A tailored course, built for your situation
Mastering ISO 27701 for Data Science Practitioners in Compliance Functions
A step-by-step implementation guide to embedding privacy by design in data workflows
$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.
Most data scientists are expected to comply with privacy standards but aren't given the tools to own them.
Who this is for
Senior data practitioner in a compliance-sensitive function, often with advisory or audit-adjacent experience, now expected to operationalize privacy standards without formal training in them.
Who this is not for
Entry-level analysts, pure software developers without data governance exposure, or executives seeking board-level summaries.
What you walk away with
- Confidently lead ISO 27701 implementation within data lifecycle projects
- Document privacy controls that satisfy internal and external audits
- Position yourself as the ownership point for privacy architecture in data initiatives
- Reduce rework by integrating compliance into design sprints, not retrofits
- Deliver data products with built-in auditability and traceability
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 27701 in the Context of Data Science
Ground your work in the actual clauses of ISO 27701 as they apply to data processing activities, identifying where your current workflows already align and where gaps exist.
12 chapters in this module
- Mapping data flows to ISO 27701 Annex A controls
- Differentiating PII from non-PII in structured datasets
- Role of the data processor under ISO 27701 Section 5
- How GDPR and CCPA interpretations shape control design
- Linking privacy principles to data pipeline stages
- Scope definition for data science projects under audit
- Documenting lawful basis for processing in model training
- Privacy threshold assessments for algorithmic outputs
- Boundary setting between model development and deployment
- Control ownership in shared data environments
- Crosswalk between ISO 27701 and internal data policies
- Establishing evidence trails for retrospective review
Module 2. Data Inventory and Mapping to Privacy Controls
Build a systematic approach to cataloging data assets with privacy attributes that feed directly into compliance documentation.
12 chapters in this module
- Identifying data sources containing personal information
- Classifying data sensitivity levels by jurisdiction
- Creating data flow diagrams for audit readiness
- Documenting third-party data sharing touchpoints
- Versioning data inventories for change tracking
- Linking datasets to data protection impact assessments
- Automating discovery in cloud-based data lakes
- Tagging fields for pseudonymization requirements
- Ownership assignment for dataset lifecycle
- Retention rules aligned with privacy notices
- Mapping data fields to ISO 27701 control 8.2
- Integrating DLP signals into control mapping
Module 3. Privacy by Design in Model Development
Embed privacy controls directly into the data science workflow, from feature engineering to model deployment.
12 chapters in this module
- Integrating privacy checks into CI/CD pipelines
- Feature selection under data minimization principles
- Bias detection as part of privacy risk assessment
- Model explainability requirements in audit contexts
- Data masking strategies for training environments
- Synthetic data use cases under ISO 27701
- Logging data access for accountability trails
- Consent verification in model input layers
- Secure model evaluation with protected data
- Privacy-preserving federated learning patterns
- Documentation templates for model governance
- Audit trail generation for algorithmic decisions
Module 4. Implementing Data Subject Rights in Data Systems
Design data architectures that enable fulfillment of access, rectification, and erasure requests without disrupting analysis workflows.
12 chapters in this module
- Right to access workflows in distributed data stores
- Data erasure validation in replicated environments
- Rectification processes across data marts
- Automated DSAR handling in data pipelines
- Consent withdrawal propagation mechanisms
- Data portability formatting for external requests
- Anonymization thresholds for data retention
- Logging data subject interactions for compliance
- Escalation paths for complex DSARs
- Response time tracking for regulatory reporting
- Integrating DSAR logs with service desk tools
- Privacy incident tagging in service requests
Module 5. Vendor and Third-Party Risk in Data Ecosystems
Assess and document vendor compliance with ISO 27701 when third parties process personal data within your data supply chain.
12 chapters in this module
- Evaluating vendor privacy controls in procurement
- Data processing agreements with cloud providers
- Third-party audit evidence collection methods
- Subprocessor oversight in SaaS platforms
- Incident response coordination with vendors
- Data sovereignty implications in vendor selection
- Vendor risk scoring for privacy maturity
- Right to audit clauses in contract templates
- Vendor data mapping for central reporting
- Privacy control mapping for API integrations
- Continuous monitoring of vendor compliance
- Exit planning for data return and deletion
Module 6. Internal Audit Preparation and Evidence Collection
Produce audit-ready documentation that demonstrates compliance with ISO 27701 controls specific to data science environments.
12 chapters in this module
- Preparing evidence packs for control 7.2
- Documenting access reviews for model repositories
- User access logging in Jupyter and Databricks
- Versioned privacy documentation for review cycles
- Change control logs for data pipeline updates
- Security testing reports for data APIs
- Data classification tagging in metadata
- Retention policy enforcement proof points
- Incident response testing documentation
- Privacy training completion tracking
- Internal review workflows for PIAs
- Audit trail generation for data exports
Module 7. Building a Data Protection Management Program
Establish a living compliance framework that evolves with data initiatives and regulatory expectations.
12 chapters in this module
- Developing a privacy governance charter
- Assigning roles in data protection leadership
- Integrating privacy into sprint planning
- Privacy KPIs for data team performance
- Cross-functional privacy working groups
- Budgeting for privacy tooling and training
- Privacy maturity self-assessments
- Roadmap development for control enhancements
- Regulatory horizon scanning for updates
- Stakeholder communication plans
- Privacy reporting cadence for leadership
- Documentation sustainability across team changes
Module 8. Data Breach Response and Notification Procedures
Prepare response plans that meet ISO 27701 requirements for personal data breaches involving data science systems.
12 chapters in this module
- Breach identification in model output logs
- Escalation protocols for unauthorized data access
- Containment strategies for compromised datasets
- Forensic data collection from ML environments
- Notification timelines under GDPR and state laws
- Documentation of breach root cause analysis
- Legal counsel coordination in incident response
- Customer communication templates for breaches
- Regulator reporting requirements by jurisdiction
- Post-breach control enhancement planning
- Simulation exercises for breach scenarios
- Lessons learned integration into data policies
Module 9. Training and Awareness for Data Teams
Create role-specific privacy training that sticks, tailored to data scientists, engineers, and analysts.
12 chapters in this module
- Privacy principles for machine learning teams
- Data handling simulations for new hires
- Annual training completion tracking
- Privacy quiz design for knowledge retention
- Role-based access training modules
- PIA documentation walkthroughs
- Incident response role-playing
- Vendor privacy onboarding content
- Microlearning for control updates
- Leadership messaging on privacy culture
- Privacy champion programs in data teams
- Feedback loops for training improvement
Module 10. Continuous Monitoring and Improvement
Implement systems to track compliance over time and adapt to changing data and regulatory environments.
12 chapters in this module
- Automated control validation in data pipelines
- Privacy metric dashboards for leadership
- Quarterly control review workflows
- Change detection in data sharing patterns
- Anomaly alerting for PII access spikes
- Remediation tracking for audit findings
- Privacy debt identification in sprints
- Control effectiveness scorecards
- Benchmarking against peer organizations
- Privacy sprint retrospectives
- Feedback integration from DSARs
- Regulatory update impact assessments
Module 11. Global Data Transfer Compliance
Navigate cross-border data flows in data science projects with documented compliance to ISO 27701 and regional laws.
12 chapters in this module
- Mapping data residency requirements
- Standard contractual clauses for cloud vendors
- Adequacy decision tracking by jurisdiction
- Data localization strategies for AI training
- Cross-border model deployment risks
- Data transfer impact assessments
- Encryption standards for international transit
- On-premises vs. cloud processing decisions
- Audit trails for international data access
- Vendor compliance with data shield frameworks
- Documentation of data routing logic
- Jurisdiction-specific consent handling
Module 12. Certification Readiness and Gap Remediation
Prepare for formal ISO 27701 certification with targeted remediation and evidence packaging.
12 chapters in this module
- Gap analysis using ISO 27701 control clauses
- Remediation prioritization by risk level
- Evidence collection for external auditors
- Internal audit findings response process
- Documentation version control setup
- Certification timeline planning
- Stakeholder coordination for audit week
- Auditor Q&A preparation for data teams
- Post-certification maintenance planning
- Scope expansion strategies for new systems
- Marketing certified compliance appropriately
- Continuous improvement after certification
How this maps to your situation
- Current role transition from advisory to operational ownership
- Need to scale compliance with AI-driven data workloads
- Expanding remit over data governance decisions
- Demonstrating leadership in privacy implementation
Before vs. after
Before
Compliance is reactive, fragmented, and dependent on external teams.
After
You own the privacy implementation, lead audits, and shape data governance policy.
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: 90 minutes of focused learning, plus optional deep-dive work with templates.
If nothing changes
Without structured implementation knowledge, privacy compliance remains a bottleneck, delaying releases, increasing audit risk, and limiting your influence in strategic data decisions.
How this compares to the alternatives
Unlike generic compliance courses, this is tailored to data science practitioners who must implement standards, not just understand them. No fluff, no theory, just actionable steps used in real audit preparations.
Frequently asked
Who is this course for?
Data science practitioners in compliance-sensitive roles who are expected to implement privacy standards but lack formal training in them.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this to non-ISO frameworks?
Yes, core patterns map to GDPR, CCPA, and NIST Privacy Framework, but ISO 27701 is the primary implementation anchor.
$199 one-time. 90 minutes of focused learning, plus optional deep-dive work with templates..
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