How long is the AI Product Manager 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 AI Product Manager 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 AI Product Manager 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 AI Product Manager 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 AI Product Manager Bootcamp?

6 deployed projects: The spec, The prototype, Shipped, The experiment, The strategy 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 AI Product Manager Bootcamp teach?

product management, AI literacy, prototyping, experimentation, evals and strategy. It prepares you for roles such as AI product manager, Product manager, Technical product manager and Product lead (AI).

Does the AI Product Manager 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

AI Product Manager Bootcamp

Spec, ship and measure six AI features with real engineers.

AI Product Manager 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

ClaudeChatGPTGeminiMicrosoft CopilotCursor

Not sure it is for you?Take the free AI Product Management skill check

By week 12, you will have shipped

Week 1Model ComparisonA side-by-side test of Claude, ChatGPT and Gemini on one product task, with notes
Weeks 1–2AI literacy for PMsA feature spec with eval criteria, published and reviewed by an engineer
Week 3Clickable PrototypeA clickable prototype of one AI feature, built in Cursor and ready for testing
Weeks 3–4DiscoveryA working prototype tested with five users, with findings
Weeks 5–6ShippingA feature shipped with a partner engineer, deployed
Week 7Metric PlanA metric plan for the shipped feature with a primary metric and guardrails
Weeks 7–8MeasuringAn experiment on the shipped feature with a decision memo
Week 9Opportunity MapAn opportunity map that ranks AI use cases by value and effort for one product
Weeks 9–10StrategyThe capstone: an AI product strategy and roadmap defended to a panel
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.

Product, design and engineering people who want to spec, ship and measure AI features with real engineers. No code required.

Before you start

Product, design or engineering experience; no code required.

Skills

product managementAI literacyprototypingexperimentationevalsstrategy

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 skillsWhat models can and cannot doReading an evalCost, latency and quality trade-offs
Week 1
AI literacy for PMs
- What models can and cannot do
- Reading an eval
- Cost, latency and quality trade-offs
You build: A feature spec with eval criteria
Week 2
Project 1: the spec
- Measurable success
- Engineering review
You build: A spec reviewed by an engineer
Project 1 · the gate at week 2
The spec
A feature spec with eval criteria, published and reviewed by an engineer
You hand in
- Spec
- Eval criteria
- Engineering review notes
The gate
The spec's success metric can be measured.

What you can do by week 12.

Six shipped specs, prototypes, features and memos, and the AI literacy to make the right call in a room full of engineers.

1
Explain what models can and cannot do, read an eval, and trade off cost, latency and quality.
2
Find AI-shaped problems, prototype without code and run user research on AI features.
3
Ship an AI feature with an engineering team, treating guardrails and policy as product decisions.
4
Define metrics for AI features, run experiments and read production traces.
5
Write an AI product strategy and a roadmap under uncertainty, including build, buy or fine-tune.
6
Defend a strategy and its bets to a panel.

Roles this prepares you for

AI product managerProduct managerTechnical product managerProduct lead (AI)

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, AI Product Manager BootcampExample

Week 2
The spec
The spec's success metric can be measured
Graded, gate signed
Week 4
The prototype
Findings change the spec
Graded, gate signed
Week 6
Shipped
The feature is live with its eval running
Graded, gate signed
Week 8
The experiment
The decision follows from the data
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 AI Product Manager 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 shipped specs, prototypes, features and memos
A recorded viva
Your record on /verify

A$200~~A$400~~