How long is AI for Cybersecurity?

8.5 hours of recorded sessions across 5 modules, taken at your own pace. 4 of the modules end in work Nova grades.

Is AI for Cybersecurity live or self-paced?

Self-paced. The sessions are recorded by an instructor who does this work, and Nova, Square 1's AI tutor, grades every checkpoint and project against a rubric you can read.

How much does AI for Cybersecurity cost?

A$45 for the founding intake, paid once; the standard price is A$90. It is the same price in every country. Founding students keep their founding price on any second programme.

What will I build in AI for Cybersecurity?

3 deployed projects: A log anomaly detector, A phishing classifier and An AI-assisted SOC workflow. Each is graded against a published rubric and kept on a record an employer can open at /verify.

What skills does AI for Cybersecurity teach?

anomaly detection, classification, LLM security and SOC. It prepares you for roles such as SOC analyst and Security engineer (AI).

Does AI for Cybersecurity guarantee a job?

No. No placement rate is published because there are no graduates to count yet. What you leave with is graded, deployed work on one record an employer can open and run, and a hiring plan you keep with the career agent.

On demandRecorded by an instructor, graded by Nova

AI for Cybersecurity

Name: AI for Cybersecurity
Price: 45.00 AUD
Availability: PreOrder

Anomaly detection, phishing, prompt injection and model abuse, for defenders.

AI for Cybersecurity is a self-paced online course: 8.5 hours of recorded sessions across 5 modules, with 4 graded by Nova, Square 1's AI tutor. The founding price is A$45, down from A$90. Start any time and keep your own pace.

Taught with

PythonClaudeChatGPTDocker

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

Module by module

Module 1AI in the security stack60 min
Module 2Anomaly detection on logs120 min · graded
Module 3Phishing and fraud detection90 min · graded
Module 4Attacking and defending LLM apps120 min · graded
Module 5Project: an AI-assisted SOC workflow120 min · graded

recorded hours: 8.5
modules, in order: 5
deployed projects: 3
graded checkpoints: 4

Who it is for, and what you receive.

Security people or Python developers who want AI tools they can defend a network with.

Before you start

Some security or Python background.

Skills

anomaly detectionclassificationLLM securitySOC

1
The recorded sessions
Taught by an instructor, taken in order at your own pace, yours for twelve months.
2
Graded work after every module
Exercises and projects marked by Nova against a rubric you can read, with what you did well and what to fix.
3
The projects
Deployed and graded, each one on your record with its repository.
4
Your hiring plan
The same six-part plan the bootcamps use, run with the career agent.
5
The record and the certificate
Every grade at square1ai.com/u/{handle}; a credential ID that resolves at square1ai.com/verify.
6
Nova as your tutor
Help that is about your actual work, because it has read all of it.

The content plan, module by module.

8.5 recorded hours from an instructor, taken in order at your own pace. Nova grades the work at the end of each module.

Where AI helps
Where it does not
Vendor claims

The projects.

Each is deployed and graded by Nova against a rubric you can read before you start.

Project 1
A log anomaly detector
Using a public web-server or authentication log dataset with seeded attacks, engineer features from the raw logs and build an anomaly detector. The hard part is alert fatigue: you must find the seeded anomalies without burying an analyst in false positives.
You hand in
- Detector repository
- Feature notes
- False-positive analysis
The rubric requires
Seeded anomalies are found at the stated false-positive rate.
Project 2
A phishing classifier
Train a classifier on a public phishing email dataset and evaluate it on messages from a later period than your training data, so you can see drift. Report where it fails and what a missed phish costs compared with a false alarm.
You hand in
- Classifier repository
- Eval report
- Drift check
The rubric requires
Precision and recall are reported on the evaluation set.
Project 3
An AI-assisted SOC workflow
Build a workflow for a fictional small security team that takes incoming alerts, enriches them with context and uses a model to suggest a triage decision. Deploy it, and make every suggestion show the log lines and lookups it relied on.
You hand in
- Workflow repository
- Deployed workflow
- Sample triaged alerts with evidence
- Short write-up
The rubric requires
Every AI suggestion carries its evidence.

What you can do at the end.

AI tools you can defend a network with, and three graded projects on your record.

1
Place AI in the security stack honestly.
2
Build anomaly detection on logs.
3
Build phishing and fraud classifiers with evals.
4
Attack and defend an LLM application.
5
Build an AI-assisted SOC workflow.

Roles this prepares you for

SOC analystSecurity engineer (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 the end.

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.
Module by module: Each module ends in graded work; the next opens when you are ready, on your own schedule.
Nova remembers: Help is about your actual work, because the tutor has every submission and every failed exercise of yours.
One page an employer can run: Every grade and project at /verify. An employer opens it and runs the code.

Record, AI for CybersecurityExample

Project
A log anomaly detector
Seeded anomalies are found at the stated false-positive rate.
Graded
Project
A phishing classifier
Precision and recall are reported on the evaluation set.
Graded
Project
An AI-assisted SOC workflow
Every AI suggestion carries its evidence.
Graded
Every module
4 graded checkpoints
Each module ends in work Nova grades line by line against a rubric you can read.
Graded

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

5 entries, at your own pace. Reserving a spot holds the founding price.

Pre-order

How we help you find a job.

Proof, not a certificate: the projects you deployed are the thing you show, and the tools below are yours to use.

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
The same six-part plan the bootcamps use: target roles, the gap map, the proof to send, weekly actions, an interview log, the outcome. You run it with the career agent.
2
A record an employer can run
Your graded projects on /verify. An employer opens it and runs the code.
3
The career agent
Paste a real job posting at /career and it maps the role to your graded work and what to do next.
4
The roles directory
Every role we prepare people for, what it pays and what it asks, at /roles.
5
A path to the live cohort
If you want the instructor, the gates and the hiring sprint, the bootcamp on the same subject is one waitlist away.

Questions people ask.

About AI for Cybersecurity, answered from the plan on this page.

Founding spots are open. Hold yours.

Recorded by an instructor who does this work, graded by Nova. Spot holders hear the opening date first, and nothing is charged before you confirm.

AI tools you can defend a network with
Three graded projects on your record

A$45~~A$90~~