A tailored course, built for your situation
Deeper command of the AI Act compliance architecture
Master the structure, obligations, and implementation logic of the EU AI Act as it applies to high-risk AI systems in data platforms
$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.
Who this is for
Senior practitioner in AI governance, data platform compliance, or regulatory implementation with exposure to EU market requirements
Who this is not for
Entry-level compliance staff, general legal counsel without technical AI focus, or professionals outside data-intensive regulated AI applications
What you walk away with
- Full command of the AI Act’s high-risk system classification criteria
- Ability to map technical documentation requirements to existing data workflows
- Interpretation fluency across Articles 5, 10, 12, 28, and Annex III
- Structured approach to conformity assessments for AI components in data pipelines
- Precedent-backed implementation playbook for audit-ready documentation
The 12 modules (with all 144 chapters)
Module 1. AI Act structure and jurisdictional reach
Break down the regulation’s legal hierarchy, scope, and thresholds for AI system classification.
12 chapters in this module
- Regulation vs Directive distinction
- Scope under Article 3
- Market placement criteria
- Exemptions and exclusions
- Territorial application rules
- Enforcement bodies by member state
- Timeline for implementation
- Interaction with other EU laws
- Definition of AI system
- High-risk criteria overview
- Role of standards bodies
- CE marking relevance
Module 2. High-risk AI systems and Annex III
Analyze the specific use cases classified as high-risk and their technical implications.
12 chapters in this module
- Biometric categorization systems
- Critical infrastructure monitoring
- Education assessment tools
- Employment screening AI
- Essential services access
- Law enforcement prediction
- Migration assistance decisions
- Judicial recommendation systems
- Real-time remote biometrics
- Post-authorization surveillance
- Thresholds for impact
- Contextual override conditions
Module 3. Obligations for providers and deployers
Clarify responsibilities across the AI lifecycle under Title III.
12 chapters in this module
- Provider vs deployer distinction
- Pre-market conformity assessment
- Quality management system requirement
- Technical documentation mandate
- Record-keeping duration
- Incident reporting duties
- Transparency to users
- Human oversight design
- Accuracy and robustness
- Data governance rules
- Model change notification
- Post-market monitoring
Module 4. Technical documentation for compliance
Build audit-ready documentation sets aligned with Annex IV.
12 chapters in this module
- System overview and diagram
- Intended purpose definition
- Performance metrics specification
- Input data provenance
- Model architecture summary
- Risk mitigation measures
- Human oversight capability
- Version control process
- Testing methodology
- Failure mode analysis
- Update and retraining logic
- Decommissioning procedure
Module 5. Conformity assessment pathways
Navigate internal and notified body routes for compliance verification.
12 chapters in this module
- Self-declaration for non-high-risk
- Notified body involvement
- Assessment scope definition
- Internal audit process
- External review timing
- Gap analysis framework
- Evidence collection
- Certification validity
- Reassessment triggers
- Cross-border recognition
- Audit trail retention
- Corrective action process
Module 6. Governance and monitoring obligations
Implement ongoing compliance controls for AI system performance.
12 chapters in this module
- Performance monitoring plan
- Anomaly detection setup
- User feedback mechanism
- Incident logging
- Model drift tracking
- Retraining triggers
- Version comparison
- Change impact analysis
- User incident reporting
- Remediation workflow
- Audit log retention
- Governance committee role
Module 7. Transparency and user information
Ensure compliant disclosure to downstream users and stakeholders.
12 chapters in this module
- System purpose disclosure
- Limitations statement
- Human oversight explanation
- Contact information
- Language requirements
- Accessibility standards
- Vendor documentation access
- API documentation level
- Support channels
- Update notification method
- Deprecation timeline
- Third-party component notice
Module 8. Data governance for training sets
Align data practices with Article 10 and data quality expectations.
12 chapters in this module
- Data provenance tracking
- Bias mitigation steps
- Representativeness check
- Data labeling accuracy
- Preprocessing transparency
- Augmentation disclosure
- Synthetic data use
- Data versioning
- Retention policy
- Consent verification
- Data subject rights
- Third-party data audit
Module 9. Human oversight mechanisms
Design effective human-in-the-loop controls for high-risk decisions.
12 chapters in this module
- Oversight timing
- Override capability
- Intervention points
- Training for reviewers
- Escalation paths
- Decision logging
- Fallback procedures
- Monitoring frequency
- Error correction
- Review documentation
- Accountability assignment
- Audit readiness
Module 10. Risk management system design
Develop a structured framework for identifying and mitigating AI risks.
12 chapters in this module
- Hazard identification
- Risk severity scoring
- Likelihood assessment
- Control effectiveness
- Residual risk evaluation
- Risk register
- Mitigation validation
- Third-party risk
- Supply chain exposure
- Emerging threat monitoring
- Incident classification
- Response planning
Module 11. Implementation playbook for platform teams
Adapt AI Act compliance to data platform and MLOps workflows.
12 chapters in this module
- Model registry integration
- Pipeline documentation
- Feature store compliance
- Model monitoring setup
- CI/CD for AI
- Access control alignment
- Audit trail capture
- Version provenance
- Environment isolation
- Testing automation
- Reproducibility setup
- Decommissioning workflow
Module 12. Compliance artifacts and audit readiness
Generate complete, defensible documentation for internal and external review.
12 chapters in this module
- SoA drafting
- Conformity checklist
- Technical file assembly
- Audit trail sample
- Process diagrams
- Control mapping
- Gap evidence
- Remediation logs
- External correspondence
- Internal sign-off
- Review cycle planning
- Playbook iteration
How this maps to your situation
- When defining AI system boundaries
- Before deploying a new model pipeline
- During internal audit preparation
- When responding to compliance queries
Before vs. after
Before
Navigating the AI Act feels fragmented, with obligations scattered across annexes and dependent on external interpretations.
After
You move through the regulation with precision, knowing exactly which requirements apply and how to satisfy them in practice.
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 6 hours of focused reading and implementation planning, structured in 10-minute modules.
If nothing changes
Without structured command of the AI Act, teams risk delayed deployments, audit findings, or misaligned investments in compliance infrastructure.
How this compares to the alternatives
Generic AI governance courses cover broad principles; this course delivers exact compliance logic, regulatory citations, and implementation sequences specific to the AI Act.
Frequently asked
Is this course focused on technical or legal compliance?
It bridges both, with technical implementation pathways for legal obligations under the AI Act.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this apply to non-EU companies?
Yes, if you deploy AI systems into the EU market or affect EU residents, the regulation applies.
$199 one-time. Approximately 6 hours of focused reading and implementation planning, structured in 10-minute 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