AI learning program
A structured learning program for people, teams and organizations that want to use AI thoughtfully and effectively. Work from the basics through prompting, evaluation, workflows and a small prototype, with guided practice throughout.
Who it is for
You do not need a technical background to begin. Bring a task you understand and a willingness to practice. People with more experience can focus on evaluation, workflow design or prototyping.
Short explanations, worked examples, guided exercises and feedback. We agree the level, tools, format and any prerequisites before a session. Training can stand on its own.
Use fictional or public information in exercises. A practice prototype is a learning artifact and needs further review before handling real operations or sensitive data.
Curriculum
Follow the sequence as a program or discuss a focused selection for your starting point and goals.
Module 1
Recognize what AI tools can and cannot do, and choose a suitable task to practice.
Practice: Compare responses to a familiar task. Identify missing context, uncertainty and claims that need checking.
Takeaway: A task checklist: where AI may help, what to keep private and what you will verify.
Module 2
Give an AI tool the context, task, constraints and output format it needs.
Practice: Turn a vague request into a reusable brief, then improve it by comparing the results.
Takeaway: A prompt template for a task you understand.
Module 3
Check an answer against sources and requirements before relying on it.
Practice: Review a response containing errors, omissions and unsupported claims. Decide what to correct or reject.
Takeaway: A review checklist with criteria for accuracy, completeness and usefulness.
Module 4
Connect prompting and review to a useful sequence of work.
Practice: Map a process, identify where AI might help and specify where a person reviews or makes the decision.
Takeaway: A workflow map with inputs, review points and a clear owner for each step.
Module 5
Translate a small need into a specification and test a first version.
Practice: Use fictional data to build or outline a small tool. Try realistic test cases and record what fails.
Takeaway: A prototype or build brief, plus test cases and gaps to resolve before operational use.
Module 6
Set boundaries for data, permissions, review and continued improvement.
Practice: Work through scenarios involving sensitive information, unreliable results and requests outside a tool's scope.
Takeaway: A practical use plan covering approved inputs, human review and when to escalate.
Ways to learn
Register interest in facilitated learning and coaching around your experience and goals. Explore the free reading series while we discuss a suitable format.
Practice together with examples relevant to your roles, shared review criteria and job aids you can use afterward.
Discuss a program across roles or departments, with learning objectives, responsible-use expectations and follow-up suited to your operating context.
Dates, duration, group size, tools and fees are confirmed in writing before you commit. No class dates are currently published here.
Registration interest
Tell us what you would like to learn. We will receive your inquiry and reply by email to discuss a suitable program. Sending this form does not reserve a place.
We will discuss availability, format and fees with you before confirming registration.
Please do not include confidential records, passwords or sensitive personal information. Read our privacy notice.
Prefer to email directly? Ask about the AI learning program.
Learn independently
Read the free AI Builder’s Playbook and try the exercises at your own pace.
Explore free learning resources ↗Consulting
Explore our business and technology consulting practices for implementation and broader organizational work.
Explore consulting services ↗