A tailored course, built for your situation
Mastering AI Act for Senior Machine Learning Governance Practitioners
A step-by-step implementation path for trusted AI deployment in regulated environments
$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 technical practitioner in AI/ML governance, embedded in a data platform environment, with hands-on experience in model deployment and compliance alignment
Who this is not for
Entry-level engineers, product managers without governance exposure, or executives seeking high-level overviews
What you walk away with
- Own end-to-end AI Act compliance workflows within your current role
- Produce audit-ready documentation that survives leadership changes
- Lead cross-functional alignment on high-risk AI use cases
- Deploy repeatable control templates across model pipelines
- Gain recognition as the internal authority on AI governance implementation
The 12 modules (with all 144 chapters)
Module 1. AI Act Foundations for Practitioners
Grounding in the legal text, scope, and real-world interpretation as applied to machine learning systems.
12 chapters in this module
- Understanding Article 5 classifications
- High-risk AI system criteria
- Obligations for providers vs deployers
- Geographic scope and applicability
- Interaction with national laws
- Relationship to existing frameworks
- Timing of conformity assessments
- Transparency requirements
- Data governance expectations
- System documentation mandates
- Human oversight thresholds
- Record-keeping obligations
Module 2. Governance Mapping for ML Workflows
Aligning AI Act requirements to existing ML pipeline stages and team responsibilities.
12 chapters in this module
- Mapping stages to Articles 8, 15
- Identifying system boundaries
- Risk classification workflows
- Model lineage and traceability
- Training data provenance
- Validation dataset controls
- Performance monitoring design
- Bias testing integration
- Logging for audit readiness
- Version control alignment
- Incident reporting triggers
- Post-deployment monitoring
Module 3. High-Risk Use Case Identification
Practical classification of AI systems based on real-world impact and regulatory scrutiny.
12 chapters in this module
- Biometric identification rules
- Critical infrastructure applications
- Education and vocational tools
- Employment decision systems
- Essential service access
- Law enforcement applications
- Migration and asylum processing
- Legal assistance tools
- Healthcare diagnostics
- Creditworthiness models
- Insurance underwriting
- Public benefits allocation
Module 4. Technical Documentation Framework
Building the AI Act Article 11 technical file with minimal overhead and maximum reuse.
12 chapters in this module
- System description template
- Intended purpose definition
- Model architecture overview
- Training data summary
- Validation results format
- Input-output specifications
- Accuracy metrics selection
- Robustness testing protocol
- Cybersecurity safeguards
- Version control log
- Change management process
- Update deployment strategy
Module 5. Risk Management Implementation
Designing and documenting the AI-specific risk management system required under Article 9.
12 chapters in this module
- Risk identification framework
- Hazard classification matrix
- Harm severity scoring
- Likelihood assessment
- Risk prioritization rules
- Mitigation control design
- Residual risk evaluation
- Ongoing monitoring plan
- Incident escalation path
- Risk register maintenance
- Human oversight integration
- Fail-safe mechanisms
Module 6. Data Governance for Training Sets
Meeting data quality and provenance requirements for high-risk AI systems.
12 chapters in this module
- Data lineage documentation
- Representativeness validation
- Bias detection methods
- Data cleaning protocols
- Annotated data quality
- Data retention policies
- Data subject rights
- Data access controls
- Data integrity checks
- Data versioning
- Data update procedures
- Data provenance audit trail
Module 7. Human Oversight Design
Creating meaningful, enforceable human oversight mechanisms for high-risk AI.
12 chapters in this module
- Oversight timing and triggers
- Role definition for supervisors
- Intervention capability
- Feedback loop design
- Oversight training program
- Performance dashboards
- Intervention logging
- Escalation protocol
- Override authority
- Oversight audit trail
- Effectiveness review
- Oversight documentation
Module 8. Transparency and Information Requirements
Implementing Article 13 requirements for deployers and providers.
12 chapters in this module
- User notification standards
- System capability disclosure
- Limitations documentation
- Contact information provision
- Instructions for use
- Public registry compliance
- API documentation
- Third-party integration rules
- Model card content
- System update notices
- Downtime communication
- Incident reporting
Module 9. Conformity Assessment Process
Navigating the internal process required before deployment of high-risk AI systems.
12 chapters in this module
- Internal audit checklist
- Compliance verification steps
- Sign-off workflow design
- Evidence collection
- Documentation review
- Gap remediation process
- Third-party assessment prep
- Notified body coordination
- Declaration of conformity
- Record retention
- Reassessment triggers
- Post-deployment review
Module 10. Cross-Functional Alignment Playbook
Leading alignment between legal, compliance, engineering, and product teams.
12 chapters in this module
- Stakeholder identification
- Governance council design
- Decision rights mapping
- Escalation path definition
- Communication protocol
- Change approval workflow
- Conflict resolution
- Feedback integration
- Training rollout
- Policy update cycle
- Audit preparation
- Incident response
Module 11. Implementation Templates Library
Reusable, real-world templates for AI Act compliance artefacts.
12 chapters in this module
- Risk register template
- Technical documentation pack
- Data governance plan
- Human oversight SOP
- Transparency notice
- Model card template
- Incident log
- Audit preparation pack
- Vendor assessment form
- Change request form
- Policy version control
- Training program outline
Module 12. Sustained Compliance and Evolution
Maintaining compliance as AI systems evolve and regulations adapt.
12 chapters in this module
- Change impact assessment
- Version update process
- Model revalidation
- Continuous monitoring
- Incident investigation
- Regulatory change tracking
- Stakeholder updates
- Documentation refresh
- Team onboarding
- Lessons learned
- Process improvement
- Governance maturity
How this maps to your situation
- Pre-deployment governance design
- Cross-functional alignment
- Audit and regulatory readiness
- Sustained operational compliance
Before vs. after
Before
Overseeing piecemeal AI compliance efforts without full ownership of the governance framework.
After
Owning end-to-end AI Act implementation with documented authority across teams and decisions.
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters total)
- 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, 60 minutes per module, designed for completion within six weeks with consistent pacing.
If nothing changes
Without clear governance ownership, AI initiatives risk delays, rework, or regulatory exposure, especially as enforcement timelines approach.
How this compares to the alternatives
Unlike generic AI ethics courses or high-level overviews, this program delivers actionable implementation steps tied directly to the AI Act’s legal text and real-world deployment challenges.
Frequently asked
Is this course relevant if my company isn’t in Europe?
Yes. The AI Act is shaping global standards, and its requirements are being mirrored in national laws and corporate governance worldwide.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me lead beyond my current role?
It expands your current mandate, giving you formal influence over governance decisions without requiring a title change.
$199 one-time. Approximately 45, 60 minutes per module, designed for completion within six weeks with consistent pacing..
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