Practical guides to working with AI
Plain-English explanations of how AI works and how to use it well at work, taken from the lessons of The Complete AI Practitioner Course.
Why AI makes things up, and how to reduce it
Why AI tools state false things with total confidence, when it is most likely to happen, and three practical ways to reduce it at work.
How to write better AI prompts: brief it like a contractor
A practical way to write AI prompts that work: treat the model like a capable contractor you have never met, and use five levers you can always pull.
How to check AI output before you trust it
Fluent is not the same as right. Simple verification habits, source-checking and a red-flags checklist for reviewing anything an AI tool produces.
Pre-training, fine-tuning and retrieval (RAG) explained
The three places an AI model's knowledge can live: pre-training, fine-tuning and retrieval. What each is good for, the trade-offs, and when to use which.
Will AI take my job? Think in tasks, not roles
Why 'will AI take my job' is the wrong question. Jobs are bundles of tasks; here is how to assess your own role and where your value grows.
How to roll out AI in your team in 30 days
A week-by-week plan for getting a team using AI well: pick the right use cases, run an honest pilot, train people, and decide whether to scale.
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The Complete AI Practitioner Course has 71 modules across 12 parts, about 18 hours of guided learning, an interactive exercise in every module, a final assessment, and a certificate with a LinkedIn credential. No code needed. US$299, paid once.
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