How long is the Data Engineering with AI 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 Engineering with AI 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 Engineering with AI 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 Engineering with AI 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 Engineering with AI Bootcamp?

6 deployed projects: Backfill, The warehouse, Contracts, The agent, checked, The platform 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 Engineering with AI Bootcamp teach?

SQL, Python, orchestration, dbt, streaming, data contracts and cloud. It prepares you for roles such as Data engineer, Analytics engineer (senior), ML platform engineer and Data platform engineer.

Does the Data Engineering with AI 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 Engineering with AI Bootcamp

Name: Data Engineering with AI Bootcamp
Price: 200.00 AUD
Availability: PreOrder

Pipelines, warehouses and quality checks, with agents doing the grunt work.

Data Engineering with AI 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

PythonPostgreSQLDockerAWSTerraform

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

By week 12, you will have shipped

Week 1CSV LoaderA Python job that loads daily CSV files into a SQL table without duplicate rows
Weeks 1–2PipelinesAn orchestrated pipeline with backfill, running on a schedule
Week 3Star SchemaA star schema with one fact table and three dimensions, built from raw tables
Weeks 3–4WarehousesA modelled warehouse with tested transformations, deployed
Weeks 5–6QualityA data-quality layer with contracts and alerts, deployed
Week 7Schema Doc AgentAn agent that writes column descriptions for one warehouse schema, checked by hand
Weeks 7–8Agents for data workAn agent that documents and reviews a warehouse, with its mistakes logged
Week 9Feature TableA scheduled job that builds a feature table for an ML model from warehouse data
Weeks 9–10PlatformThe capstone: a data platform serving an ML feature and a RAG index, monitored
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.

Engineers with SQL and Python and some backend or analytics experience who want to build the pipelines, warehouses and quality layers that AI systems eat from.

Before you start

SQL and Python; some backend or analytics experience.

Skills

SQLPythonorchestrationdbtstreamingdata contractscloud

A week, about 15 hours

Live on Zoom: 4h
Set reading 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 twelve-week plan
Every week has its theme, its topics and what you build, published before you apply and taught live by your instructor.
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 skillsBatch and streaming, when eachOrchestrationIdempotency and backfills
Week 1
Pipelines
- Batch and streaming, when each
- Orchestration
- Idempotency and backfills
You build: An orchestrated pipeline
Week 2
Project 1: backfill
- Scheduling
- Identical reruns
You build: A pipeline with backfill, running on a schedule
Project 1 · the gate at week 2
Backfill
An orchestrated pipeline with backfill, running on a schedule
You hand in
- Pipeline
- Orchestration
- Backfill
- Schedule
The gate
A backfill produces identical output to the original run.

What you can do by week 12.

Six deployed pipelines and platform pieces, with the contracts and lineage that make a data platform something an AI team can build on.

1
Build orchestrated batch and streaming pipelines with idempotency and backfills.
2
Model a warehouse for analytics with tested, documented transformations.
3
Build a data-quality layer with contracts, anomaly detection, lineage and alerts.
4
Use agents for SQL, migrations and documentation, and check their work before it lands.
5
Run a data platform that serves an ML feature and a retrieval index.
6
Defend a platform and its lineage.

Roles this prepares you for

Data engineerAnalytics engineer (senior)ML platform engineerData platform engineer

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 Engineering with AI BootcampExample

Week 2
Backfill
A backfill produces identical output to the original run
Graded, gate signed
Week 4
The warehouse
Every model has a test and documentation
Graded, gate signed
Week 6
Contracts
A contract violation blocks downstream runs
Graded, gate signed
Week 8
The agent, checked
Agent output is checked before it lands
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 Engineering with AI 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 deployed pipelines and platform pieces
A recorded viva
Your record on /verify

A$200~~A$400~~