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Deeper command of the AI Act compliance architecture

$199.00
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A tailored course, built for your situation

Deeper command of the AI Act compliance architecture

Build auditable AI governance systems with precision using the full scope and intent of the AI Act

$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 data engineer or technical governance specialist working at a cloud-scale data and AI platform company, focused on compliant system design and implementation

Who this is not for

Entry-level practitioners, policy generalists, or non-technical compliance staff who lack hands-on data pipeline or model deployment responsibilities

What you walk away with

  • Interpret AI Act high-risk criteria with technical precision
  • Map requirements directly to data pipeline controls
  • Produce model documentation that satisfies auditor scrutiny
  • Anticipate regulator follow-ups on data provenance and logging
  • Own the technical compliance playbook across AI deployments

The 12 modules (with all 144 chapters)

Module 1. AI Act scope and high-risk triggers
Understand how Article 6 defines high-risk systems and what technical indicators signal classification.
12 chapters in this module
  1. What the AI Act regulates
  2. High-risk system definition
  3. Use cases in scope
  4. Threshold for risk tiering
  5. Examples of non-compliant deployment
  6. Regulatory logic behind classification
  7. How classification affects data design
  8. Pre-classification checklist
  9. When to escalate for legal review
  10. Documentation needed for tier assignment
  11. Common misinterpretations
  12. Framework alignment with NIST AI RMF
Module 2. Obligations for providers and deployers
Clarify responsibilities across roles under Title III and map them to technical roles.
12 chapters in this module
  1. Provider vs deployer duties
  2. Technical accountability boundaries
  3. Shared responsibility model
  4. Evidence required from engineers
  5. Internal audit expectations
  6. Data retention obligations
  7. Versioning and logging mandates
  8. Compliance sign-off workflow
  9. Cross-team coordination points
  10. Model lifecycle oversight
  11. Enforcement authority scope
  12. Penalties for non-compliance
Module 3. Risk-based classification system
Apply the AI Act’s Annex III to evaluate machine learning use cases.
12 chapters in this module
  1. Critical infrastructure risk
  2. Biometrics in public space
  3. Employment and promotion
  4. Education scoring systems
  5. Essential services access
  6. Law enforcement use cases
  7. Real-time monitoring exceptions
  8. Prohibited systems list
  9. Derogations and national security
  10. Temporary derogation process
  11. Internal risk board function
  12. Escalation protocol for borderline cases
Module 4. Transparency and information duties
Implement clear user communication and model disclosure requirements.
12 chapters in this module
  1. User-facing documentation
  2. Model capability disclosure
  3. Limitations notice standards
  4. Chatbot transparency rules
  5. Deepfake labeling mandates
  6. API consumer obligations
  7. Open source exceptions
  8. Third-party integration rules
  9. Version change notifications
  10. Accuracy reporting baseline
  11. Human oversight disclosures
  12. Time-bound exceptions
Module 5. Data governance for training sets
Meet data quality, provenance, and bias mitigation requirements under Article 10.
12 chapters in this module
  1. Training data provenance
  2. Bias assessment timing
  3. Representativeness criteria
  4. Data lineage documentation
  5. Bias mitigation steps
  6. Documentation of data choices
  7. Version-controlled datasets
  8. Annotated data retention
  9. Preprocessing audit trail
  10. Labeling quality assurance
  11. Third-party data sourcing
  12. Data refresh policy
Module 6. Technical documentation for audits
Build robust technical files that survive regulator scrutiny.
12 chapters in this module
  1. Annex IV requirements
  2. System architecture diagramming
  3. Intended use specification
  4. Risk management documentation
  5. Logging and monitoring setup
  6. Accuracy metrics reporting
  7. Version history tracking
  8. Update and rollback plan
  9. Conformity assessment path
  10. Internal review process
  11. External auditor handoff
  12. Living document maintenance
Module 7. Record-keeping and logging
Design logs that fulfill traceability and accountability mandates.
12 chapters in this module
  1. Autogenerated logging rule
  2. Human oversight events
  3. Input and output retention
  4. Model decision logging
  5. System availability logging
  6. Error and failure logging
  7. Security incident logs
  8. Log access controls
  9. Retention period definition
  10. Log format standardization
  11. Audit trail integrity
  12. Exportability for review
Module 8. Fundamental rights impact assessment
Integrate human rights checks into deployment workflows.
12 chapters in this module
  1. Scope of rights assessment
  2. Affected population analysis
  3. Disproportionate impact checks
  4. Consultation requirements
  5. Mitigation plan documentation
  6. Ongoing monitoring plan
  7. Timeline for review
  8. Public access to assessment
  9. Legal advisor coordination
  10. Bias audit integration
  11. Remediation process design
  12. Documentation for regulators
Module 9. Quality management systems
Implement ISO-style oversight for AI compliance workflows.
12 chapters in this module
  1. Internal oversight function
  2. Role of compliance officer
  3. Audit schedule planning
  4. Corrective action process
  5. Training for staff
  6. Documentation control
  7. Change management process
  8. Supplier oversight
  9. Incident reporting
  10. Continuous improvement loop
  11. Policy update workflow
  12. Management review cycle
Module 10. Conformity assessment process
Navigate the steps to declare compliance for high-risk systems.
12 chapters in this module
  1. Internal vs notified body review
  2. Evidence collection
  3. Technical file assembly
  4. Risk management file
  5. Testing documentation
  6. Performance metrics
  7. Post-market monitoring
  8. Declaration of conformity
  9. CE marking rules
  10. National enforcement reach
  11. Voluntary certification paths
  12. Audit trail for sign-off
Module 11. Post-market monitoring
Design feedback loops and updates to maintain compliance.
12 chapters in this module
  1. Performance tracking system
  2. User complaint process
  3. Model drift detection
  4. Retraining triggers
  5. Version update policy
  6. Incident response protocol
  7. Field monitoring tools
  8. Accuracy degradation flag
  9. Feedback loop integration
  10. Reporting to oversight body
  11. Documentation update frequency
  12. Decommissioning process
Module 12. Implementation playbook integration
Adapt the framework to real-world data and AI systems.
12 chapters in this module
  1. Prioritizing use cases
  2. Gap analysis method
  3. Control mapping exercise
  4. Stakeholder alignment
  5. Pilot deployment
  6. Compliance debt tracking
  7. Toolchain integration
  8. Cross-functional handoffs
  9. Metrics for success
  10. Lessons from first rollout
  11. Scaling across teams
  12. Maintaining current awareness

How this maps to your situation

  • When audit readiness is required
  • Before model deployment
  • During compliance gap assessment
  • After regulatory inquiry

Before vs. after

Before
Navigating AI Act requirements through fragmented guidance and incomplete technical mappings
After
Commanding the full compliance architecture with auditable, repeatable 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 3 hours per module, designed for integration with real-time project work.

If nothing changes
Organizations deploying AI without structured compliance face regulatory scrutiny, deployment delays, and reputational exposure.

How this compares to the alternatives

Generic AI governance courses focus on principles; this course delivers actionable compliance architecture grounded in the AI Act’s binding text and real-world audit expectations.

Frequently asked

Is this course technical or policy-focused?
It's designed for technical practitioners who implement systems. Every module connects legal text to data pipeline, model design, and logging requirements.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this cover comparisons with other frameworks?
Yes, including alignment with NIST AI RMF and ISO 42001 where applicable.
$199 one-time. Approximately 3 hours per module, designed for integration with real-time project work..

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
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