A tailored course, built for your situation
Become the Go To Practitioner on AI Act Implementation
A 12-module mastery path to being the reference point on AI Act readiness across your peers and leadership
$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 product and compliance practitioners in data and AI platforms who influence governance outcomes but aren’t compliance generalists
Who this is not for
Entry-level practitioners, non-technical policy analysts, or those outside data/AI product roles
What you walk away with
- Lead AI Act compliance interpretation within product teams without waiting for legal or external consultants
- Produce documented control mappings that stakeholders accept on first review
- Anticipate regulator and auditor follow-ups with source-backed responses
- Orchestrate vendor assessments aligned to AI Act Article 16 and Annex III classifications
- Be the first call when cross-functional leads need to operationalise AI Act requirements
The 12 modules (with all 144 chapters)
Module 1. AI Act Scope and Applicability
Define which products and use cases fall under high-risk classification based on Annex III. Interpret 'intended purpose' and 'deployed context' to determine compliance scope.
12 chapters in this module
- Understanding high-risk use cases
- Assessing intended purpose
- Evaluating deployer context
- Mapping model types to risk tiers
- Vendor input classification
- Third-party dependency review
- Use case boundary setting
- Thresholds for exemption
- Documentation of rationale
- Engagement with legal teams
- Internal escalation paths
- First compliance decision log
Module 2. Obligations for High-Risk Systems
Map AI Act Title IV requirements to engineering and product workflows. Translate legal language into technical and process controls.
12 chapters in this module
- Understanding technical documentation
- Designing data governance plans
- Logging system performance
- User information requirements
- Transparency for operators
- Human oversight mechanisms
- Accuracy metrics definition
- Robustness testing
- Bias mitigation planning
- Post-deployment monitoring
- Incident reporting process
- Control traceability matrix
Module 3. Conformity Assessment Pathways
Navigate the self-assessment vs notified body route. Prepare internal evidence packages for external validation.
12 chapters in this module
- Determining assessment type
- Internal audit checklist
- Evidence collection strategy
- Gap analysis framework
- Internal review cycle
- Notified body engagement
- Technical file assembly
- Statement of conformity
- Quality management systems
- Risk management documentation
- Testing methodology review
- Final sign-off workflow
Module 4. Data Governance for Compliance
Build data lineage and provenance practices that meet AI Act requirements for training, validation, and testing data.
12 chapters in this module
- Data provenance tracking
- Bias testing datasets
- Representativeness analysis
- Data collection documentation
- Version control for datasets
- Data access controls
- Annotation quality checks
- Data retention policies
- Consent verification process
- Data split documentation
- Model-data alignment
- Audit trail for data changes
Module 5. Technical Documentation Standards
Create living documentation that satisfies Article 11 and supports ongoing compliance reviews.
12 chapters in this module
- System architecture diagrams
- Purpose specification
- Risk classification rationale
- Input-output specifications
- Performance metrics
- Conformity assessment record
- Version history tracking
- Human oversight description
- Use case limitations
- Security measures overview
- Maintenance procedures
- Update log template
Module 6. Transparency and User Information
Design user-facing disclosures that meet Article 13 requirements without compromising IP or usability.
12 chapters in this module
- User instructions drafting
- Intent communication
- System limitations disclosure
- Human oversight explanation
- Contact point setup
- Language clarity standards
- Multilingual rollout plan
- Accessibility considerations
- Documentation versioning
- Feedback loop mechanism
- Update notification process
- Complaint handling workflow
Module 7. Human Oversight Design
Integrate human review points into AI workflows that satisfy Article 14 requirements.
12 chapters in this module
- Identifying oversight moments
- Role definition for reviewers
- Training for human operators
- Escalation triggers
- Decision logging
- Review frequency planning
- Override capability design
- Intervention success metrics
- Bias detection in review
- Workload management
- System feedback integration
- Oversight audit trail
Module 8. Accuracy, Robustness, and Cybersecurity
Implement testing and monitoring practices that ensure system reliability under Article 15.
12 chapters in this module
- Performance benchmarking
- Stress testing scenarios
- Adversarial attack resistance
- System degradation monitoring
- Fail-safe mechanisms
- Input validation rules
- Model drift detection
- Cybersecurity control alignment
- Penetration testing plan
- Incident response link
- Recovery time objectives
- System availability tracking
Module 9. Record Keeping and Logging
Establish audit-ready logging that captures system behavior and decision points.
12 chapters in this module
- Event logging scope
- System interaction capture
- Model version tracking
- Input-output logging
- User action recording
- Time stamping accuracy
- Log retention policy
- Access control for logs
- Audit trail queries
- Log integrity protection
- Export format standards
- Third-party access rules
Module 10. Vendor and Supply Chain Compliance
Assess third-party AI components and services against AI Act requirements.
12 chapters in this module
- Vendor documentation request
- Subsystem risk classification
- Contractual obligation mapping
- Due diligence checklist
- Compliance verification method
- Liability allocation
- Ongoing monitoring plan
- Change notification terms
- Exit strategy clauses
- Audit rights negotiation
- Performance benchmark sharing
- Escalation path setup
Module 11. Internal Governance and Escalation
Design internal workflows that ensure compliance ownership and rapid response to issues.
12 chapters in this module
- Oversight body formation
- Compliance role assignment
- Escalation triggers
- Incident reporting flow
- Cross-team coordination
- Decision documentation
- Policy update cycle
- Training rollout plan
- Audit preparation cycle
- Stakeholder communication
- Feedback integration
- Lessons learned review
Module 12. Staying Ahead of Enforcement Trends
Monitor evolving enforcement interpretations and adapt compliance practices proactively.
12 chapters in this module
- Regulatory watch process
- Enforcement case tracking
- Guidance document review
- National authority updates
- Court ruling analysis
- Industry best practice shifts
- Internal policy alignment
- Stakeholder awareness updates
- Control refinement cycle
- Public statement review
- Compliance culture metrics
- Future-proofing strategy
How this maps to your situation
- Product teams launching AI features in regulated sectors
- Data platform owners assessing governance alignment
- Cross-functional leads coordinating compliance
- Technical practitioners influencing control design
Before vs. after
Before
Relying on external guidance and fragmented internal knowledge to interpret AI Act requirements
After
Leading AI Act implementation with confidence, producing accepted artefacts, and being sought out for clarity across teams
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 3 hours per week over 12 weeks, designed to fit around product delivery cycles.
If nothing changes
Without structured knowledge of AI Act implementation, practitioners risk being bypassed in key decisions, relying on consultants, or producing rework-heavy deliverables that delay product timelines.
How this compares to the alternatives
Unlike generic AI ethics courses or high-level compliance summaries, this program delivers actionable, article-by-article implementation guidance tailored to technical product owners and data platform practitioners.
Frequently asked
Is this course technical or legal in focus?
It bridges both, designed for technical product owners who need to implement requirements without becoming lawyers.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me lead internal AI Act efforts?
Yes, you’ll gain the documented methods and reference materials needed to lead implementation confidently.
$199 one-time. Approximately 3 hours per week over 12 weeks, designed to fit around product delivery cycles..
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