A tailored course, built for your situation
Mastering AI Act for Data and Governance Practitioners
A structured path to owning AI compliance across teams and regions
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
AI governance feels scattered and reactive across teams
The situation this course is for
Without a unified framework, AI compliance is handled inconsistently across regions and functions, leading to rework, audit surprises, and missed opportunities to shape strategy.
Who this is for
Senior data governance, platform, or compliance practitioner influencing AI policy across regions and functions
Who this is not for
Entry-level practitioners, auditors focused on checklists, or teams not involved in AI governance rollout
What you walk away with
- Operationalize the AI Act across multiple business units using repeatable compliance patterns
- Lead cross-functional alignment on AI risk thresholds and documentation standards
- Design scalable compliance workflows that reduce rework across region-specific implementations
- Anticipate regulator expectations with structured technical documentation templates
- Become the go-to reference for product and engineering teams launching AI features
The 12 modules (with all 144 chapters)
Module 1. AI Act Foundations and Scope
Understand the structure, obligations, and geographic reach of the AI Act as it applies to data-driven organizations.
12 chapters in this module
- Key definitions: AI system, high-risk, provider, deployer
- Regulatory scope: when the AI Act applies
- Territorial reach: EU and extraterritorial implications
- Core obligations for deployers and providers
- Role mapping: your place in AI Act compliance
- Sector-specific nuances in enforcement
- Timeline of implementation phases
- Difference between AI Act and national laws
- Interaction with EU Fundamental Rights Charter
- Labeling and transparency requirements
- Supply chain responsibilities
- Exemptions and research carve-outs
Module 2. Risk Categorization Under the AI Act
Learn how to classify AI systems by risk level and determine compliance requirements accordingly.
12 chapters in this module
- Unacceptable risk: prohibited uses
- High-risk: criteria and examples
- Limited risk: transparency obligations
- Minimal risk: documentation only
- Dynamic risk reassessment over time
- Mapping existing AI inventory to categories
- Vendor AI systems: shared responsibilities
- Internal AI tools: compliance scope
- Threshold for 'safety component' designation
- Human oversight triggers
- Use case escalation paths
- Documentation for risk classification decisions
Module 3. Data and Governance Requirements
Implement compliant data practices for high-risk AI systems, including training, validation, and monitoring.
12 chapters in this module
- Data quality standards for training sets
- Bias and representativeness checks
- Documentation of data provenance
- Version control for datasets
- Ongoing monitoring for data drift
- Record-keeping obligations
- Use of synthetic data
- Personal data handling under GDPR overlap
- Model input/output logging
- Traceability from data to decision
- Third-party data compliance
- Data lineage for audit readiness
Module 4. Technical Documentation Standards
Build and maintain complete technical files for high-risk AI systems as required by Article 11.
12 chapters in this module
- Mandatory content elements
- System description and purpose
- Architecture and model types
- Design and development rationale
- Testing methodologies
- Performance metrics and limitations
- Lifecycle oversight process
- Version control and updates
- Conformity assessment planning
- Record retention period
- Third-party audit access
- Template for standardized documentation
Module 5. Transparency and User Information
Ensure compliance with disclosure obligations for users and stakeholders of AI systems.
12 chapters in this module
- User-facing explanations
- Clear instructions for use
- Disclosure of AI interaction
- Exception handling notices
- Right to human review
- Model update notifications
- Language and accessibility requirements
- Marketing claims compliance
- Customer support readiness
- Internal awareness campaigns
- Training for frontline staff
- Audit trail for user communications
Module 6. Human Oversight Mechanisms
Design effective human-in-the-loop and human-on-the-loop controls for high-risk AI.
12 chapters in this module
- Types of oversight: in vs on the loop
- Critical decision points for intervention
- Training for human reviewers
- Escalation protocols
- Response time expectations
- Override capability design
- Monitoring system performance
- Feedback loops into model retraining
- Accountability for final decisions
- Documentation of human actions
- Role clarity across teams
- Testing oversight under stress conditions
Module 7. Robustness and Cybersecurity
Implement technical safeguards to ensure AI system security and reliability.
12 chapters in this module
- Adversarial attack resistance
- Input validation and sanitization
- Model resilience testing
- Fail-safe modes
- Cybersecurity integration
- Penetration testing for AI components
- Secure development lifecycle
- Monitoring for anomalous behavior
- Incident response planning
- Model rollback procedures
- Third-party vulnerability management
- Compliance with NIS2 overlap
Module 8. Conformity Assessment Pathways
Navigate the process for demonstrating compliance with the AI Act through internal or external review.
12 chapters in this module
- Self-assessment vs notified body
- High-risk system checklist
- Internal audit process design
- Third-party certification steps
- Notified body selection criteria
- Documentation package assembly
- Gap analysis methodology
- Remediation planning
- Declaration of conformity
- Ongoing surveillance requirements
- Post-market monitoring
- Handling non-compliance findings
Module 9. AI Governance Across Regions
Adapt AI Act compliance strategies for global operations and regional variations.
12 chapters in this module
- Harmonizing standards across geographies
- Local legal override considerations
- Regional enforcement priorities
- Cross-border data flows
- Translation and localization
- Local stakeholder engagement
- Centralized vs decentralized compliance
- Regional advisory boards
- Cultural context in AI use
- Local incident reporting
- Global playbook with local flexibility
- Benchmarking compliance maturity
Module 10. Cross-Functional Implementation
Lead adoption of AI Act principles across product, engineering, legal, and operations teams.
12 chapters in this module
- Stakeholder identification
- RACI mapping for AI compliance
- Product lifecycle integration
- Engineering team enablement
- Legal alignment on liability
- Procurement and vendor oversight
- HR and training rollout
- Finance and budget ownership
- Project management coordination
- Change management approach
- Success metrics across functions
- Feedback integration loops
Module 11. Monitoring and Reporting
Establish ongoing compliance monitoring and internal reporting structures.
12 chapters in this module
- Key risk indicators dashboard
- Compliance scorecards
- Incident logging and analysis
- Trend reporting to leadership
- Audit preparation cycle
- Regulator engagement protocol
- Stakeholder update rhythm
- Lessons learned documentation
- Corrective action tracking
- Continuous improvement process
- Benchmarking against peers
- Internal audit schedule
Module 12. Future-Proofing AI Governance
Anticipate upcoming amendments, enforcement trends, and expansion of the AI Act framework.
12 chapters in this module
- EU AI Office update tracking
- Proposed amendments to watch
- Emerging sector-specific rules
- AI liability directive alignment
- Global regulation convergence
- Enforcement case law trends
- Stakeholder coalition developments
- Public scrutiny patterns
- Technology shifts affecting compliance
- Long-term governance staffing
- Budget planning for compliance
- Building external influence
How this maps to your situation
- When launching a new AI product
- Before regulatory inquiry
- During internal audit prep
- After organizational restructuring
Before vs. after
Before
AI compliance efforts are siloed and reactive, requiring constant coordination across teams and regions.
After
You lead consistent, proactive AI Act implementation across business units, with standardized artifacts and clear ownership.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 3-4 hours per module, designed for completion over 6-8 weeks with practical application between modules.
If nothing changes
Without structured governance, organizations face increased regulatory scrutiny, inconsistent implementation, and reputational risk when AI systems underperform or cause harm.
How this compares to the alternatives
Unlike generic AI ethics courses, this program delivers actionable, legally-grounded implementation steps aligned with the AI Act , specifically designed for practitioners operating across regions and functions.
Frequently asked
Is this course relevant if I'm not based in the EU?
Yes. The AI Act sets a global benchmark, and its requirements affect any organization deploying AI systems into the EU market, regardless of location.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me with internal stakeholder alignment?
Yes. Modules include RACI mapping, cross-functional rollout plans, and templates for securing buy-in from product, engineering, legal, and leadership teams.
$199 one-time. Approximately 3-4 hours per module, designed for completion over 6-8 weeks with practical application between modules..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours