translink's open Townsville timetable, and a model that predicts scheduled minutes from distance.
| What we counted | Result |
|---|---|
| Routes, stops and trips in the file | 17 routes, 638 stops, 992 trips |
| Distinct pairs of consecutive stops | 719 |
| Middle straight-line distance between stops | 394 m |
| Middle scheduled time between stops | 1 minute |
| Pairs timetabled at 0 minutes | 138, because times are whole minutes |
| Training, validation and test pairs | 60, 240 and 419 |
| Training epochs | Error on the 60 training pairs | Error on the 240 validation pairs |
|---|---|---|
| 100 | 0.611 | 38.2 |
| 400 | 0.462 | 1.43, the lowest |
| 1,000 | 0.458 | 15.2 |
| 5,000 | 0.452 | 268.4 |
| 100,000 | 0.443 | 2,727.5 |
| 200,000 | 0.442 | 1,619.7 |
The model only ever learns from 60 pairs. Another 240 are kept aside to measure how it does on stops it has never seen, and 419 more are saved for one final test.
Training error keeps falling, which looks like progress. Validation error bottoms out at epoch 400 and then climbs, which shows the model memorising its 60 examples instead of learning the pattern.
Early stopping keeps the weights from the epoch with the lowest validation error and halts once 2,000 more epochs bring no improvement. Here that rule fires at epoch 2,400.
On the 419 test pairs, the weights saved at epoch 400 score an error of 1.069. The weights after 200,000 epochs score 4,509.9, thousands of times worse. A simple straight line fitted to the same 60 pairs scores 1.196, with buses taking about 3.7 minutes per kilometre of straight-line distance. The flexible model only beats the straight line because it was stopped early.
These are our numbers from the timetable valid 7 October to 6 December 2026. The model is a degree-9 polynomial, chosen because it overfits clearly; our reading is that its validation error explodes mainly on segments longer than any in the training set, where a high-degree curve swings wildly. Scheduled minutes are not measured travel times.
Learned on bus segments, then applied to any model trained by repeated steps, from small regressions to neural networks.
| Habit | In practice | What it prevents |
|---|---|---|
| Split before you start | Training, validation and test sets fixed in advance | Fooling yourself with data the model has seen |
| Plot both curves | Training and validation error by epoch | Mistaking memorisation for learning |
| Keep the winning weights | Save whenever validation improves | Ending up with the last weights instead of the strongest |
| Use patience | Stop after a set number of epochs without improvement | Stopping on random noise |
| Test once, at the end | Touch the test set only after all choices are made | A test score that is secretly a validation score |
The last habit is the hardest to keep. Once you have looked at test results and changed something, the test set has become part of your decisions, and its score no longer measures performance on genuinely new data. Our learners keep the 419 test segments locked away until the very end.
Fit a straight line and a curve to the bus segments in Python, draw both error curves and write the early stopping rule.
Early stopping alongside weight decay and dropout, and why each one works, with experiments on real data.
Question any model your employer builds or buys about its validation data and the point at which its training ended.
No transport operator, government department or statistics office is involved with our classes. Census figures come from the ABS, the timetable is public, and every segment count, error value and curve here was produced by code we wrote.
Local facts with a data angle.
The Townsville file lists 17 routes, from the Ferry Terminal and the city out to suburbs such as Kelso and Bushland Beach, run by Kinetic for Translink.
State schools in Townsville are back on Tuesday 6 October 2026 and break up on Friday 11 December, per the education department calendar.
Queensland has stayed on UTC+10 all year since 1992, so Townsville timetables never have to handle a clock change.
Whole minutes and zero-minute hops
Because the timetable records times to the minute, 138 consecutive stops are scheduled 0 minutes apart. A model has to cope with that rounding, and a learner has to decide whether those rows are data or noise before training anything.
Treat the ages loosely; where you begin is settled in the free session.
Reading the timetable, working out distances between stops and plotting minutes against metres.
Python for TeensData Science for TeensLines and curves fitted by gradient descent, with training and validation curves drawn by hand.
AI and Machine Learning for TeensStatistics & ProbabilityOverfitting, early stopping, regularisation and model selection, tested on real datasets.
AI and ML MasterclassData Science CourseEvaluating and maintaining models that make decisions at work.
Generative AI CoursePython Automation CourseBecause every model, large or small, faces the same question our bus model does: is it learning, or memorising?
Models of every size are trained in steps, checked against data held back, and saved at checkpoints, the same ideas our learners meet on 60 bus segments. Seeing a validation curve turn upward at epoch 400 while training error keeps falling makes those ideas concrete in a way no explanation can, and it explains why a model can perform beautifully on familiar examples and badly on new ones.
A Townsville learner who has watched that happen asks better questions of any AI system: what was it tested on, how was that kept separate, and what happens on cases unlike its training data? Those questions apply equally to a chatbot's answers and to a model built at work.
AI will keep getting more capable, and a Townsville learner who understands why models fail on new data will be the one trusted to build and judge them in 2026. The longer argument is in why coding still matters in 2026.
Townsville stretches along the coast and inland, and an online lesson reaches every suburb without a car or a bus.
A learner near the Strand and another out at Kelso join the same lesson at the same time from home.
Teachers use Queensland year levels, from Year 7 to Year 12, and all lessons run in English.
The first, unpaid session has you training something small while the teacher watches, and it closes with advice on stage, course and slot. There is no card to enter.
Learners at the same stage from North Queensland, the rest of Australia and abroad, so every level has a sensible slot.
About eight lessons a month at a fixed time, with holidays and exam periods planned with the teacher.
Neither North Queensland nor India adjusts its clocks, which fixes the distance to our teachers at four and a half hours.
A 4pm lesson stays at 4pm
With no clock changes on either side, a Townsville lesson at 4pm begins at 11:30am in India in every month of the year.
Three figures, nothing hidden.
One free lesson that ends with a level, a recommended course and a weekly time.
A month of tuition, normally eight lessons, with fifteen to twenty learners at your stage.
Roughly eight private lessons a month with a single teacher.
North Queensland families pay in US dollars at the same single rate as everyone outside India, with no regional loading. Billing starts only once the trial has fixed a course and time; the pricing page explains holidays, missed lessons and changing format.
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We pick a first task that fits: charting bus segments for a Year 8, a first model and its error curves for a Year 11, or the full early stopping experiment for an adult.
What Townsville learners and families often ask first.
The 2021 Census counted 179,011, and half were 35 or younger.
Early stopping is a training rule that watches a model's error on validation data it does not learn from, keeps the weights from its lowest-error point, and ends training once that error stops improving for a set number of steps. It prevents a model from memorising its training examples.
Overfitting is when a model fits its training data more and more closely while getting worse on new data. In our Townsville project the training error keeps falling while the validation error rises from 1.43 to over 2,700.
Learners take the 719 stop-to-stop segments in Translink's open Townsville timetable, train a flexible model to predict scheduled minutes from distance on 60 of them, and watch validation error reach its lowest point at epoch 400 before rising. Early stopping keeps the epoch-400 model, which beats a straight line on the final test.
No. Teenagers start with charts and straight lines, and the ideas of training and validation make sense once they have seen the curves. The maths deepens as learners are ready for it.
Between the end of school and dinner, or at the weekend, settled during the trial and always quoted in Townsville time; India runs four and a half hours behind, year round.
They can, from six years old, usually through Scratch first; this page is written with older students and adults in mind.
No, and none is claimed. All teaching is live and online, with no premises anywhere in Australia. A learner needs a laptop or desktop, working sound and a reliable connection, and the contact number shown is an Indian one.
The first lesson is free. After that a group place is USD 100 a month for two live lessons a week, around eight a month, with fifteen to twenty learners, or USD 150 a month for the same pattern one to one. Course, format and time are agreed before anything is paid.
Fifteen to twenty learners, matched on level, pace and what they want to build rather than on age or suburb. If no suitable group meets at a workable time, one-to-one lessons are offered instead.
Teenagers keen on AI can read the Python AI course for younger learners or AI classes for teens in Australia. Further south, see AI and programming on the Sunshine Coast, and the state guide is coding and AI classes in Queensland.