From idea to an outcome
Connect problem framing, AI tools, a simple prototype, and a presentation. Exercises reflect participants' subject areas and coding experience.
Learn by building.
Connect AI to your work.
Define a problem, prepare the inputs, create something useful, and check the result. We shape practical workshops around your institution or team's experience and goals.
Start with the goal and the learners.
Practice with everyday work
Break down tasks such as writing documents, finding information, or organizing data. Define what can be automated and what people need to check.
Build, connect, and review
Connect tools and data, then inspect results and errors. We check accounts, access, and development environments in advance.
Follow a task from definition to review.
Choose what to improve
Identify users and recurring tasks. Write down AI's role and the criteria for a useful result.
Make the inputs usable
Organize sources and structure, then specify the output format and the conditions to check.
Create and run something small
Depending on the course, produce a document draft, a data workflow, a simple interface, or an automation.
Find errors and explain the result
Compare outputs with their sources. Explain what works, what does not, and what to improve.
Leave with work you can return to.
A task brief
A one-page outline of users, inputs, expected outputs, and review criteria.
A practical artifact
A document, organized dataset, or prototype, with the steps used to create it.
A review record
A checklist of errors, corrections, supporting evidence, limitations, and next steps.
These are example modules and deliverables. The agreed scope depends on the goal, group size, schedule, prior experience, and available tools.
Tell us who is learning and what they want to do.
Include your institution or team, group size, prior experience, preferred timing and format, and the work you want to explore.