The EU Artificial Intelligence Act (AI Act) introduces the EU’s first comprehensive, risk‑based legal framework for artificial intelligence. This online course explains the Act’s structure, the obligations it places on providers, deployers and users of AI, and practical steps organisations must take to achieve compliance. Through short lessons, scenario‑based exercises and downloadable templates, you will learn how to identify high‑risk systems, implement governance and documentation, and design compliance pathways that align with the Act and related EU rules (e.g., data protection).
This 6‑hour online e‑learning course is designed to be practical and job‑relevant: bite‑sized modules cover legal concepts, technical controls, organisational governance, and real‑world examples so learners can apply the principles immediately within their organisations.
Participants who complete the course and pass the final multiple‑choice assessment receive a Certificate of Completion. The certificate documents the number of learning hours and the core competencies covered (AI Act fundamentals, risk classification, documentation & governance). Organisations can use the certificate as evidence of staff training in internal audits or supplier reviews.
The course is organised into modular lessons. Each lesson combines short videos, reading, interactive knowledge checks and scenario exercises. Downloadable templates are provided so learners can put the learning into practice immediately.
Module structure (8-10 hours total based on your speed)
|
Module |
What we cover |
Key learning outcomes |
Interactive session |
|
Module 1 — Introduction (45 mins) |
High‑level overview of the EU AI Act, risk‑based approach, key definitions (AI system, provider, deployer, user), and how the Act interacts with GDPR and other EU law. Course navigation and how to use the templates. |
Understand the Act’s scope and structure, identify the roles and responsibilities in the AI value chain, and know how to use the course resources. |
N/A |
|
Module 2 — Prohibited AI practices & transparency obligations (45 mins) |
Detailed review of practices the Act prohibits (unacceptable risks) and transparency requirements (AI‑generated content labelling, user notices, information obligations). Intersection with ethical and policy considerations. |
Recognise prohibited uses and required transparency measures; be able to draft a compliant user notice and synthetic content label. |
N/A |
|
Module 3 — High‑risk AI systems (75 mins) |
How to identify high‑risk systems (Annex listings and classification rules), obligations that attach to high‑risk systems (technical documentation, risk management systems, data governance, human oversight), and examples from sectors (HR, finance, health). |
Run a high‑level high‑risk classification, list required risk‑management artefacts and mitigation measures, and propose initial remediation steps. |
N/A |
|
Module 4 — Low/Limited‑risk AI & ISO 42001 alignment (60 mins) |
Differentiating low/limited‑risk systems from high‑risk; recommended good‑practice controls; introduction to ISO 42001 (AI management systems) and how it complements the AI Act. Practical steps to scale governance for lower‑risk systems. |
Distinguish low/limited‑risk controls, explain how ISO 42001 provides a management framework, and prepare a proportional governance checklist. |
N/A |
|
Module 5 — Conformity (self‑) assessment & documentation (60 mins) |
Conformity assessment pathways for high‑risk systems (including self‑assessment vs third‑party routes), preparing technical documentation, logging, and evidence for audits and market surveillance. Practical tips for small and medium teams. |
Understand conformity options, prepare a conformity documentation plan and a basic self‑assessment workflow. |
N/A |
|
Module 6 — General‑purpose AI (GPAI) models (45 mins) |
Unique considerations for general‑purpose and foundation models (scope, transparency, emergent behaviour, APIs, model‑carding, and how the Act addresses GPAI). Risk mitigation strategies and vendor controls. |
Identify GPAI‑specific risks, draft model‑card style disclosures and vendor controls, and plan monitoring for emergent behaviour. |
N/A |
Each learner receives: