UK · Sixth formers and adults · Python

Data science course in the UK

Every student taking A level maths in England already works with real data. The Department for Education's subject content requires specifications to make students "become familiar with one or more specific large data set(s) in advance of the final assessment", data that "must be real and sufficiently rich", explored with "spreadsheets or specialist statistical packages". Ofqual adds that the data "should not be cleansed by the awarding organisation": missing values and awkward units stay in. Then comes the exam, where, in OCR's words, "Students will not have access to the data set in the exam", and the analysis is done with a calculator's statistical functions. Code is nowhere in that picture. Yet the thing students are practising, turning a messy real table into a defensible conclusion, is exactly what data scientists do in Python every day. This course fills that gap for UK sixth formers who want to go further than the exam asks, and for adults who want data skills for work: loading real data, cleaning it honestly, summarising and charting it, and building first models.

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Live teaching since 2020 · 10,000+ students · real data, cleaned honestly, analysed in code

In short

The DfE subject content for AS and A level mathematics in England requires every specification to make students familiar with one or more real large data sets before the final assessment, explored using technology such as spreadsheets or statistical packages. Ofqual's guidance says the data should be real, not cleansed by the exam board, and include a mix of categorical and numerical data, and that exam questions should give a material advantage to students who know it. Students do not have the data set in the exam and analyse subsets with a calculator. Modern Age Coders teaches data science live and online to UK teenagers aged 14 to 18 and adults: Python and pandas, cleaning and joining real data, summary statistics, charts, sampling, correlation and first machine learning models. Sixth formers can explore their own board's large data set in code as a teaching resource; we never work on anything submitted for assessment. The first class is free; afterwards a group place is USD 100 a month and one-to-one lessons USD 150 a month.

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Three courses for working with data

Data science for teenagers, data science for adults, and A level maths with its statistics. Each card opens the full syllabus.

Data Science for Teens course thumbnail

DSU / 01

Data Science for Teens

Python, pandas, charts and first machine learning models, for ages 14 to 18 with basic Python.

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Data Science Course course thumbnail

DSU / 02

Data Science for Adults

Python, SQL, machine learning and deep learning, for university students, graduates and professionals.

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A-Level Maths course thumbnail

DSU / 03

A Level Maths

Pure, mechanics and statistics, including work with the large data set.

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The large data set

Every A level maths student in England is handed real data

From the DfE's subject content for AS and A level mathematics and Ofqual's guidance on it. The requirement covers A levels in England.

What the specifications must require, as the DfE subject content puts it
RequirementWording
Know a data set in advance"become familiar with one or more specific large data set(s) in advance of the final assessment"
Explore it with technology"use technology such as spreadsheets or specialist statistical packages to explore the data set(s)"
Read real summaries"interpret real data presented in summary or graphical form"
Ask real questions"use data to investigate questions arising in real contexts"
Technology throughoutGraphing tools and spreadsheets "must permeate the study of AS and A level mathematics"
How each board handles it, from its own pages
BoardLarge data set arrangement
AQA (7357)A Family Food extract for 2018 and 2019 exams; "For exams from 2020 there is a new dataset", available on AQA's site
Pearson EdexcelA large data set that supports the assessment of Statistics in Paper 3: Statistics and Mechanics
OCR Mathematics AOne pre-release data set, used for the life of the specification
OCR Mathematics B (MEI)Three large data sets, each updated or replaced on a three-year cycle, with one assessed

Real, and deliberately messy

Ofqual's guidance says the data sets "consist of real data", and that "the data may be reorganised into a standard format but should not be cleansed by the awarding organisation". They should include the source where possible, a mix of categorical and numerical data, and be "suitable for analysis using a spreadsheet and/or statistical data package".

Uncleaned real data is the everyday material of data science. A level students meet it at 16.

Knowing it pays in the exam

Ofqual expects questions on the data set to "give a material advantage" to students who have studied it. OCR notes that exam questions set in its context often come with several graphs and more reading than traditional statistics questions.

OCR also says students "should work with real data from many different sources", not only the pre-release set.

Sources, read 21 September 2026: DfE, AS and A level mathematics subject content; Ofqual, GCE Subject Level Guidance for Mathematics; AQA 7357, Use of data in statistics; Pearson Edexcel A level Mathematics specification; OCR support articles on the large data set for Mathematics A and Mathematics B (MEI).

The missing middle

A spreadsheet in class, a calculator in the exam, and no code at all

The requirement stops at spreadsheets and statistical packages, and the exam at a calculator. Nothing asks a student to write a line of code, which is why so few do.

OCR describes the practical side candidly: "The LDS is published as an Excel file to make it easy to extract data for tables and charts", and "Scheduling whole class lessons in computer suites is still an issue for some teachers." In the exam itself, students have no data set and analyse any subset with "a calculator with standard statistical functions", as the DfE content puts it.

Three ways to work with the same data
Spreadsheet in classCalculator in the examPython in our course
Size it handles comfortablyThousands of rowsA small subset typed inMillions of rows
CleaningBy hand, cell by cellNot possibleWritten once, rerun on every update
RepeatableHard to audit what was clickedOnly on paperEvery step recorded in code
ChartsBuilt-in chart typesNoneAny chart, reproducible
Next stepMore formulasThe exam answerJoining data, sampling, models

Why the exam does not need code

The exam is testing statistical reasoning: what a summary means, whether a sample is fair, whether a correlation says anything. Code would add a skill the qualification does not examine.

That is a fair design choice, and it leaves room for a course that adds the skill deliberately.

Why a student might want it anyway

Running the same analysis in Python forces every assumption into the open. A student who has cleaned the data in code knows exactly which rows were dropped and why, which is the reasoning the exam rewards.

We explore a student's own board data set as a teaching resource; we never touch anything submitted for assessment.

From exam to code

The A level statistics skills, and what they become in Python

Each topic in the statistics section has a direct counterpart in data science. Learning them side by side makes both stronger.

A level statistics topics and their data science equivalents
A level topicIn PythonWhy it matters beyond the exam
Sampling methodsRandom and stratified samples drawn in codeEvery survey, experiment and model starts with a sample
Summary statisticsMeans, medians, quartiles and spreads computed per groupThe first look at any new data set
Outliers and cleaningRules for missing values and outliers, written down and appliedDecisions others can check and challenge
Charts and interpretationHistograms, box plots and scatter plots from the dataShowing a result honestly
Correlation and regressionCorrelation coefficients and a fitted lineThe simplest predictive model
Hypothesis testingTests run on real samples, with the assumptions statedTelling a real effect from noise

Weather and climate

Public weather records make a good first project: missing readings, units to convert, and seasons to compare.

Transport and travel

Public travel and vehicle statistics raise real questions about sampling, grouping and fair comparison.

Your own question

The strongest projects start from something the student actually wants to know, with public data to test it.

Public data sets from UK government sources are free to use for projects. Students keep their notebooks and code in their own repository, and every chart they publish says where its data came from, the same habit Ofqual asks boards to follow by including sources.

Beyond A level

Data science for adults, and for students not taking A level maths

Nobody needs A level maths to start. The course meets learners where they are.

Routes into data science
You areA sensible route
A sixth former taking A level mathsPython basics, then Data Science for Teens alongside the statistics course
A teenager who codes but does not take mathsData Science for Teens, with the statistics taught as needed
An adult who lives in spreadsheetsData Analysis: Excel, SQL, then Python
An adult aiming at data rolesData Science for Adults, from Python to machine learning
Someone who wants models without code firstThe Orange visual machine learning course, then Python

Data and AI

Modern AI is built on data, and understanding how data is sampled, cleaned and labelled is the strongest defence against trusting a model too much.

Our pages on training AI, not just prompting it and building real AI projects take this further.

Maths support alongside

Students who find the statistics hard can study A level maths with us as well, with the large data set covered as part of the course.

For university students using data in any subject, coding for university students maps useful coding by degree.

Stages

Four stages in data science

Start at the stage your current skills put you in.

From loading a file to a first model
StageWhat should be true
1. Load and lookYou load a real data file in Python and describe what it contains
2. Clean and summariseYou handle missing values and outliers by stated rules and compute group summaries
3. Chart and questionYou chart the data honestly and test a question with a sample
4. Model and explainYou fit a first model, measure how well it does and explain its limits

Stage two is where honesty lives

Every cleaning decision changes the answer, so each one is written down.

The wider sequence of subjects is on the coding roadmap.

Stage four needs stage two

A model trained on carelessly cleaned data is confidently wrong.

Measuring a model means admitting where it fails.

The catalogue

Nine courses for data work

Data science itself, the maths and tools under it, and where it leads.

I

Data science

By age

DSU / DS / 01

Data Science for Teens

Python, pandas and first models, ages 14 to 18.

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DSU / DS / 02

Data Science for Adults

Python, SQL, machine learning and deep learning.

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DSU / DS / 03

Data Analysis

Excel, SQL, Python and dashboards for work.

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II

Foundations

Maths and code

DSU / FN / 01

A Level Maths

Statistics and the large data set, with pure and mechanics.

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DSU / FN / 02

Python for Teens

The language data science is written in.

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III

Where data leads

Models and AI

DSU / AI / 01

AI and Machine Learning for Teens

Python to real models.

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DSU / AI / 02

Orange Visual Machine Learning

Models without code, for ages 13 to 18.

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DSU / AI / 03

Data and AI for Non-Programmers

Answers from data for adults who do not code.

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How lessons run

Live lessons with real data

Lessons are taught from India, where there is no clock change, so the UK sits four and a half hours behind in British Summer Time and five and a half hours behind in winter. That leaves after-school, evening and weekend slots in UK time.

After sixth form

Early evening on weekdays.

Evening

For adults fitting learning around work.

Weekend

Longer sessions for a data project.

A free first class

We look at your maths and coding, and pick a route and a first data set.

Small groups

Five to ten learners at the same level.

One to one

For a faster pace or a particular project.

Notebooks you keep

Every analysis is saved in your own repository.

Sources on every chart

Students record where each data set came from.

Nothing assessed

We never work on anything you submit to a school, college or university.

Student work

Projects our students have built

Four finished projects from our students. The full collection, across ages and subjects, is in 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 data science

Charged monthly in US dollars, at one rate for learners anywhere outside India. There is no joining fee, and you can stop when any month ends. The software we use is free.

Free first class

USD 0

no card required

  • A look at your maths and coding
  • A route and a first data set
  • No payment details needed
Book it

Group batch

USD 100

a month, billed in US dollars

  • Five to ten learners at one level
  • The same teacher each week
  • Real data in every lesson
  • Stop at the end of any month
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One to one

USD 150

a month, billed in US dollars

  • A teacher for you alone
  • Built around your own data question
  • Paced to suit you
Enquire

What families say

Rated 4.9 across 547 Google reviews

What our students and their families wrote on Google, unchanged.

★★★★★

"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

Questions about data science

What UK learners ask about data science

What is the large data set in A level maths?

A real data set each exam board provides in advance, which the DfE requires students to explore using technology. Exam questions are set in its context, but students do not have the data set in the exam.

Is the large data set cleaned?

No. Ofqual's guidance says it may be reorganised into a standard format but should not be cleansed by the exam board, so missing values and quirks remain.

Does A level maths teach coding?

No. The requirement is for technology such as spreadsheets or statistical packages, and the exam uses a calculator. Coding is an extra skill that our course adds.

Can you help my child with the large data set?

Yes, as a teaching resource: we can explore it in Python and discuss what it shows. We never work on anything submitted for assessment.

Do I need A level maths for data science?

No. Teenagers can start with basic Python, and adults can begin with our data analysis course. Statistics is taught as it is needed.

Which language do you use?

Python, with pandas for data and plotting libraries for charts, plus SQL for querying databases in the adult courses.

What age is the teen course for?

Data Science for Teens is for ages 14 to 18 and expects basic Python. Younger or newer coders start with Python for Teens.

Can I learn data science as an adult with no coding?

Yes. Our data analysis course starts with Excel and SQL before Python, and a non-programmers course covers data and AI without code.

What does it cost?

The first class is free. After that it is USD 100 a month in a group or USD 150 a month one to one, with no enrolment fee.

When can I have lessons?

Weekday evenings or weekends in UK time, fixed in the free class. Our teachers are four and a half hours ahead of the UK in summer and five and a half in winter.

Elsewhere on this site

Related pages

Maths, AI and the coding around data.

Learn to train AI, not just prompt it

Where data meets models.

Build real AI projects

Projects that use what data science teaches.

Python classes online

The language underneath.

Coding for university students

Data skills for any degree.

Coding classes for teens

How we teach teenagers.

Coding classes in the UK

All our UK pages.

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Bring a data question to a free class

Leave a number and we will call at a UK time that suits you. Tell us your maths and coding level and a question you would like data to answer; the class starts there.

Would you like to read first? See the full course list, how lessons are taught, and work students have finished.

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

WhatsApp from a UK phone is often quickest. Our team is in India, so the number begins +91, and we have no UK office.

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