A tailored course, built for your situation
Deeper command of the AI Act compliance framework for technical implementation
Build from policy text to production-ready controls with confidence
$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
Early-career software engineer in a data and AI environment facing regulated workloads
Who this is not for
Executives seeking board-level summaries, legal counsel focused on liability interpretation, or non-technical compliance staff
What you walk away with
- Interpret AI Act articles with precision and apply them to system design
- Map high-risk AI obligations directly to data architecture and model lifecycle decisions
- Produce implementation-ready compliance artefacts that pass technical review
- Anticipate auditor and reviewer questions before documentation is submitted
- Own the technical narrative across cross-functional AI governance workflows
The 12 modules (with all 144 chapters)
Module 1. Foundations of the AI Act
Understand the structure, scope, and legal force of the AI Act, focusing on definitions of high-risk systems, prohibited practices, and conformity pathways.
12 chapters in this module
- What constitutes a high-risk AI system
- Prohibited AI practices under Article 5
- General principles of risk management
- Obligations for providers and deployers
- Conformity assessment options
- Role of notified bodies
- Geographic scope and extraterritorial effect
- Interaction with other regulations
- Timeline for implementation
- Key definitions in Title III
- Technical documentation requirements
- Summary of Annex III use cases
Module 2. Technical scope of high-risk classification
Translate the AI Act’s high-risk categories into engineering signals, focusing on real-world systems like biometric identification and critical infrastructure.
12 chapters in this module
- Understanding Annex III systems
- Biometric categorisation systems
- Critical infrastructure monitoring
- Education and vocational assessment
- Employment and recruitment tools
- Creditworthiness evaluation
- Law enforcement applications
- Migration management systems
- Public benefits eligibility
- Healthcare diagnostics
- Remote ID and surveillance
- Multi-factor risk aggregation
Module 3. Data governance under the AI Act
Implement data quality and provenance requirements from Article 10, focusing on training, validation, and monitoring data sets.
12 chapters in this module
- Data quality assurance principles
- Bias detection in training data
- Documentation of data provenance
- Representativeness of data sets
- Data lifecycle management
- Record-keeping for audits
- Versioning of training data
- Handling sensitive attributes
- Data retention policies
- Anonymization and privacy
- Monitoring data drift
- Data lineage for compliance
Module 4. Risk management system design
Design and document a risk management system aligned with Article 9, covering identification, estimation, and mitigation of risks.
12 chapters in this module
- Risk identification framework
- Hazard scenario mapping
- Severity and likelihood scoring
- Residual risk evaluation
- Fail-safe mechanisms
- Human oversight requirements
- Risk documentation structure
- Iterative risk assessment
- Incident reporting design
- Post-deployment monitoring
- Risk control validation
- Independent review triggers
Module 5. Transparency and documentation obligations
Build technical documentation and user information that satisfies Articles 11 and 13, including instructions for use and model cards.
12 chapters in this module
- Purpose and scope of technical documentation
- Model card requirements
- Version control documentation
- Performance metrics disclosure
- Expected lifetime and drift
- Input data specifications
- System limitations
- Instructions for use
- Human-in-the-loop guidance
- Update and patch procedures
- Language requirements
- Accessibility of documentation
Module 6. Human oversight implementation
Design effective human oversight mechanisms that meet Article 14, including real-time intervention and post-decision review.
12 chapters in this module
- Human-in-the-loop vs human-on-the-loop
- Real-time intervention design
- Post-decision review workflows
- Training for oversight personnel
- Audit logging for oversight
- Escalation triggers
- Role assignment for monitoring
- Interface design for control
- Feedback loops into model updates
- Oversight effectiveness metrics
- Fallback procedures
- Accountability trails
Module 7. Accuracy, robustness, and cybersecurity
Implement requirements from Article 15 on system performance, resilience, and security against adversarial attacks.
12 chapters in this module
- Performance under edge conditions
- Robustness testing methods
- Adversarial attack resistance
- Model drift detection thresholds
- Cybersecurity integration
- Secure development lifecycle
- Penetration testing alignment
- Failure mode analysis
- Redundancy mechanisms
- Model version rollback
- Monitoring for manipulation
- Incident response linkage
Module 8. Conformity assessment pathways
Navigate internal and third-party conformity routes, focusing on self-assessment documentation and notified body coordination.
12 chapters in this module
- Internal conformity process
- Self-declaration of conformity
- Notified body engagement
- Assessment of third-party providers
- Quality management system alignment
- Technical file assembly
- Audit readiness checklist
- Witness testing coordination
- Post-market surveillance planning
- Change management process
- Certification timeline
- Regulatory liaison design
Module 9. Implementation in MLOps pipelines
Integrate AI Act compliance checks into CI/CD, model monitoring, and deployment gates within MLOps environments.
12 chapters in this module
- Pre-deployment compliance gate
- Model risk scoring integration
- Automated bias testing
- Documentation auto-generation
- Version locking for audits
- Explainability by default
- Monitoring for prohibited use
- Drift alerting mechanisms
- Incident logging pipeline
- Human oversight triggers
- Policy compliance dashboards
- Audit trail export
Module 10. Audit and inspection readiness
Prepare for regulatory scrutiny with complete, traceable, and defensible compliance artefacts.
12 chapters in this module
- Audit trail structure
- Document retention schedule
- Internal audit prep
- Mock inspection drills
- Cross-team coordination plan
- Evidence mapping to articles
- Version-controlled artefacts
- Change log transparency
- Third-party data handling
- Incident reporting readiness
- Corrective action workflows
- Follow-up response design
Module 11. Cross-border deployment considerations
Navigate compliance when deploying AI systems across EU and non-EU jurisdictions, including data transfer and enforcement variation.
12 chapters in this module
- Extraterritorial application
- Data transfer mechanisms
- Local deployment variants
- Enforcement jurisdiction
- Subsidiary compliance alignment
- Language localization
- Cultural adaptation risks
- Local oversight requirements
- Incident reporting across borders
- Notified body coordination
- Supervisory authority contact
- Global incident response
Module 12. Future-proofing and evolution
Anticipate amendments, delegated acts, and emerging interpretations of the AI Act to maintain long-term compliance.
12 chapters in this module
- Tracking delegated acts
- Monitoring European Commission updates
- Stakeholder consultation signals
- Amendment impact assessment
- Industry standards convergence
- Alignment with ISO 42001
- NIST AI RMF integration
- Internal policy refresh cycle
- Training for new team members
- Vendor compliance tracking
- Public register preparation
- Staying ahead of enforcement trends
How this maps to your situation
- Before first compliance review
- During technical design phase
- Post-model development, pre-deployment
- When responding to auditor requests
Before vs. after
Before
Reactive engagement with compliance, relying on external guidance and fragmented documentation
After
Proactive technical ownership of AI Act requirements with repeatable, audit-ready implementation patterns
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 45 hours total, designed for self-paced learning with real-world implementation checkpoints.
How this compares to the alternatives
Unlike generic compliance overviews or legal summaries, this course is built for engineers who must implement AI Act requirements directly into systems, data pipelines, and MLOps workflows , with zero fluff and full technical specificity.
Frequently asked
Who is this course for?
Software engineers, MLOps practitioners, and technical leads implementing AI systems in regulated environments.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this relevant for non-EU companies?
Yes , any organization deploying AI systems into the EU market must comply, making this essential for global engineering teams.
$199 one-time. Approximately 45 hours total, designed for self-paced learning with real-world implementation checkpoints..
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