How long is the Computer Vision 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 Computer Vision 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 Computer Vision 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 Computer Vision 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 Computer Vision Bootcamp?

6 deployed projects: Dataset and baseline, The classifier, Video, Grounding, Real time 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 Computer Vision Bootcamp teach?

Python, OpenCV, PyTorch, detection, segmentation, multimodal models and edge inference. It prepares you for roles such as Computer vision engineer, ML engineer (vision), Perception engineer and Applied scientist (vision).

Does the Computer Vision 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

Computer Vision Bootcamp

Name: Computer Vision Bootcamp
Price: 200.00 AUD
Availability: PreOrder

From pixels to a deployed vision pipeline you can explain line by line.

Computer Vision 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

PythonPyTorchHugging FaceJupyterDocker

Not sure it is for you?Take the free Computer Vision skill check

By week 12, you will have shipped

Week 1Image AugmenterA Python script that applies flips, crops and colour shifts to a small image set
Weeks 1–2Images as dataA labelled dataset and a classical baseline, published
Week 3Transfer Learning RunA pretrained network fine-tuned on a small image set in a Jupyter notebook
Weeks 3–4Convolutional networksAn image classifier trained and deployed as an API
Weeks 5–6Detection and segmentationA detector running on video, deployed
Week 7Image CaptionerA script that captions a folder of images with a Hugging Face vision-language model
Weeks 7–8Vision-languageA vision-language application over real images, deployed
Week 9Frame Rate BenchmarkA benchmark that measures frames per second for your model on CPU and GPU
Weeks 9–10ProductionThe capstone: a real-time vision pipeline with monitoring
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 Python and the ML toolkit who want to build vision systems that run on real images and video, not just a notebook.

Before you start

Python and the ML toolkit (or the ML Engineer Bootcamp first).

Skills

PythonOpenCVPyTorchdetectionsegmentationmultimodal modelsedge inference

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 skillsImage processing fundamentalsDatasets, labelling and augmentationClassical vision that still works
Week 1
Images as data
- Image processing fundamentals
- Datasets, labelling, augmentation
- Classical vision that still works
You build: A labelled dataset and a classical baseline
Week 2
Project 1: dataset and baseline
- Labelling tools
- Reproducibility
You build: Dataset and baseline, published
Project 1 · the gate at week 2
Dataset and baseline
A labelled dataset and a classical baseline, published
You hand in
- Labelled dataset
- Augmentation
- Baseline
- Report
The gate
The baseline is reproducible.

What you can do by week 12.

Six deployed vision models and pipelines, from a labelled dataset to real-time inference, with the failure analyses that show you know where each one breaks.

1
Build a labelled dataset with augmentation and a classical baseline.
2
Train and evaluate CNN classifiers with transfer learning and per-class metrics.
3
Build object detection, segmentation and tracking on video and analyse failures.
4
Build vision-language applications and measure grounding.
5
Run real-time and edge inference with drift monitoring and privacy controls.
6
Defend a vision pipeline frame by frame.

Roles this prepares you for

Computer vision engineerML engineer (vision)Perception engineerApplied scientist (vision)

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, Computer Vision BootcampExample

Week 2
Dataset and baseline
The baseline is reproducible
Graded, gate signed
Week 4
The classifier
Per-class metrics reported on a held-out set
Graded, gate signed
Week 6
Video
mAP reported and a failure analysis written
Graded, gate signed
Week 8
Grounding
Grounding accuracy measured
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 Computer Vision 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 vision models and pipelines
A recorded viva
Your record on /verify

A$200~~A$400~~