The AI Masterclass: from zero to a shipped website in two days.
Not a prompt-tips seminar. A practical intensive where you learn what AI really is, direct a coding agent safely — and build, test and ship a real website with your own hands.
Built for people starting from zero.
If you can use a laptop, you can do this course. No coding background required.
Complete beginners
You've heard about AI agents but never driven one. We start at the real beginning — what a model is — and have you running your own agent inside the first 45 minutes.
Business owners
You want AI working in your business, not just in headlines. Learn to direct it with intent — brief it, constrain it, verify it — and leave with a live website to prove it.
Teams getting started
Give your whole team one shared, safe way of working with AI — instructions, memory, Git and security habits — instead of ten private experiments.
Two days, 22 modules, one continuing project.
Every module below is a live deck plus a hands-on lab. Modules 0 and 1 are open as free previews.
Day 1
Understand, Direct and Control AI- Welcome · ~10–15 min00Welcome & Foundation — what AI is and how we'll work with itPreview
- 09:00–09:4001Setup lab: launch your first AI coding agentPreview
- 09:40–10:1002Markdown early: the files that make AI work understandable
- 10:10–10:3003VS Code vs terminal vs web chat
- 10:45–11:1504What is an LLM and how does it work?
- 11:15–11:4505Anatomy of an AI system
- 11:45–12:1506Prompt engineering
- 13:00–13:3007Context engineering
- 13:30–14:0008Global rules, project instructions and guardrails
- 14:15–14:4509Memory and external knowledge
- 14:45–15:1510AI security, privacy and safe operations
- 15:15–16:0011AI decisions, verification and reusable skills
Day 2
Organise, Build, Test and Maintain- 09:00–09:2012Recap and recover the project
- 09:20–09:5013Local files, Git and backups
- 09:50–10:2014Project structure and reusable skills
- 10:35–11:0015Plan the website
- 11:00–12:1516Build the first website
- 13:00–13:4517Debugging, testing and refinement
- 13:45–14:1518Security and deployment basics
- 14:30–15:0019Cowork-style agents and multi-step workflows
- 15:00–15:4020Website capstone
- 15:40–16:1521Showcase, reflection and next steps
What you'll actually be able to do.
Not "exposure" to AI — capability. By the end of day two, each of these is something you've done with your own hands, on your own machine, on a real project.
- ▸Explain what an LLM is, how it generates responses, and why it can make mistakes
- ▸Describe the parts of an AI system — model, instructions, context, tools, files and services
- ▸Write clear prompts and structure tasks with constraints and acceptance criteria
- ▸Manage context, project instructions and persistent memory across sessions
- ▸Apply practical security habits around files, tools, commands and credentials
- ▸Use AI for structured decision support while verifying important claims
- ▸Protect your work with local files, Git version control and backups
- ▸Build, test and refine a real website with an AI coding agent
Foundation first. Hands on always.
This is not a slideshow you watch — it's a workshop you do. Every concept lands in a lab within minutes.
Explain
A short, plain-English explanation of the concept — what it is and why it matters — before any tool is opened.
Demonstrate
The facilitator does it live on the room screen — including mistakes and recovery, not just the happy path.
Practice
You do the same thing immediately, in a hands-on lab, with support reaching every seat in the small group.
Review
We look at what the agent did and why — building the verification habit that separates operators from spectators.
One continuing project
You don't do 22 disconnected exercises. One project runs through the whole course — the brief you write on day one becomes the website you ship on day two, with instructions, memory and Git history carrying forward at every step.
Foundation before tools
Day one builds the mental model — what an LLM is, why it can be confidently wrong, how an AI system fits together. Tools change every quarter; the principles you learn here transfer across all of them.
You walk out with working assets, not notes.
Everything below exists on your machine and in your student account when you leave the room.
A working agent environment
Claude Code or Codex installed, authenticated and configured on your own machine — ready for the next project.
A working, tested website
Your capstone: a real site you planned, built, debugged and tested in the browser — not a demo you watched.
A Git-managed project
A local project under version control, with the commit-and-recover habits that protect everything you build next.
Instructions, memory & handover files
A Markdown README, project brief, project instructions and a memory/handover file — the system that makes AI work repeatable.
A security & permissions checklist
A practical checklist for files, tools, commands and credentials, so safe operation becomes the default.
A repeatable process
A reusable project template plus a plan → build → review → improve loop you can apply to any future AI project.
Honest answers to the usual questions.
Do I need any coding or AI experience?
No. The masterclass is designed for beginners with little or no AI coding experience. We start with what an AI model actually is and build up from there — every concept is explained in plain English before you use it.
What should I bring?
A laptop you can install software on, and its charger. We handle account access, installation and authentication together in the first module, with support on hand — setup time is part of the schedule, not an afterthought.
What tools will we use?
An AI coding agent — Claude Code or Codex — alongside VS Code, the terminal, Markdown and Git. We teach transferable principles, not memorized clicks, so what you learn carries across tools and versions.
How big are the classes?
We run small groups on purpose. Every module includes a hands-on lab, and the facilitator needs to reach every seat — so the room stays small enough for individual help when something goes sideways.
Do I keep the materials?
Yes. You keep your student account, all 22 decks and lab sheets, the starter project template, and everything you build in class — including the website and its Git history.
What happens after the masterclass?
You leave with a reusable template and a process for continuing independently. If your team or business wants to go further, our For Teams sessions and custom app builds pick up exactly where the course leaves off.
Two days from now, you could be shipping.
Join the next NavySteel AI Masterclass — small group, hands-on, and a real website to show for it.