Mephana Academy
Understanding AI. Working with it effectively.
Mephana Academy focuses on understanding and applying AI, and developing the technical skills to build on its capabilities. The focus is professionals and organisations: people who want to explore what AI could mean for their work and what it takes to use it well.
Two learning directions
The two directions address different starting levels and learning needs. The technical direction has its own entry point; it does not require completing the practical direction first.
Working with AI in practice
For professionals with some familiarity with AI tools who want to tackle more substantial work. Topics include understanding how language models and AI agents work, giving clear assignments, supervising tasks and checking results. Developing repeatable ways of working is also part of this direction. The focus includes applications that can use tools to carry out tasks, and the decisions and checks you make along the way.
Technical development with AI
For developers and other technical professionals already working with AI. Topics include connecting AI applications to other systems, observing and evaluating their behaviour, and building reusable capabilities such as integrations and plugins. This includes understanding what an application actually executes, investigating failures and setting boundaries on execution.
Understanding, practice and judgment
The approach combines an understanding of the technology with practical exercises and careful evaluation. The aim is to help participants explain what an AI application is doing, recognise its limitations and assess whether the result is useful.
That includes the whole task: preparing an assignment, supervising the work and checking or correcting the outcome. This helps you judge when AI adds value and which way of working suits the task.
Rooted in Curaçao
I’m Ian van Eenennaam, from Curaçao and fluent in Dutch and Papiamentu. That background shapes my approach at the Academy: with room to explain concepts and discuss questions in these languages, using situations that connect with participants’ working lives.
This connection between language and practice also guides the more technical learning. Participants’ questions and experience help determine which explanations and examples are relevant.
What would you like to learn about AI?
What would you like to understand or do better with AI? Whether you’re exploring this for yourself or your organisation, tell me about your work, your current experience and what you would like to learn.
A few sentences about your learning needs are enough to start the conversation.