A tailored course, built for your situation
Deeper command of the AI Act compliance framework
Master the structure, obligations, and implementation pathways of the EU AI Act as a core engineering competency
$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 data and AI platforms supporting regulated deployments
Who this is not for
Entry-level compliance staff or non-technical policy analysts without implementation responsibilities
What you walk away with
- Complete internalization of the AI Act’s structure and risk classification system
- Ability to map technical system designs directly to AI Act compliance obligations
- Confidence in producing technical documentation that meets Article 11 and Annex V requirements
- Strategic influence in cross-functional AI governance meetings
- Reputation as the go-to implementer for AI Act readiness in high-stakes engagements
The 12 modules (with all 144 chapters)
Module 1. AI Act scope and applicability boundaries
Define which systems and use cases fall under the AI Act’s purview, with emphasis on high-risk AI systems and data pipeline responsibilities.
12 chapters in this module
- Understanding the AI Act geographic reach
- Defining an AI system under Title I
- Exclusions and limited-risk exceptions
- Role of the provider vs deployer
- Sector-specific deviations in finance and healthcare
- Integration with existing data governance roles
- Mapping AI Act scope to pipeline architecture
- When pilot systems trigger compliance
- Third-party model integration risks
- Fine-tuning and post-deployment thresholds
- Handling open-source model dependencies
- Boundary decisions for internal tools
Module 2. Risk classification framework implementation
Apply the AI Act’s four-tier risk model to real-world systems, with decision guides for ambiguous cases.
12 chapters in this module
- Prohibited AI use cases under Annex I
- High-risk criteria from Annex III
- Cumulative risk assessment method
- Temporal thresholds for system classification
- Dynamic reclassification triggers
- Provider self-assessment workflows
- Handling dual-use foundation models
- Downstream application risk inheritance
- Model cards and risk tier alignment
- Documentation for classification decisions
- Internal audit trail standards
- Escalation paths for borderline cases
Module 3. Technical documentation for conformity
Build compliant technical files that meet Article 11 and Annexes IV and V requirements.
12 chapters in this module
- Mandatory content of technical documentation
- System purpose and intended use statements
- Architecture diagrams and data flows
- Training data provenance and curation
- Performance metrics and limitations
- Human oversight mechanisms
- Version control and change logs
- Security and cybersecurity safeguards
- Accuracy and robustness standards
- Post-market monitoring strategy
- Record retention timelines
- Template customization for audits
Module 4. Data governance obligations under the AI Act
Align data processing practices with transparency and bias mitigation mandates.
12 chapters in this module
- Data quality benchmarks for training sets
- Bias detection and correction protocols
- Documentation of data curation steps
- Personal data handling under GDPR crossover
- Data lineage for audit readiness
- Representativeness validation methods
- Anonymization thresholds for sharing
- Data retention and deletion workflows
- Vendor data sourcing compliance
- Public dataset usage policies
- Bias audit frequency standards
- Incident logging for data drift
Module 5. Human oversight and control design
Implement effective human-in-the-loop mechanisms for high-risk systems.
12 chapters in this module
- Defining meaningful human intervention
- Role clarity for oversight personnel
- Timing thresholds for intervention
- Alerting and notification systems
- Override capability design
- Training content for human reviewers
- Accountability for override decisions
- Logging oversight actions
- Simulation testing for oversight paths
- Fallback procedure documentation
- Monitoring oversight fatigue
- Audit evidence for oversight efficacy
Module 6. Transparency and user information standards
Ensure compliance with disclosure and notice requirements for deployers and users.
12 chapters in this module
- User-facing system disclosure rules
- Instructions for use documentation
- Model card publication standards
- API-level transparency measures
- Real-time interaction disclosures
- Multilingual notice delivery
- Accessibility compliance integration
- Trademark and branding disclosures
- Third-party integration notices
- Change notification workflows
- Version update communication
- Public register alignment
Module 7. Conformity assessment procedures
Navigate internal and notified body evaluation pathways based on system classification.
12 chapters in this module
- Self-certification eligibility rules
- Notified body engagement triggers
- Selection criteria for third-party assessors
- Documentation package assembly
- Assessment timeline expectations
- Gap analysis for reapplication
- Remote audit readiness
- Corrective action response protocol
- Certificate maintenance obligations
- Post-market surveillance linkage
- Cross-border recognition challenges
- Internal mock assessment drills
Module 8. Post-market monitoring and incident reporting
Establish systems to track performance, detect drift, and report serious incidents.
12 chapters in this module
- Performance degradation thresholds
- Drift detection monitoring intervals
- Incident logging and classification
- Serious incident reporting timeline
- National authority coordination
- Recall and rollback decision trees
- User feedback integration loop
- Version deprecation process
- Security incident cross-reporting
- API change impact assessment
- Supply chain disruption planning
- Quarterly compliance review cadence
Module 9. Foundation model governance paths
Apply special obligations for general-purpose AI models under Title III.
12 chapters in this module
- Defining a foundation model
- Transparency for pre-trained weights
- Downstream impact mitigation
- Model card content standards
- Weight sharing and redistribution rules
- Computational resource disclosure
- Environmental impact reporting
- Dual-use risk documentation
- Co-design with academic partners
- API access control policies
- Fine-tuning responsibility boundaries
- Open-weight model compliance
Module 10. Compliance integration with engineering workflows
Embed AI Act requirements into SDLC, CI/CD, and MLOps pipelines.
12 chapters in this module
- Pre-commit compliance checks
- Model registry integration
- Automated documentation generation
- Compliance gates in deployment
- Version tagging for audits
- Metadata attachment standards
- CI/CD pipeline logging
- Rollback traceability
- Model performance baselining
- Drift detection automation
- Security scan integration
- Audit trail export functionality
Module 11. Cross-border deployment strategies
Navigate AI Act applicability in multinational deployments and export scenarios.
12 chapters in this module
- Determining EU market exposure
- Export control overlap considerations
- Third-country legal compatibility
- Localization requirements
- Language and jurisdiction mapping
- Data transfer mechanism alignment
- Enforcement jurisdiction clarity
- Liability partitioning design
- Insurance coverage implications
- Distributor compliance obligations
- Reseller training content
- Incident coordination protocols
Module 12. Future-proofing and regulatory horizon scanning
Stay ahead of amendments, delegated acts, and enforcement guidance.
12 chapters in this module
- Monitoring EASA and AI Office updates
- Delegated act anticipation
- National implementation divergence
- Judicial interpretation tracking
- Stakeholder consultation engagement
- Industry working group participation
- Internal training program updates
- Compliance library maintenance
- Benchmarking against peer firms
- Gap analysis for proposed changes
- Scenario planning for new tiers
- Long-term AI governance roadmap
How this maps to your situation
- When scoping a new AI system for EU deployment
- During technical design of high-risk AI components
- Preparing documentation for internal audit
- Leading cross-functional AI governance alignment
Before vs. after
Before
Uncertainty in how technical design choices map to regulatory obligations, leading to reactive compliance efforts and fragmented documentation.
After
Confident, proactive implementation of AI Act-compliant systems with reusable artefacts and structured decision logic.
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 8 hours of focused learning, designed to be completed in short sessions across two weeks.
If nothing changes
Without structured mastery, compliance remains ad hoc, increasing exposure to audit findings, project delays, and erosion of technical authority in governance discussions.
How this compares to the alternatives
Generic AI ethics courses lack regulatory precision; policy-heavy trainings miss implementation depth. This course delivers technical practitioners the exact compliance framework mastery needed to lead real AI Act readiness projects.
Frequently asked
Is this course technical or policy-focused?
It is technical, designed for implementers. It translates legal obligations into engineering decisions and documentation patterns.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this cover post-market monitoring?
Yes. Module 8 details incident reporting, performance tracking, and drift detection systems compliant with Article 26.
$199 one-time. Approximately 8 hours of focused learning, designed to be completed in short sessions across two weeks..
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