Skip to main content
Image coming soon

AIG7720 Mastering ISO 27701 for AI and Machine Learning Engineers

$199.00
Adding to cart… The item has been added

What do you take away from the ISO 27701 for AI and Machine course?

Own privacy compliance artefacts from scoping through audit without supervision Produce regulator-ready documentation for AI model deployments Lead cross-functional privacy implementation in M&A or product launches Reduce rework by applying ISO 27701 controls at the design phase of AI pipelines Become the internal reference for privacy-by-design in machine learning systems.

How does this map to your situation?

AI model deployment in regulated environment M&A due diligence for data systems Product launch with personal data Regulator inquiry preparation.

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.

What does the ISO 27701 for AI and Machine cover on delivery and format?

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 to be completed in parallel with active projects.

How does this compare to the alternatives?

Unlike generic compliance courses, this program focuses specifically on applying ISO 27701 to AI and machine learning systems, with real-world examples and templates that integrate directly into engineering workflows.

What does the ISO 27701 for AI and Machine cover on frequently asked?

Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.

How is the ISO 27701 for AI and Machine delivered?

The ISO 27701 for AI and Machine is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. A certificate of completion is issued by The Art of Service when you finish.

How much does the ISO 27701 for AI and Machine cost?

The ISO 27701 for AI and Machine is $199 as a one time payment. There is no subscription and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: Machine Learning in Chaos Engineering Dataset, Machine Learning Engineering at Scale, Large Tech Firm Machine Learning Engineer Playbook, Machine Learning Engineering for Production Systems.

More answers: what you get with every course, refund policy, all help answers.

A tailored course, built for your situation

Mastering ISO 27701 for AI and Machine Learning Engineers

Build privacy-by-design into AI systems with structured implementation of ISO 27701 requirements

$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 AI engineer in a regulated environment who leads technical compliance integration but lacks formalized privacy framework mastery

Who this is not for

Entry-level developers, non-technical compliance staff, or consultants without hands-on AI system design experience

What you walk away with

  • Own privacy compliance artefacts from scoping through audit without supervision
  • Produce regulator-ready documentation for AI model deployments
  • Lead cross-functional privacy implementation in M&A or product launches
  • Reduce rework by applying ISO 27701 controls at the design phase of AI pipelines
  • Become the internal reference for privacy-by-design in machine learning systems

The 12 modules (with all 144 chapters)

Module 1. Introduction to ISO 27701 in AI Context
Understand how ISO 27701 extends ISO 27001 to privacy controls and why it matters for AI and machine learning systems processing personal data.
12 chapters in this module
  1. What ISO 27701 regulates
  2. Key differences from ISO 27001
  3. Privacy vs data security scope
  4. Applicability to AI systems
  5. Regulatory drivers in US context
  6. Integration with AI lifecycle
  7. Data subject rights mapping
  8. Controller vs processor roles
  9. Privacy by design principle
  10. Documentation expectations
  11. Audit preparation scope
  12. Common misconceptions
Module 2. Data Inventory and Flow Mapping
Build accurate data flow diagrams for AI systems that satisfy ISO 27701 requirements and stand up to regulator scrutiny.
12 chapters in this module
  1. Identifying PII in training data
  2. Third-party data sources
  3. Data labeling pipelines
  4. Model inference inputs
  5. Storage locations mapping
  6. Cross-border data flows
  7. Retention periods by data type
  8. Purpose limitation checks
  9. Automated data discovery tools
  10. Documentation standards
  11. Version control for diagrams
  12. Stakeholder review process
Module 3. Privacy Impact Assessment (PIA) Execution
Conduct thorough PIAs for machine learning projects that preempt regulatory concerns and accelerate approval.
12 chapters in this module
  1. When to trigger a PIA
  2. Scope definition for AI models
  3. Risk assessment methodology
  4. Model bias evaluation
  5. Data minimization checks
  6. Consent mechanisms review
  7. Data subject access testing
  8. Third-party vendor risks
  9. Automated decision-making disclosure
  10. Escalation thresholds
  11. Template customization
  12. Executive summary drafting
Module 4. Controller and Processor Roles Definition
Clarify obligations in AI supply chains and vendor relationships under ISO 27701 and US regulatory expectations.
12 chapters in this module
  1. Determining controller status
  2. Processor contract requirements
  3. Cloud provider responsibilities
  4. Model hosting arrangements
  5. Data labeling vendors
  6. API access controls
  7. Audit rights negotiation
  8. Subprocessor oversight
  9. Breach notification chains
  10. Joint responsibility models
  11. Geographic jurisdiction mapping
  12. Compliance verification process
Module 5. Consent and Legitimate Basis Management
Design AI systems that operate on valid legal bases and enable auditable consent tracking.
12 chapters in this module
  1. Valid legal bases for AI
  2. Consent for training data
  3. Opt-out mechanisms
  4. Public interest claims
  5. Legitimate interest assessments
  6. Data subject rights interfaces
  7. Consent logging systems
  8. Withdrawal handling
  9. Model retraining triggers
  10. Granular consent design
  11. UI disclosure standards
  12. Audit trail generation
Module 6. Data Subject Rights Implementation
Build AI system capabilities that respond to DSARs without compromising model integrity.
12 chapters in this module
  1. Right to access implementation
  2. Right to deletion in ML
  3. Model retraining impact
  4. Anonymization techniques
  5. Data portability formats
  6. Automated response systems
  7. Verification workflows
  8. Exemption logging
  9. Model version rollback
  10. Incident escalation
  11. Third-party coordination
  12. Response timeline tracking
Module 7. Privacy by Design in AI Architecture
Embed privacy controls into AI system design to reduce compliance rework and accelerate deployment.
12 chapters in this module
  1. System boundary definition
  2. Data minimization patterns
  3. Federated learning use
  4. Differential privacy integration
  5. Synthetic data pipelines
  6. On-device processing
  7. Model explainability
  8. Access control layers
  9. Encryption in use
  10. Audit logging design
  11. Bias monitoring
  12. Model drift alerts
Module 8. Vendor and Third-Party Oversight
Manage privacy compliance across AI development partners and cloud providers.
12 chapters in this module
  1. Vendor risk scoring
  2. Processor contract clauses
  3. Security control validation
  4. Audit right enforcement
  5. Subprocessor tracking
  6. Cloud configuration reviews
  7. API security testing
  8. Incident response coordination
  9. Compliance evidence collection
  10. Performance metrics
  11. Exit strategy planning
  12. Contract renewal review
Module 9. Internal Audit and Readiness
Prepare for ISO 27701 audits with checklists and evidence packages tailored to AI environments.
12 chapters in this module
  1. Audit scope definition
  2. Control mapping exercise
  3. Evidence collection plan
  4. AI-specific control gaps
  5. Interview preparation
  6. Documentation audit
  7. System walkthroughs
  8. Remediation tracking
  9. Stakeholder alignment
  10. Gap closure proof
  11. Mock audit execution
  12. Final submission
Module 10. Incident Response and Breach Management
Respond to privacy incidents in AI systems with speed and regulatory precision.
12 chapters in this module
  1. Breach detection in AI
  2. Data leak indicators
  3. Model inversion risks
  4. Response team activation
  5. Regulator notification timeline
  6. Law enforcement coordination
  7. Public statement drafting
  8. Technical containment steps
  9. Evidence preservation
  10. Root cause analysis
  11. Remediation planning
  12. Post-mortem reporting
Module 11. Ongoing Compliance and Monitoring
Maintain ISO 27701 compliance in production AI systems with automated controls.
12 chapters in this module
  1. Control review frequency
  2. Automated policy checks
  3. Data usage monitoring
  4. Model performance audit
  5. Bias detection alerts
  6. Access review cycles
  7. Policy update process
  8. Training refresh schedule
  9. Third-party reassessment
  10. Compliance dashboard
  11. Executive reporting
  12. Continuous improvement
Module 12. Certification and External Audit
Navigate the ISO 27701 certification process with confidence and minimal disruption.
12 chapters in this module
  1. Choosing a certification body
  2. Pre-certification review
  3. Stage 1 audit prep
  4. Evidence delivery
  5. Interview readiness
  6. Non-conformance response
  7. Stage 2 audit flow
  8. Corrective action tracking
  9. Certification maintenance
  10. Surveillance audit schedule
  11. Scope expansion
  12. Public disclosure

How this maps to your situation

  • AI model deployment in regulated environment
  • M&A due diligence for data systems
  • Product launch with personal data
  • Regulator inquiry preparation

Before vs. after

Before
Privacy compliance is reactive, fragmented across teams, and dependent on external reviewers
After
You lead privacy implementation end to end, produce regulator-ready artefacts, and own escalations from peer teams

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 to be completed in parallel with active projects.

How this compares to the alternatives

Unlike generic compliance courses, this program focuses specifically on applying ISO 27701 to AI and machine learning systems, with real-world examples and templates that integrate directly into engineering workflows.

Frequently asked

Is this course relevant for engineers outside the EU?
Yes. ISO 27701 is a global standard increasingly adopted in US-based firms for AI governance and M&A due diligence.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help with actual certification?
Yes. The course includes a full certification readiness pathway with evidence checklists and audit response templates.
$199 one-time. Approximately 3 hours per module, designed to be completed in parallel with active projects..

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
!