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AI Foundations Data Science
16 weeks · the deepest course we run

The long road, walked properly.

Sixteen weeks from no maths and no code to a trained model you can explain and defend. It is the longest course in Foundations because this is the one that genuinely cannot be rushed.

Join the waitlist See all sixteen weeks
16 weeksFour phases of four
No mathsEntry requirement
1 modelTrained and defended
Longest course
16 wks
zero to a model you built
You finish with
1 model
and its honest limits
Taught live, never recorded
Week 1 starts at what a number is
01The question everyone asks

"Do I need to be good at maths?"

No, and we would rather answer it here than have you talk yourself out of the course. Here is exactly what is and is not expected of you.

Learners working through a problem together
Needed
Comfort with a spreadsheet

If you can build a formula that adds a column and works out an average, you have enough to start week one.

Needed
Willingness to be wrong in public

Sixteen weeks of getting things wrong in a small room with someone who explains why is the actual method.

Not needed
A maths or statistics degree

We teach the statistics you need, when you need it, in the context of a problem rather than as a syllabus.

Not needed
Any programming at all

Week five is where code starts, and it starts at the beginning. Nobody is expected to arrive knowing Python.

02Sixteen weeks

Four phases, four weeks each.

Each phase ends with something finished before the next one starts, so you always know whether the last four weeks actually landed.

Reading data honestlyWeeks 1 to 4

Before any modelling, the ability to look at a table and know what it is and is not telling you. Most bad data science is a reading failure, not a maths failure.

Week 01What a dataset actually is
Week 02Distributions without the formulas
Week 03Correlation, cause and traps
Week 04Telling the story truthfully
Making the machine workWeeks 5 to 8

Python from the first line, taught as a tool for handling data rather than as computer science. By week eight you can load, clean and reshape a real dataset on your own.

Week 05Python from nothing
Week 06Tables in code, not in Excel
Week 07Cleaning the mess
Week 08Charts that argue a point
Models that predictWeeks 9 to 12

The first real models, and more importantly the discipline around them: splitting data properly, measuring honestly, and noticing when a result is too good to be true.

Week 09Your first prediction
Week 10Measuring whether it works
Week 11Overfitting and how it lies
Week 12Choosing between models
A project you defendWeeks 13 to 16

One problem, taken from a raw dataset to a trained model and a written argument, then presented to people who will push back on it.

Week 13Choosing a real problem
Week 14Building the thing
Week 15Writing the argument
Week 16Defending it out loud
03Where you get to

Sixteen weeks, measured honestly.

Nobody becomes a senior data scientist in four months and we are not going to pretend otherwise. This is where the course genuinely takes you.

Week 4

Reads data honestly

You can look at a table and say what it supports, what it does not, and what is missing.

Week 8

Handles it in code

Loading, cleaning and reshaping real data in Python without needing a template to copy.

Week 12

Builds and checks models

Training a model is the easy half. You will know how to tell whether the result means anything.

Week 16

Defends a piece of work

A finished project, the reasoning written down, and the ability to hold it up under questioning.

Python pandas NumPy scikit-learn Jupyter Claude Cursor Google Colab

All of it runs in the browser, so nothing depends on the machine you own.

04Who it is for

Sixteen weeks is a real commitment.

It is the right course for a smaller group of people than the shorter ones, and we would rather you knew that before you start than after week six.

This is you

Data Science fits

  • You are changing career and want the depth, not a taster.
  • You can protect six to eight hours a week for four months.
  • You want to understand why a model works, not just run one.
  • You have tried to self-teach this and stalled somewhere around statistics.
This is not you

Start somewhere shorter

  • You want something working in weeks. AI Automation is six.
  • You mainly want to read and present data rather than model it. That is Data Analytics.
  • Four months is more than you can commit to right now. It will run again.
05Cohorts

When the next one runs.

Sixteen weeks means fewer intakes a year and a small room each time. Dates below come straight from our scheduling system.

06FAQ

Questions people
actually ask

Still unsure? Message us on WhatsApp and a human will answer.

Waitlist

Fewer intakes, smaller rooms.

A sixteen week course runs less often than a six week one, so the list matters more here. When the next Data Science intake opens, it hears first.

Dates, timetable and pricing sent before they go public.
First refusal on seats in the next cohort.
No commitment, and nothing to pay to hold your place.

We only use this to tell you when Data Science opens. No newsletter, and you can ask us to remove you at any time.

You are on the list.

We will email you the dates, the timetable and the pricing for the next Data Science cohort before any of it goes on the site.

07The rest of Foundations

Not sure this is the one?

The other Foundations courses run from six to sixteen weeks and start from exactly the same place: nothing assumed.