What are the best vibe coding and AI agents classes in Melbourne?
Ones where the learner directs the AI and can still prove its work is right. Vibe coding means building software by describing it to an AI assistant; an AI agent is a program that uses tools to act on a goal. Greater Melbourne counted 4,917,750 people in 2021. We teach both live online to teens and adults, privately or in a small group at the same standard, alongside Python, maths and VCE technique, and the trial lesson is free.
Here is a small AI agent a Melbourne learner can build in an afternoon: ask it where the nearest tram stop is, and it calls a tool that searches the 1,603 tram stop points OpenStreetMap records across inner Melbourne. The tool works. Then someone tidies the code and swaps the careful distance formula for a quicker one that treats a degree of longitude as if it were as long as a degree of latitude. In Melbourne it is not. Is the agent still right? Nobody can tell by reading the answers, because they all sound fine. So our learners write 300 test questions with known correct answers, a golden set, and run every version of the tool against it before anything ships. The quicker formula gets 21 of the 300 wrong.
Facts last verified 7 October 2026. Teaching is online; no Melbourne branch is claimed.
Chosen by what the learner wants to build. Every course starts with a free lesson and no card details.

First Python and first AI experiments, with a teacher checking that the child understands every line the computer runs.
See the syllabus
Building real apps by describing them to AI tools, then testing what comes back until the learner can defend every part.
See the syllabus
How models learn, how they fail and how to measure both, the grounding a student needs before trusting an agent.
See the syllabus
Full-stack projects built with AI assistants, plus the algorithms and tests that keep generated code honest.
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 syllabusSelected QuickStats rows for the Greater Melbourne capital city area, each beside the figure for Australia.
| Measure | Greater Melbourne | Australia |
|---|---|---|
| People | 4,917,750 | Not compared |
| Median age | 37 | 38 |
| Families | 1,299,184 | Not compared |
| Private dwellings | 2,057,482 | Not compared |
| Residents aged 25 to 29 | 383,135, or 7.8% | 7.0% |
| Employed people working as professionals | 656,333, or 26.8% | 24.0% |
In 2021, 6.7% of Greater Melbourne residents were aged 20 to 24, 328,543 people, against 6.2% across Australia.
Professionals were 26.8% of employed Melbourne residents aged 15 and over, against 24.0% nationally: the group most likely to be handed AI agents at work.
Flats and apartments were 15.6% of occupied homes in Greater Melbourne, 277,512 of them, close to the national 14.2%.
All figures are the Australian Bureau of Statistics' published totals and shares. Census tables are adjusted separately to protect privacy, so the parts are never added up here to produce a figure of our own. Live data for the city is published too: the Bureau of Meteorology's half-hourly capital city observations for Melbourne come from the station it names Melbourne (Olympic Park), a feed our older learners use when they first point an agent at data that changes while they watch.
Two phrases everyone is searching for, and what they mean in a real lesson.
Describing what you want to an AI assistant in plain English and letting it write the code. It is fast and genuinely useful. In our lessons the learner then reads, runs and tests every piece until they can explain it without the assistant.
Programs that take a goal, decide which tool to call, read the result and keep going. Our learners build small ones that answer questions from real data, such as Melbourne's tram stops, and then measure how often they are right.
Every agent or vibe-coded app gets a golden set: questions with known answers that it must pass before and after any change. It is the cheapest insurance in software, and it is the centre of our Melbourne project.
Who this suits
Teenagers who already build things with AI tools and want to understand them, university students whose courses now expect it, and adults across Melbourne's professional workforce who want agents at work without handing over their judgement.
An agent tool that finds the nearest tram stop, three versions of its distance code, and 300 test questions with answers we already know.
| Tool version | Answers naming the wrong stop | Worst extra walk |
|---|---|---|
| Careful: longitude scaled by the cosine of the latitude | 0 of 300 | None |
| Quick: raw degrees, as if latitude and longitude were equal | 21 of 300 | 79.1 metres |
| Refactor bug: latitude and longitude swapped | 300 of 300 | Kilometres |
Pick 300 points, each within 400 metres of a real tram stop, and work out the true nearest stop for each with the haversine formula. The answers are typically 157 metres away and never more than 396.
The careful tool matches all 300. The quick one names a different stop 21 times, a 7% failure rate that no single test would reveal. The swapped version fails everything, which any test catches.
A random handful of 10 golden questions catches the quick version only about half the time. Thirty catch it 89.9% of the time, and fifty 98.1%.
Melbourne sits about 37.8 degrees south, where a degree of longitude covers only about 79% of the ground a degree of latitude does. Treat them as equal and the tool quietly favours stops to the east or west. Among the answers that chose a farther stop point, half added less than two metres to the walk, which is exactly why nobody notices them; the worst added 79.1. A golden set notices.
The stop list is an OpenStreetMap snapshot taken on 7 October 2026 for a rectangle we chose over central and inner Melbourne. OpenStreetMap records each side of the road as a separate stop point, so the 1,603 points carry 916 distinct names; some answers counted as different points still share a name. The golden answers are straight-line distances, not walking routes, and nothing here describes the tram network's service or timetables.
From the Victorian Curriculum and Assessment Authority's study design pages. We teach the technique these studies draw on; assessed work is always the student's own.
| Study | Accreditation | What VCAA lists |
|---|---|---|
| VCE Algorithmics (HESS) | Units 3 and 4, from 2023 | Unit 3 Algorithmic problem-solving; areas of study on data modelling with abstract data types, algorithm design and applied algorithms; a School-assessed Task |
| VCE Applied Computing | Units 1 to 4, from 2025 | 2026 school-based assessment information for Data Analytics and for Software Development |
VCAA's planning advice for Algorithmics lists several ways to analyse an algorithm's running time, from step counting to the Master Theorem and measuring how long implemented code actually takes. The golden-set project above is the measuring kind of thinking that advice describes, applied to whether an answer is right rather than how fast it arrives.
Graphs, search and algorithm design written in real code, with complexity worked out by hand and then checked by experiment.
Data analysis and software development projects, with the documentation and testing habits a School-assessed Task rewards.
School-assessed Tasks belong to the student under VCAA rules. We teach methods and give feedback on practice work, never on the assessed task itself.
The bands are a guide. The free lesson sets the starting level.
Making small programs with and without AI help, and noticing when the computer did something nobody asked for.
Python and AI for KidsScratch Coding for KidsApps built by describing them to an AI tool, then read line by line and tested on cases chosen to break them.
Vibe Coding for TeensPython for TeensAgents that call tools on real data, golden sets, failure rates and the algorithm thinking VCE Algorithmics expects.
AI and Machine Learning for TeensProblem Solving for TeensBuilding and evaluating agents for real tasks, and knowing which decisions should never leave a person's hands.
Vibe Coding for CollegeGenerative AI CourseBecause the quick version of our tram-stop tool sounded right in all 300 answers and was wrong in 21 of them.
An agent that answers in a confident sentence gives no sign when it is wrong. The quick tool never crashed, never raised an error and never produced an absurd result; it simply chose a slightly farther stop about one time in fourteen. A person reading a few answers would approve it. Only a set of questions with known answers, run before and after the change, exposes the drift, and only someone who understands the distance formula can say why it happened and fix it.
That is the job vibe coding creates rather than removes. When an assistant writes more of the code, the human's work shifts to deciding what correct means, writing the tests that prove it and reading failures with understanding. A Melbourne learner who has watched 10 golden questions miss a 7% failure rate half the time will never again trust an agent on the strength of a short demo.
So the reason to learn to code in 2026 is not to compete with AI at typing. It is to be the person who can tell a working agent from a plausible one, and that takes knowing how the code underneath behaves. The longer argument is in whether coding is still worth learning in 2026.
From the inner north to the Mornington Peninsula, the commute to class is the walk to a laptop.
A teenager in the inner north and an adult in the outer east can share one lesson from their own desks.
Teachers say Foundation, Year 9 or Unit 3 the way a Victorian school does, and plan around the four Victorian terms. Teaching is in English.
The trial is a full working lesson. The teacher then proposes a level, a course and a regular hour, and no payment details are requested.
A group is fifteen to twenty people at a similar point, gathered from Victoria, other states and other countries, so a reasonable hour exists for nearly every level.
Normally two sessions a week, roughly eight a month, with breaks for Victorian holidays and the VCE exam period arranged ahead of time.
Melbourne moves its clocks on the same Sundays as Sydney, 4 October 2026 and 4 April 2027, so our teachers are five and a half hours behind Melbourne in summer and four and a half in winter.
The Victorian school year
The Victorian Government lists Term 4 of 2026 as Monday 5 October to Friday 18 December, and Term 1 of 2027 opening on Wednesday 27 January, with students in government schools starting on 28 January. It calls the first year of primary school Foundation or Prep: a child starting Foundation (Prep) in 2027 needs to turn 5 by 30 April 2027. Course plans follow those dates.
Three figures, and nothing hidden behind them.
A full lesson at no cost, ending with a recommended level, course and weekly time.
A month of teaching, usually eight lessons, with fifteen to twenty learners at the same level.
The same monthly rhythm of around eight lessons, one teacher and one learner.
One price in US dollars applies to every learner outside India, so Brunswick and Frankston receive the same invoice and there is no Melbourne price sheet. You pay only once the trial has settled what to study and when; breaks, missed sessions and moves between group and private teaching are set out on the pricing page.
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The first task fits the learner: a first AI-assisted program for a younger teen, a vibe-coded app with tests for a confident one, or the tram-stop golden set for anyone who wants to see an agent fail.
What Melbourne learners and families ask us first.
Vibe coding is building software by describing what you want to an AI assistant and letting it write the code. In our classes the learner then reads, runs and tests that code until they understand it and can change it themselves.
An AI agent is a program that takes a goal, chooses tools to use, reads their results and keeps working towards the goal. Our learners build small agents that answer questions from real data and then measure how often they are right.
A golden set is a collection of test questions whose correct answers are already known. Every version of an agent or tool is run against it, so a change that quietly breaks some answers is caught before anyone relies on it.
Learners build a nearest-tram-stop tool on 1,603 OpenStreetMap stop points, write 300 golden questions and test three versions of the distance code. The quick version gets 21 answers wrong; the careful one gets none.
QuickStats gives Greater Melbourne 4,917,750 residents at the August 2021 count, with a median age of 37, one year under the Australian median of 38.
We teach the algorithm design, data structures and analysis that VCE Algorithmics (HESS) draws on. School-assessed Tasks are the student's own work under VCAA rules, and we never work on any assessed task.
Weekday afternoons and evenings or weekend slots, settled at the trial and always quoted in Melbourne time. India sits four and a half hours behind Melbourne from April to October and five and a half behind over summer.
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.
For machine learning in more depth, read AI and machine learning classes in Australia. North of the Murray, our Sydney page hunts for a median bus stop and the New South Wales page explains the HSC. Start from the Australia coding page for every other Australian guide.