A tailored course, built for your situation
Mastering NIST CSF for Data Science and Gen AI Leaders
Build authority in AI governance frameworks with structured, cross-functional implementation skills
$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.
Falling behind on AI governance consistency across teams
The situation this course is for
AI projects stall when governance isn't consistently applied, leading to rework, compliance gaps, and lost trust from security and audit teams
Who this is for
Senior technical leader driving AI strategy and implementation in regulated or global tech environments
Who this is not for
Individual contributors not involved in AI governance, system design, or cross-team coordination
What you walk away with
- Translate NIST CSF controls into actionable AI system safeguards
- Align AI engineering teams across regions on common governance baselines
- Produce auditable documentation packages for AI deployments
- Lead AI governance rollouts without waiting for central compliance teams
- Demonstrate compliance readiness to internal and external assessors
The 12 modules (with all 144 chapters)
Module 1. NIST CSF Core Structure for AI Systems
Break down the NIST Cybersecurity Framework into components relevant to AI development lifecycle and data pipelines
12 chapters in this module
- Understanding the five functions
- Mapping Identify to AI asset inventory
- Apply Protect to model access controls
- Detect anomalies in training data
- Respond to model drift events
- Recover from compromised AI outputs
- Organize controls by AI layer
- Classify risk severity levels
- Document control ownership
- Link to data lineage systems
- Integrate with MLOps tools
- Customize for semiconductor use cases
Module 2. Governance Integration Across Business Units
Coordinate AI governance practices across data, engineering, security, and compliance teams using NIST CSF
12 chapters in this module
- Align data science with InfoSec
- Engage compliance early in design
- Build cross-functional playbooks
- Assign role-based responsibilities
- Track implementation progress
- Standardize reporting formats
- Conduct joint control reviews
- Resolve conflicting priorities
- Integrate with enterprise risk
- Scale frameworks across regions
- Manage third-party AI vendors
- Document global consistency
Module 3. AI-Specific Control Mapping
Adapt NIST CSF controls to address AI-specific risks like bias, drift, explainability, and data poisoning
12 chapters in this module
- Identify model training risks
- Protect against adversarial attacks
- Detect data distribution shifts
- Respond to fairness violations
- Recover from corrupted models
- Map controls to AI lifecycle
- Define monitoring baselines
- Set thresholds for alerts
- Document model decisions
- Enforce version governance
- Track model lineage
- Audit access to model endpoints
Module 4. Implementation Roadmap for Global Rollout
Deploy NIST CSF-aligned AI governance across multiple regions and business units with phased consistency
12 chapters in this module
- Assess current AI maturity
- Prioritize high-risk use cases
- Define regional rollout paths
- Localize control interpretations
- Train regional champions
- Establish feedback loops
- Monitor adoption metrics
- Adjust for cultural differences
- Align with legal requirements
- Report progress to leadership
- Maintain global standards
- Update controls quarterly
Module 5. Documentation and Audit Readiness
Create clear, defensible documentation packages for internal and external audits of AI systems
12 chapters in this module
- Structure SoA for AI systems
- Write control justifications
- Gather evidence systematically
- Use templates for efficiency
- Version documentation assets
- Link controls to frameworks
- Prepare for regulator queries
- Respond to auditor findings
- Automate evidence collection
- Store records securely
- Demonstrate continuous improvement
- Archive outdated versions
Module 6. Cross-Team Communication Strategies
Communicate NIST CSF requirements effectively to non-security teams involved in AI development
12 chapters in this module
- Translate security jargon
- Tailor messages by role
- Run effective workshops
- Create visual aids
- Develop FAQs for engineers
- Host office hours
- Distribute progress updates
- Gather feedback iteratively
- Clarify ownership boundaries
- Resolve cross-team conflicts
- Celebrate milestones
- Sustain engagement over time
Module 7. Control Automation in MLOps Pipelines
Embed NIST CSF controls directly into CI/CD and model deployment workflows
12 chapters in this module
- Integrate with Databricks
- Connect to Snowflake
- Use API guardrails
- Enforce model signing
- Scan for vulnerabilities
- Validate data quality
- Monitor inference patterns
- Log control events
- Trigger automated responses
- Pause deployments on failure
- Notify security teams
- Maintain audit trails
Module 8. Risk Assessment for AI Projects
Apply NIST CSF to conduct thorough, repeatable risk assessments for new and existing AI systems
12 chapters in this module
- Define risk criteria
- Classify AI use cases
- Assess data sensitivity
- Evaluate model impact
- Score technical risks
- Identify control gaps
- Prioritize mitigations
- Document decisions
- Review with stakeholders
- Update assessments regularly
- Track remediation status
- Report to leadership
Module 9. Vendor and Third-Party Management
Extend NIST CSF governance to external AI providers, models, and data sources
12 chapters in this module
- Assess vendor security
- Review model documentation
- Audit third-party code
- Negotiate SLAs
- Enforce data usage terms
- Monitor model performance
- Verify compliance claims
- Conduct on-site reviews
- Manage API risks
- Terminate non-compliant vendors
- Build exit strategies
- Maintain oversight logs
Module 10. Incident Response Planning for AI
Prepare response protocols for AI-related incidents using NIST CSF Respond and Recover functions
12 chapters in this module
- Define incident types
- Establish detection criteria
- Activate response teams
- Contain model outputs
- Investigate root causes
- Notify affected parties
- Restore model integrity
- Update monitoring rules
- Document lessons learned
- Revise playbooks
- Report to legal
- Communicate externally
Module 11. Continuous Monitoring and Improvement
Maintain and evolve AI governance practices using NIST CSF metrics and feedback loops
12 chapters in this module
- Define KPIs for AI governance
- Track control effectiveness
- Measure team adoption
- Gather user feedback
- Run control audits
- Update policies regularly
- Benchmark against peers
- Adjust for technology changes
- Incorporate lessons learned
- Optimize workflows
- Reduce manual effort
- Demonstrate ROI
Module 12. Executive Communication and Leadership
Present AI governance progress and risks to senior leaders using NIST CSF as a common language
12 chapters in this module
- Summarize risk posture
- Highlight key metrics
- Explain control gaps
- Propose investment areas
- Align with business goals
- Track compliance status
- Report incident trends
- Show improvement over time
- Frame decisions strategically
- Use visual dashboards
- Anticipate executive questions
- Lead governance evolution
How this maps to your situation
- Adopting AI at scale across global teams
- Ensuring compliance in regulated markets
- Reducing rework from inconsistent governance
- Gaining recognition as a trusted AI leader
Before vs. after
Before
AI governance varies by team, leading to inconsistency, audit findings, and slow scaling
After
Consistent, documented governance applied across regions and functions, enabling faster, trusted deployment
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters total)
- 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 week over 12 weeks to complete all modules and apply templates
If nothing changes
Without structured governance, AI initiatives risk non-compliance, security gaps, and loss of leadership trust
How this compares to the alternatives
Unlike generic cybersecurity courses, this program focuses specifically on applying NIST CSF to AI systems in global tech organizations
Frequently asked
Is this course focused on NIST CSF or AI governance?
It integrates both, teaching how to apply NIST CSF specifically to AI systems and data pipelines
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me lead AI governance across regions?
Yes, each module includes strategies for aligning teams across geographies and business units
$199 one-time. Approximately 3 hours per week over 12 weeks to complete all modules and apply 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