A tailored course, built for your situation
Faster path from policy intent to working ISO 42001 implementation
A 12-module sprint to turn AI governance intent into working artefacts in days, not months, tailored for data engineers leading internal AI rollout
The situation this course is for
Governance work often stalls between mandate and execution, teams collect requirements for months, revise drafts endlessly, and still deliver late. This erodes trust and pushes decisions to consultants.
Who this is for
Senior Data Engineer in a regulated enterprise, embedded in data platform teams, often first to implement governance controls at the schema or pipeline level
Who this is not for
Beginners in data engineering, consultants selling governance as a service, executives seeking board-level summaries
What you walk away with
- Produce a working Statement of Applicability in under 5 days
- Map ISO 42001 controls directly to data pipeline logic
- Turn policy drafts into deployment-ready configuration templates
- Reduce review cycles by delivering auditor-ready artefacts upfront
- Become the go-to practitioner for rapid governance prototyping
The 12 modules (with all 144 chapters)
- What ISO 42001 requires
- Data-tier boundaries
- Exclusions with justification
- Scope statement template
- Review cycle timing
- Stakeholder alignment
- Version control approach
- Cross-team visibility
- Change trigger criteria
- Documentation format
- Approval workflow
- Sign-off sequence
- Policy line breakdown
- Control mapping method
- Data flow alignment
- Owner assignment logic
- Tooling compatibility
- Automation feasibility
- Review frequency setting
- Exception handling
- Version control sync
- Testing integration
- Rollback procedure
- Status reporting
- Clause-by-clause review
- Applicability criteria
- Exclusion justification
- Implementation evidence
- Owner naming
- Integration with PL/SQL
- Version tagging
- Audit trail setup
- Cross-reference format
- Update triggers
- Review calendar
- Approval tracking
- Pipeline ingestion points
- Schema ownership
- Access control sync
- Logging integration
- Retention rules
- Masking logic
- Validation hooks
- Error handling
- Metadata tagging
- Version lineage
- Dependency mapping
- Reprocessing logic
- Log schema design
- Permission snapshot timing
- Change detection
- Retention automation
- Report formatting
- Delivery mechanism
- Access control
- Timestamp sync
- Storage path
- Naming convention
- Versioning rule
- Audit handoff
- Risk criteria definition
- Data classification
- Impact scoring
- Likelihood assessment
- Control alignment
- Mitigation tagging
- Exception workflow
- Review cycle
- Stakeholder input
- Documentation format
- Update triggers
- Sign-off process
- Git integration
- Branch strategy
- PR review rules
- Testing environment
- Merge criteria
- Deployment schedule
- Rollback triggers
- Change logging
- Notification setup
- Stakeholder alignment
- Approval workflow
- Post-deploy validation
- Stakeholder mapping
- Meeting rhythm
- Decision log
- Feedback integration
- Escalation path
- Documentation sharing
- Change notification
- Timeline alignment
- Priority tagging
- Conflict resolution
- Approval tracking
- Status reporting
- Document checklist
- Narrative structure
- Evidence pairing
- Version control
- Access protocol
- Redaction rules
- Response templates
- Escalation path
- Timeline alignment
- Review cycle
- Update triggers
- Sign-off process
- Sprint planning
- Task breakdown
- Owner assignment
- Progress tracking
- Review meeting
- Documentation update
- Risk tagging
- Exception handling
- Stakeholder update
- Version control
- Approval workflow
- Retrospective
- Change detection
- Trigger criteria
- Review scope
- Update process
- Stakeholder input
- Documentation sync
- Version history
- Audit trail
- Approval workflow
- Rollout plan
- Testing protocol
- Status reporting
- Pattern extraction
- Template packaging
- Adoption incentives
- Training materials
- Feedback loop
- Version control
- Support model
- Documentation hub
- Change management
- Success metrics
- Lessons learned
- Improvement cycle
How this maps to your situation
- When the AI governance team issues a new policy draft
- Before the quarterly compliance audit begins
- After a data platform upgrade or migration
- When onboarding a new data engineering team
Before vs. after
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 1.5 hours per module , designed to fit within existing sprint cycles.
How this compares to the alternatives
Generic ISO 42001 courses teach theory; this course delivers data-engineering-specific templates, version-controlled workflows, and automation scripts you can deploy the same week.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.