How long is the Data Science Bootcamp?

12 weeks at about 15 hours a week. The weeks run as six two-week blocks; each block ends in a project you deploy and a gate you must pass before the next block opens.

Is the Data Science Bootcamp live or self-paced?

Live. It is taught on Zoom by one instructor, with a 30-minute one-to-one every week. Nova, Square 1's AI tutor, grades every exercise and project between sessions against a rubric you can read.

When are the live sessions for the Data Science Bootcamp?

Live sessions run on weekday evenings from 5:30 PM Sri Lanka and India time, with full-day sessions at weekends. That is 5:00 PM in Pakistan, 5:45 PM in Nepal and 6:00 PM in Bangladesh, so the sessions fit around a working day.

How much does the Data Science Bootcamp cost?

A$200 for the founding cohort, paid once; the standard price is A$400. It is the same price in every country. Founding students keep their founding price on any second programme.

What will I build in the Data Science Bootcamp?

6 deployed projects: A finding, The experiment, The model, The dashboard, Automated reporting and Employer brief. Each is graded against a published rubric and kept on a record an employer can open at /verify.

What skills does the Data Science Bootcamp teach?

SQL, Python, pandas, statistics, A/B testing, dashboards and communication. It prepares you for roles such as Data analyst, Data scientist, Analytics engineer (junior) and Business intelligence analyst.

Does the Data Science Bootcamp guarantee a job?

No. No placement rate is published because the first cohorts have not graduated. What you leave with is six deployed projects, a recorded defence of your code and a hiring plan worked through with your instructor, including a two-week hiring sprint at the end.

Live bootcampTaught live on Zoom, one instructor

Data Science Bootcamp

Name: Data Science Bootcamp
Price: 200.00 AUD
Availability: PreOrder

From messy data to a decision a business acts on, six times.

Data Science Bootcamp is a 12-week live online bootcamp, taught on Zoom by one instructor at about 15 hours a week, with 6 deployed projects and a one-to-one every week. The founding price is A$200, down from A$400. Live sessions run on weekday evenings from 5:30 PM Sri Lanka and India time, with full-day sessions at weekends.

Taught with

PythonpandasNumPyPostgreSQLJupyter

Not sure it is for you?Take the free Data Science skill check

By week 12, you will have shipped

Week 1Data Quality CheckA pandas script that profiles a dataset for missing values, duplicates and outliers
Weeks 1–2Data inAn analysis of a real dataset with a published notebook and a one-page finding
Week 3Hypothesis TestA notebook that runs one hypothesis test on real data and states the result plainly
Weeks 3–4Statistics that matterAn experiment analysed end to end, with a decision memo
Weeks 5–6ModellingA predictive model with a validation report, deployed as an API
Week 7Chart SetA set of three charts that answer one business question, each with a written caption
Weeks 7–8StorytellingA live dashboard for a stakeholder, deployed, with a recorded walkthrough
Week 9AI Summary StepA script that turns a weekly data table into a written summary with an LLM
Weeks 9–10AI in the loopThe capstone: an automated analysis and reporting pipeline with an AI step, deployed
Weeks 11–12Employer brief and hiring sprintThe employer brief shipped, and demo day

weeks, live on Zoom: 12
hours a week: 15
projects to build: 10
minutes 1-1, every week: 30

Who it is for, and what you receive.

Analysts, graduates and career-changers comfortable with spreadsheets who want to turn messy data into decisions a business acts on. Python is taught from block one.

Before you start

Comfortable with spreadsheets; Python is taught from block one.

Skills

SQLPythonpandasstatisticsA/B testingdashboardscommunication

A week, about 15 hours

Live on Zoom: 4h
Recorded lessons and exercises: 6h
The project: 5h

1
Six deployed projects
Each graded by Nova against a published rubric and signed off by the instructor at the gate.
2
The recorded lessons
The track's lessons and exercises, graded line by line, open for twelve months after the cohort ends.
3
Live on Zoom every week
A 90-minute live code review, a 60-minute squad lab, 60 minutes of office hours, and a 30-minute 1-1 with your instructor.
4
Your hiring plan
Opened in week 1 and reviewed in every 1-1: target roles, the gap map, the proof list, weekly actions, an interview log, the outcome.
5
The record
Every grade and every project with its repository at square1ai.com/u/{handle}, and the recording of your viva, verifiable by any employer.
6
The certificate
A credential ID that resolves at square1ai.com/verify to the real completion.
7
The hiring sprint
Weeks 11 and 12: CV and portfolio from graded work, applications, mock interviews scored against the role, demo day.
8
Nova for twelve weeks
A tutor with every submission of yours in its memory, at 2am as well as in class.

Twelve weeks in six parts.

Each part teaches for a week, then you build and deploy a project, then a gate checks it before the next part opens. The project and its gate are the part's entry on your record.

Live time each week on Zoom: a 90-minute class where the instructor reviews real submissions, a 60-minute squad lab, 60 minutes of office hours, and your own 30-minute 1-1. Nothing is lectured live; the recorded lessons do that.

Key skillsSQL for analysisPandas and cleaningExploratory analysis that finds things
Week 1
Data in
- SQL for analysis
- Python and pandas from zero
- Cleaning
- Exploratory analysis that finds things
You build: First analysis notebook
Week 2
Project 1: a finding
- Reproducible notebooks
- Stating caveats
You build: An analysis with a published one-page finding
Project 1 · the gate at week 2
A finding
An analysis of a real dataset with a published notebook and a one-page finding
You hand in
- Notebook
- One-page finding
- Caveats
The gate
The finding is reproducible and its caveats are stated.

What you can do by week 12.

Six published analyses, models and dashboards, decision memos a manager would act on, and the Python and SQL to do it again anywhere.

1
Query, clean and explore real data in SQL and pandas and write a finding a stakeholder can act on.
2
Analyse an experiment with the right statistics and write a decision memo.
3
Build and validate a predictive model and report its performance honestly.
4
Build a dashboard a stakeholder uses without you, and present to a decision maker.
5
Use LLMs for analysis and code and check what they tell you.
6
Defend an analysis and say where the AI could mislead.

Roles this prepares you for

Data analystData scientistAnalytics engineer (junior)Business intelligence analyst

No placement rate is shown, because there are no graduates to count yet. The roles above are what the projects are built for.

Your record at week 12.

Every exercise and project is graded by Nova against a rubric you can read, and every grade is kept on one page an employer can open and run. This is what the programme writes to it.

Graded, line by line: Nova reads every submission against the brief and the rubric and returns a score, what you did well and what to fix.
Six gates: A block does not open until the previous project passes its gate. You always know where you are and what is next.
A weekly 1-1: Thirty minutes with your instructor, who has already read your code before the call.
One page an employer can run: Every grade, project and the viva recording at /verify. An employer opens it, runs the code and watches you defend it.

Record, Data Science BootcampExample

Week 2
A finding
The finding is reproducible and its caveats are stated
Graded, gate signed
Week 4
The experiment
The memo's recommendation follows from the numbers
Graded, gate signed
Week 6
The model
Held-out performance is reported honestly
Graded, gate signed
Week 8
The dashboard
The stakeholder can answer their question without you
Graded, gate signed

The entries, not the grades: those are yours to earn. The page lives at /verify and an employer needs no account to open it.

8 entries, twelve weeks. Reserving a spot holds the founding price.

Reserve a seat

How we help you find a job.

The last block is not curriculum. It is the hiring sprint, and the proof you built in the ten weeks before it.

The course booklet

The whole plan on a few pages: the parts, the projects, the gates and the price. We email it to you.

Get the booklet

1
Your hiring plan, from week 1
Six parts you and your instructor keep: target roles, the gap map from real postings, the proof to send, weekly actions, an interview log, the outcome. Read before every 1-1.
2
The hiring sprint
Weeks 11 and 12: CV, portfolio, applications, mock interviews, and demo day in front of hiring partners.
3
A record an employer can run
Your deployed projects and the recorded viva on /verify. An employer opens it, runs the code and watches you defend it.
4
The career agent
Paste a real job posting at /career and it maps the role to your graded work and what to do next.
5
The roles directory
Every role we prepare people for, what it pays and what it asks, at /roles.

Questions people ask.

About Data Science Bootcamp, answered from the plan on this page.

One cohort, one instructor. Hold your spot.

A cohort of 25, one instructor, 12 weeks, six things you ship. Spot holders hear the start date first, and nothing is charged before you confirm.

Six published analyses, models and dashboards
Decision memos a manager would act on
A recorded viva
Your record on /verify

A$200~~A$400~~