How these courses were made
Timson AI Academy teaches responsible use of AI, so here is exactly how AI was used to build it.
The courses were designed and directed by Rey Timson, a learning designer and AI educator with a background in AI and natural language processing. I used AI tools (Claude, by Anthropic) to help draft lesson text, quiz questions, diagrams and code examples, following my own course structure and learning design.
What I did
- Chose the learning paths and courses, based on labour-market research
- Set the structure, depth, learning outcomes and assessment standard
- Chose which sources the courses rely on
- Directed, reviewed and revised the content
- Take responsibility for what is published
What AI helped with
- Drafting lesson text, examples and activities
- Writing quiz and assessment questions
- Drawing diagrams and writing code examples
- Building the course pages
Built on trusted sources
Every course draws on published guidance from Anthropic, OpenAI, Microsoft, AWS, IBM, Google and official regulatory sources. These are linked in each module under "Go further", so you can check them yourself.
Quality checks
- Code is tested. The Python examples in the technical courses were run to check they work and that their output matches what the lessons say.
- Links are checked. External links were verified when the courses were published.
- Content is reviewed and updated regularly. AI and AI law change quickly, so each course shows when it was last reviewed.
AI-assisted content can contain mistakes. That is one reason these courses teach you to check AI output. If you spot an error, please email reytimson@gmail.com and I'll correct it.
Why I'm telling you this
Transparency, human oversight and accountability are core principles of responsible AI, and they're taught throughout this academy. Using AI this way, with a person directing and reviewing the work and being open about it, is the practice these courses recommend.
Educational content only. It is not legal, security or professional advice.