Australia · Ages 14 to adult · Question, clean, summarise, model

Data science course

Data science is the craft of turning a messy table into an answer you can defend. Before any model, it means choosing the right data, cleaning it, and summarising it in a way that does not mislead, which is harder than it sounds. Our data science course teaches Australians from 14 to adulthood to do all of that in Python, live online, using real public data from Australian agencies. This page sets out the approach, works through one example on the latest council population figures from the Australian Bureau of Statistics, and shows where the same skills appear in the Australian Curriculum and in the national occupation classification.

Book the free first class Book a priority demo See the worked example Ask on WhatsApp

Live teaching since 2020 · 10,000+ students · Real Australian data in every unit

In short

A data science course teaches how to collect, clean, summarise, visualise and model data to answer real questions, usually in Python. ANZSCO describes a data scientist as someone who applies analytical techniques and scientific procedures to large datasets. Modern Age Coders teaches data science live online to Australian teens from 14 and adults, with ABS and other public data, in small groups or one to one, and the first class is free.

Start here

Three data science courses

Picked by age and experience. Each card opens the syllabus.

Data Science for Teens course thumbnail

DSAU / 01

Data Science for Teens

Ages 14 to 18 with basic Python: real data, statistics and first models.

Open the syllabus →
Data Science Course course thumbnail

DSAU / 02

Data Science Course for Adults

For 18 and over: Python, machine learning and deep learning from the beginning.

Open the syllabus →
Statistics & Probability course thumbnail

DSAU / 03

Statistics and Probability

The maths underneath: distributions, averages and testing ideas against data.

Open the syllabus →

The cycle

Five steps, and the model is only one of them

Beginners rush to the model. Most of the work, and most of the mistakes, come earlier.

The data science cycle as taught in our course
StepThe question at this stepTypical trap
AskWhat exactly do we want to know, and for whom?A question too vague to answer
AcquireWhere does trustworthy data come from, and what does each row mean?Rows that are not what they seem, such as totals mixed with parts
CleanWhat is missing, duplicated or wrongly coded?Silently dropping awkward rows
Summarise and chartWhat is typical, and what is unusual?Reporting a mean for skewed data
Model and checkDoes a model beat a simple baseline on new data?Testing on the data used for training

Two occupations, one skill set

ANZSCO lists 224114 Data Analyst, who "Gathers, cleans and interprets data", and 224115 Data Scientist, who "Applies analytical techniques and scientific procedures to large datasets by creating advanced algorithms and data models".

The course covers the analyst's work first, because the scientist's work stands on it.

Why public data

Australian agencies publish high-quality data under open licences. Learners can check every number they produce against the source, which is the habit we want.

Real data is also messier than textbook data, and that mess is the lesson.

A worked example

The average council that does not exist

One question, asked of the ABS's 2025 estimated resident population for every local government area: how big is a typical Australian council?

We downloaded the 2025 figures from the ABS Data API. The file has 548 rows. Six are unincorporated areas, labelled as such in the ABS codelist, which are not councils, so a careful analyst sets them aside first and says so. That leaves 542 local government areas. Then come two different answers to "how big is a typical council?"

Summaries of 2025 council populations (our calculation from ABS data)
SummaryValueWhat it tells you
Mean (average)50,025Pulled up by a few very large councils
Median (middle council)13,306Half the councils are smaller than this
Councils above the mean134 of 542About one in four is above "average"
Largest councilBrisbane, 1,375,301Over 13,000 times the smallest
Smallest councilMaralinga Tjarutja, 102Its whole 2025 estimate

One council moves the mean

Take Brisbane out and the mean falls from 50,025 to 47,575. The median barely moves, from 13,306 to 13,264.

The simple summary wins

Here the plain median describes a typical council far better than the mean. A 10% trimmed mean, 28,921, sits in between and is still well above most councils.

Show the shape

A histogram on a log scale shows why: most councils are small, with a long tail of big cities. Students draw it before writing any summary.

The skill being taught

Choosing a summary is a decision, not a default. For skewed data such as populations, incomes or house sizes, the median usually tells the truth about the typical case, while the mean answers a different question: what each council would get if everyone were shared out equally.

Both are correct calculations. Only one fits the question asked.

Checking our own work

Every number above comes from one Python script that reads the ABS file directly. Learners rerun it, then change one thing at a time and predict the result before running it again.

We do not add the councils up to compare with a national total, because published parts and published totals are produced separately.

Source, read 14 October 2026: ABS Data API, Estimated Resident Population by LGA, 2025, Creative Commons Attribution 4.0. Summaries are our own calculations.

At school

Data skills in the Australian Curriculum

Students meet data handling in Digital Technologies well before senior school.

Years 7 and 8

Content description AC9TDI8P01 asks students to "acquire, store and validate data from a range of sources using software, including spreadsheets and databases".

Our course moves the same work from spreadsheets into Python, so it can be repeated, checked and scaled.

Years 9 and 10

By Year 10 the curriculum describes students visualising data "allowing greater exploration of trends and outliers to support or challenge their analyses".

The council example above is exactly that: an outlier challenging a summary.

Victorian senior students taking Data Analytics will find exam-specific help on our VCE Applied Computing: Data Analytics page. This course builds the general skills and never completes assessed work.

Sources, read 14 October 2026: ACARA, Digital Technologies curriculum content, Years 7 to 10; ABS, ANZSCO 2022 unit group 2241.

Projects

What learners build

Each project uses public data and ends with a short written finding a non-specialist can follow.

Project sequence in the data science course
ProjectDataMain skill
Typical councilABS population by local government areaMean, median and skew
Weather extremesPublic daily weather observationsCleaning gaps and spotting outliers
School holiday calendarState education department term datesDates, joins and tidy tables
Commuter patternsPublic transport usage filesGrouping, time series and charts
First modelA labelled public datasetTrain, test and beat a baseline

Learners drawn to the modelling end can continue with AI and machine learning classes. Those who want stronger programming habits first can take the software development course.

Charts

Choosing a chart that answers the question

A chart is an argument. Learners pick the type by the question, then check that it cannot be misread.

Questions and the charts that suit them
QuestionChart that fitsWhat to watch
How are values spread out?Histogram, often on a log scale for populationsBin widths that hide the shape
How do groups compare?Bar chart starting at zeroTruncated axes that exaggerate gaps
How does something change over time?Line chartMissing periods drawn as if continuous
Are two measures related?Scatter plotReading a pattern as cause and effect
What share does each part make?A sorted bar chart rather than many pie slicesParts that do not add up to the whole

The council data again

Drawn on an ordinary axis, the council populations look like one tall bar and hundreds of invisible ones. On a log scale the shape appears, and the gap between mean and median makes sense at a glance.

Learners draw both and write one sentence on what each would lead a reader to believe.

Charts with captions

Every chart in the course has a title that states the finding, a labelled source and a date.

If the caption cannot be written in one sentence, the chart is not finished.

Using data responsibly

Data about people needs care

Much useful data describes people. Learners practise handling it responsibly from the first project.

Aggregates, not individuals

Course datasets are chosen from aggregate public data, such as counts for a council or a month, so no individual can be identified.

Learners discuss why agencies adjust small counts and why those adjustments mean parts are not added up to match a published total.

Saying what the data cannot show

A finding is only as good as the data behind it. Each written result ends with one sentence on what the data does not cover.

That habit protects readers from conclusions the numbers cannot support.

Students who want to see how data skills connect to AI can read learn to train AI, not just prompt it.

Progress

Four levels of data skill

Progress is measured by what a learner can do with a fresh dataset, not by time served.

From table reader to modeller
LevelWhat you can do
1. ReaderLoad a public dataset and explain what each row and column means
2. CleanerFind and fix missing, duplicated and miscoded values, and record what you changed
3. AnalystChoose summaries and charts that fit the data and the question
4. ModellerTrain a model, test it on new data, and compare it with a simple baseline

How much maths is needed?

School maths is enough to begin. Averages, percentages and graphs come first; the statistics behind models is taught as it is needed.

Learners who want more depth can add our statistics course.

Is data science a guaranteed career?

We make no job or salary promises. The course builds real, checkable projects and the judgement behind them.

Those projects are what a learner can show and talk through.

The catalogue

Data courses

Grouped by stage. The free class decides where a learner starts.

I

Getting started

Teens and adults

DSAU / ST / 01

Data Science for Teens

Ages 14 to 18, basic Python.

Open the syllabus

DSAU / ST / 02

Data Analysis Course

Excel, SQL, Python and BI, 18+.

Open the syllabus

DSAU / ST / 03

Data and AI for Non-Programmers

Spreadsheets to dashboards.

Open the syllabus
II

The maths

Alongside the code

DSAU / MA / 01

Statistics and Probability

From data to hypothesis tests.

Open the syllabus

DSAU / MA / 02

Maths for Data Science

Statistics, linear algebra, ML.

Open the syllabus
III

Models

After the basics

DSAU / ML / 01

Data Science Course

Python, ML and deep learning, 18+.

Open the syllabus

DSAU / ML / 02

AI and Machine Learning for Teens

Models for 13 to 18.

Open the syllabus

DSAU / ML / 03

Orange Data Mining for College Students

Visual machine learning.

Open the syllabus

How lessons run

Data lessons in your time zone

Teachers are based in India, and the Indian working day overlaps Australian afternoons and evenings. Times are agreed in your state's time and adjusted for daylight saving.

After school

For teens in term time.

Evening

For adults, by arrangement.

Weekend

Longer analysis sessions.

Free first class

A real dataset loaded and one honest summary written.

Groups

Fifteen to twenty learners comparing answers to the same question.

One to one

For a particular dataset, job need or pace.

Sources shown

Every dataset is cited, with its licence and date.

Reproducible

Every result comes from a script the learner can rerun.

Code by the learner

Teachers guide; learners write and explain the code.

Student work

Student work, published

Applications our students built and published. Browse more in the student labs.

NutriLife AI nutrition coach project screenshot

AI and ML

NutriLife

An AI nutrition coach that reads what you eat and works you toward a target.

by Bhavya · Open it

Misti AI chatbot for maths and coding screenshot

AI and ML

Misti

A chatbot that answers mathematics and programming questions, built and deployed by a student.

by Harshit · Open it

GuardianX AI internet safety assistant screenshot

AI and ML

GuardianX

An assistant that helps a young person recognise unsafe situations online.

by Vivaan · Open it

SkyCast weather forecast application screenshot

Web app

SkyCast

A weather forecasting site with live conditions for any location.

by Krish

Fees

Fees for the data science course

Learners outside India pay a monthly fee in US dollars. Nothing is due at sign-up and there is no contract.

Free first class

USD 0

no card required

  • A dataset loaded and summarised in the lesson
  • Advice on where to start
  • No card details
Book it

Group batch

USD 100

a month, billed in US dollars

  • Fifteen to twenty learners per class
  • Shared datasets, compared answers
  • The same teacher each week
  • Stop after any month
Start here

One to one

USD 150

a month, billed in US dollars

  • Lessons around one learner's data
  • Flexible depth and pace
  • Times around school or work
Enquire

What families say

Rated 4.9 across 547 Google reviews

Published reviews from our Google profile, reproduced as written.

★★★★★

"The one step solution for my son. Modern Age Coders make learning coding so simple that kids love it. The teachers explain complex concepts clearly with practical exercises and interactive content."

Ria Mukherjee

Parent

★★★★★

"Modern Age Coders has been a game-changer for me. I struggled to grasp IT concepts and coding before joining, but their classes transformed everything. I can now confidently write complex programs with ease."

Samriddha Mondal

Student

★★★★★

"One of the most wonderful education centres out there. Education is not limited to school syllabus but focuses on skill development."

Vansh Agarwal

Student

★★★★★

"My child Dhairya is really enjoying the Modern Age Coders classes. This is his first online class and he eagerly looks forward to it. I can already see his improvement, and the teachers are very cooperative."

Sonam Oswal

Parent of Dhairya

★★★★★

"Modern Age Coders have wonderful teachers who teach in a clear, easy and practical way. The teacher boosts students' confidence and inspires them to learn without hesitation."

Sonu Goyal

Parent

★★★★★

"I highly recommend this computer coding class! The teachers are incredibly knowledgeable and passionate about coding."

Ritu Kedia

Parent

Learners ask

Questions about data science courses in Australia

What does a data science course teach?

How to ask a clear question, find and clean data, summarise and chart it honestly, and build and test simple models, usually in Python.

What is the difference between the mean and the median?

The mean adds everything up and divides by the count; the median is the middle value. For Australian councils in 2025 the mean is 50,025 residents but the median is 13,306, because a few large councils pull the mean up.

Do I need to know Python first?

Adults can start from zero in the adult course. The teen data science course expects basic Python, which our Python for Teens course provides.

What data do learners use?

Public Australian data such as ABS population figures, weather observations and transport usage, always cited with its licence.

What does ANZSCO say a data scientist does?

ANZSCO 224115 Data Scientist applies analytical techniques and scientific procedures to large datasets by creating advanced algorithms and data models.

How is this different from machine learning classes?

Data science covers the whole process from question to answer. Machine learning is one part of it, which our AI and machine learning classes cover in more depth.

Will this help with VCE Data Analytics?

It builds the general skills. Exam-specific help is on our VCE Data Analytics page, and we never complete assessed work.

What age can start?

From 14 with basic Python in the teen course, or 18 and over in the adult course.

Will I get a data job afterwards?

We do not promise jobs or salaries. The course gives you checkable projects and the judgement to explain them.

Is there a fee for the first lesson?

No. The first lesson is free and needs no card. After that, a monthly fee applies, shown in the fees panel.

Also on this site

Related pages

Pages that sit beside this one.

Coding classes in Australia

Where all our Australian pages start.

AI and machine learning classes

Models in more depth.

VCE Data Analytics help

For Victorian senior students.

Software development course

Testing, Git and debugging.

Coding for career changers

For adults switching fields.

AI classes for teens

Use, check and build AI.

Start here

Book a free data lesson

Leave your details and we will call when it suits you. The first class loads a real dataset and ends with a recommendation.

Read about how our lessons work, or browse all courses.

WhatsApp us · +91 91233 66161 · connect@modernagecoders.com

The quickest reply comes through WhatsApp. Calls from Australia reach our India-based staff on the +91 number; we do not run an Australian office.

Free, no card, no obligation.

Want a class sooner? Book a priority demo

A priority demo is a full class of about 45 to 60 minutes. After the class the mentor sends a written skill report and a personal learning roadmap on WhatsApp. If you enrol, the demo fee is adjusted against your first month's fee. Share your demo Order ID with us on WhatsApp and we take it off.

Book a priority demo

Keep exploring Modern Age Coders

Related courses and guides

Learn more

Free resources

From the blog

Start here

Free classPriority demoCall us