EU AI Act Training: Compliance Certification
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Overview
What is EU AI Act and Ethical AI Compliance Training?
EU AI Act and Ethical AI Compliance training is a structured professional programme that teaches organisations how to understand, classify, govern, document, and monitor artificial intelligence systems under the EU AI Act and related Spanish and EU legal requirements.
This course provides a practical EU AI Act summary for business and compliance teams while also going deeper into EU AI Act compliance, high-risk AI systems, EU AI Act Article 50 transparency obligations, EU AI Act Annex III risk categories, GPAI model governance, AI Act fines, and ethical AI compliance.
The training explains the obligations of providers, deployers, importers, distributors, and downstream users. It also helps participants understand how the AI Act interacts with GDPR, LOPDGDD, human rights, equality, workplace regulation, product liability, AI governance, and third-party risk management.
Who Should Enroll in This EU AI Act and Ethical AI Compliance Course?
This course is designed for professionals and organisations that develop, procure, deploy, manage, audit, or govern AI systems.
For Individual Professionals:
If you are a compliance officer, lawyer, data protection officer, AI governance manager, product owner, HR manager, technology consultant, risk professional, software developer, AI project manager, or aspiring ethical AI compliance officer, this course provides practical knowledge for AI Act readiness.
- Understand the EU AI Act: Learn the structure, purpose, scope, key definitions, risk categories, implementation timeline, and compliance obligations.
- Build AI Governance Skills: Understand how to classify AI systems, document risk, manage oversight, and prepare for audit or regulatory review.
- Improve Career Value: Gain knowledge relevant to EU AI Act jobs, AI governance roles, responsible AI consulting, digital compliance, and AI risk management.
- Apply Ethical AI Principles: Learn how fairness, transparency, explainability, accountability, non-discrimination, and human oversight support trustworthy AI.
For Businesses and Corporate Teams:
If your organisation uses AI in HR, finance, customer service, healthcare, education, recruitment, fraud detection, marketing, public services, biometric systems, or automated decision-making, this course supports practical compliance readiness.
- AI Act Compliance Planning: Build an internal AI inventory, risk classification process, governance model, documentation framework, and monitoring routine.
- High-Risk AI Readiness: Understand requirements for high-risk AI systems, including risk management, data governance, documentation, logging, human oversight, accuracy, robustness, and cybersecurity.
- GPAI and Generative AI Governance: Prepare for general-purpose AI obligations, transparency rules, synthetic content controls, watermarking, and downstream deployment responsibilities.
- Audit and Enforcement Preparedness: Understand market surveillance, regulatory powers, EU AI Act fines, civil liability, contractual controls, and third-party AI risk.
What topics does this EU AI Act and Ethical AI Compliance course cover?
This course covers the EU AI Act from introduction to implementation. It explains the legal structure, definitions, risk categories, high-risk AI system requirements, GPAI governance, transparency obligations, enforcement, liability, ethical AI principles, and Spain-specific legal duties.
The course also includes current implementation guidance. The European Commission explains that the European AI Office and Member State authorities are responsible for implementing, supervising, and enforcing the AI Act, while the AI Board, Scientific Panel, and Advisory Forum support governance. The Commission has also published a General-Purpose AI Code of Practice to help industry comply with AI Act obligations relating to safety, transparency, and copyright for GPAI models.
Curriculum Summary:
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Module |
Key Topics |
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Module 1: Introduction to EU AI Regulation |
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Module 2: EU AI Act Risk Categories |
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Module 3: High-Risk AI System Requirements |
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Module 4: Governance of General-Purpose and Generative AI |
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Module 5: Enforcement, Risk, and Liability Frameworks |
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Module 6: Ethical AI Principles and Governance Structures |
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Module 7: Spanish AI Legal and Regulatory Framework |
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What is the Financial Cost/Risk of EU AI Act Non-Compliance?
The financial and operational risk of poor AI governance can be significant. Non-compliance may create exposure to administrative fines, product restrictions, regulatory audits, reputational harm, discrimination claims, data protection breaches, contract disputes, and loss of market access.
- AI Act Penalty Exposure: The EU AI Act includes enforcement mechanisms and penalties for serious breaches, making AI governance a financial risk issue as well as a technical issue. Regulation (EU) 2024/1689 is the official EU legal text laying down harmonised rules on artificial intelligence.
- High-Risk AI Failure: High-risk AI systems may require strict lifecycle controls, risk management, data quality, technical documentation, conformity assessment, CE marking, monitoring, and human oversight.
- Transparency Risk: Article 50-related transparency rules affect interactions with AI systems, synthetic content, generative AI outputs, and deepfake disclosures. The Commission is preparing support instruments for marking and labelling AI-generated content and transparency obligations.
- GPAI and Generative AI Risk: Providers of GPAI models must address transparency, copyright, and safety or security requirements, with additional expectations for systemic-risk models.
- Spanish Regulatory Risk: Organisations operating in Spain must also consider AESIA oversight, GDPR, LOPDGDD, employment law, equality rules, public sector requirements, and data protection duties.
- Operational and Contractual Risk: Weak AI contracts, unclear provider/deployer roles, undocumented model changes, poor vendor due diligence, and uncontrolled downstream deployment can create liability across the AI supply chain.
Learning Outcomes
Certification Information
Curriculum
Module 1: Introduction to EU AI Regulation
- 1.1 Origins and Legislative Structure of the EU AI Act
- 1.2 Key Definitions and Regulatory Terminology
- 1.3 EU Digital Strategy and Alignment with Other Laws
- 1.4 Obligations for Providers, Deployers, Importers, and Distributors
Module 2: EU AI Act Risk Categories
- 2.1 Prohibited AI Practices and Unacceptable Risk
- 2.2 High-Risk AI Use Cases and Classification Criteria
- 2.3 Transparency Rules for Limited-Risk AI
- 2.4 Minimal-Risk AI and Voluntary Best Practices
Module 3: High-Risk AI System Requirements
- 3.1 Governance and Lifecycle Risk Management
- 3.2 Data Quality, Training Practices, and Bias Control
- 3.3 Documentation, Conformity Assessment, and CE Marking
- 3.4 Human Oversight, Monitoring, and System Reliability
Module 4: Governance of General-Purpose and Generative AI
- 4.1 General-Purpose AI Models and Regulatory Scope
- 4.2 Systemic GPAI Obligations and Testing Requirements
- 4.3 Transparency, Watermarking, and Synthetic Content Rules
- 4.4 Responsibilities for Fine-Tuning and Downstream Deployment
Module 5: Enforcement, Risk, and Liability Frameworks
- 5.1 Market Surveillance, Audits, and Regulatory Powers
- 5.2 Penalties, Fines, and Non-Compliance Consequences
- 5.3 Civil and Product Liability in AI-Driven Systems
- 5.4 Contractual Controls and Third-Party Risk Management
Module 6: Ethical AI Principles and Governance Structures
- 6.1 Fairness, Non-Discrimination, and Human Rights Alignment
- 6.2 Transparency, Explainability, and Trustworthiness
- 6.3 Ethical Risk Assessment and Mitigation Techniques
- 6.4 Organizational AI Governance, Oversight, and Accountability
Module 7: Spanish AI Legal and Regulatory Framework
- 7.1 Spain’s Implementation of the EU AI Act
- 7.2 GDPR, LOPDGDD, and National Data Protection Duties
- 7.3 Spanish Labor, Workplace, and Equality Regulations
- 7.4 National AI Strategy, Public Sector Rules, and Enforcement Bodies
Final Exam
- Final Exam of the EU AI Act Training
