for people breaking in

Build something real. Then be able to explain it.

Tutorials leave you with a copy of someone else’s notebook. We give you a project with an actual dataset, an actual deadline and someone reviewing your code. So what you put on your CV is yours, and you can defend it in the room.

Join a track Help with an interview dataset

Three tracks

Each runs on a real, messy dataset, not the clean teaching version. You finish with a repository, a deployed link and a README you wrote.

Machine learning

Framing the problem, splitting data honestly, feature work, training, and the part most courses skip: proving your model beats the obvious baseline, then getting it behind an API that someone else can call.

Data analysis

From a raw export to a defensible answer. Cleaning, joining, spotting the thing that’s quietly wrong in the data, and building the chart that makes a decision-maker act.

Web development

Python on the back, a real interface on the front. Auth, a database, a deploy pipeline, and a URL you can send to a hiring manager.

The interview take-home

You’ve been sent a dataset and a deadline. This one needs saying plainly, so here it is.

What we do

Sit with you while you work it. We’ll help you read the brief properly, choose an approach and understand why, unblock you when something breaks, review your code, and rehearse the follow-up questions until you can answer them cold. You’ll leave understanding the analysis well enough to have done it alone.

What we don’t

Write it for you or hand you a finished submission. That gets found out in the technical round, and it costs you the offer and the reference. If that’s what you’re after, we’re the wrong people. And we’ll say so on the first call rather than take your money.

Booked by the hour, usually one or two sessions. Bring the brief, the data and whatever you’ve already tried.

If you’re switching into tech

Most people we work with aren’t computer science graduates. They’re in operations, finance, teaching or retail, and they can already see where the work is going.

Start from zeroPython from the beginning, aimed at doing something useful in week one rather than finishing a syllabus.

Office hoursA standing slot to bring whatever is blocking you. An error, a concept, a job spec you don’t understand.

Code reviewSomeone reads what you wrote and tells you what a senior engineer would flag, which is how you actually improve.

Portfolio & CVGetting your projects presentable: a README that explains the decisions, and a CV that describes the work in the language of the job ad.

Mock interviewsTechnical and behavioral, recorded, with the specific things to fix written down afterwards.

What’s worth learningAn honest read on which tools matter for the roles you’re applying to and which are noise this year.

Google Sheets and Apps ScriptUnderrated, and on more job descriptions than people expect. If you can automate a report and build a dashboard inside a Workspace an employer already owns, you are useful in week one.

What you leave with

A repository

Under your own account, with commit history that shows how you got there. The thing a technical interviewer can actually look through.

A live link

Deployed and working. A dashboard, an API or a site, something a stranger can open without installing anything.

A written explanation

What the problem was, what you tried, what you rejected and why. The document that makes the difference between a project and a portfolio.

The ability to talk about it

The point of all of it. If you can’t walk someone through your own decisions, the project isn’t finished.

Where are you stuck?

Tell us what you’re trying to get into and what you’ve already tried. We’ll tell you what to do next, whether or not you work with us.

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