AI Literacy for Professionals and the EU AI Act

About this course

A short, non-technical course for anyone who uses, buys or decides about AI at work. Learners see how modern AI and large language models really work and fail, practise using generative AI tools well and safely, learn what the EU AI Act asks of organisations and their staff (including the Article 4 AI literacy duty, as amended in 2026), and apply a simple risk canvas to a use case from their own role. Suitable as an organisation's AI literacy programme for staff.

For: business professional, tech leader, student, architect, software engineer, data professional.

Learning outcomes

On successful completion you will be able to:

1. 1Explain in plain language how modern AI systems, including machine learning and large language models, are built, what they do reliably and where they fail.
2. 2Describe the EU AI Act's risk-based structure, its prohibited practices, the Article 4 AI literacy duty and the obligations that follow for deployers in the learner's own context.
3. 3Use generative AI tools effectively and safely for work tasks, applying prompting techniques, verification of outputs and data-protection rules.
4. 4Analyse a workplace AI use case for benefits, risks, affected people and the human oversight it needs.
5. 5Decide when AI use in one's own role is appropriate, and raise concerns about bias, privacy, security or misuse through the right channels.

Modules and lessons

1. Week 1How modern AI works⌄

   • How modern AI works, without the hype
2. Week 2Using AI well at work⌄

   • Using generative AI well and safely at work
3. Week 3The EU AI Act and your obligations⌄

   • The EU AI Act and what it asks of you
4. Week 4Risk, ethics and judgement⌄

   • Risk, fairness and human oversight in practicecase study

Assessment

• Quiz (40%)

  Four short weekly quizzes drawn from the lesson quiz banks.

• Portfolio (20%)

  Three real work tasks completed with an approved generative AI tool, each with the prompt, how the output was verified and a short reflection.

• Case analysis (40%)

  AI use-case risk canvas for a scenario from the learner's own role, covering benefits, affected people, risks, oversight and an appropriate-use decision.

Pass mark 60%. Grades: Distinction, Merit, Pass.