Practical AI governance Workshop
RCCE students will learn the governance, oversight, and management of artificial intelligence systems within organizations, covering AI risk assessment, ethical AI frameworks, model accountability, bias detection and mitigation, and AI regulatory compliance. RCCE students will learn to establish AI governance committees, define acceptable AI use policies, implement model risk management processes, conduct AI impact assessments, monitor AI system behavior for drift and unintended outcomes, comply with emerging AI regulations, and respond to incidents where AI systems produce harmful or unexpected results. This practice-intensive course emphasizes applied skills through lab exercises, real-world scenarios, and production-realistic workflows. Starting from foundational concepts, RCCE students will learn by doing, building muscle memory and practical confidence through repeated hands-on engagement. Students complete exercises that mirror actual workplace tasks, ensuring skills transfer directly to their professional roles.
- Security Engineers building defensive controls
- Security Analysts and Blue Team members
- Systems Administrators with security responsibilities
- GRC and Risk Professionals supporting controls
- Professionals implementing Practical AI governance Workshop
- Execute hands-on tasks for governance, oversight & management of ai systems
- Execute hands-on tasks for why it matters — covering Prevents reputational and legal harm.
- Execute hands-on tasks for executive leadership
- Execute hands-on tasks for legal & compliance — covering Sets AI strategy and risk appetite.
- Execute hands-on tasks for engineering & data science — covering Monitors regulatory landscape.
- Execute hands-on tasks for nist ai rmf — covering Four functions: Govern, Map, Measure,.
- Execute hands-on tasks for iso/iec 42001 — covering AI management system standard.
- Execute hands-on tasks for eu ai act — covering Risk-based regulatory framework.
- Execute hands-on tasks for ieee 7000 series — covering Ethical design methodology.
- Execute hands-on tasks for nist ai risk management framework
- Execute hands-on tasks for review board
- Execute hands-on tasks for compliance team
| Module 01 | Governance, Oversight & Management of AI Systems |
| Module 02 | Why It Matters |
| Module 03 | Executive Leadership |
| Module 04 | Legal & Compliance |
| Module 05 | Engineering & Data Science |
| Module 06 | NIST AI RMF |
| Module 07 | ISO/IEC 42001 |
| Module 08 | EU AI Act |
| Module 09 | IEEE 7000 Series |
| Module 10 | NIST AI Risk Management Framework |
| Module 11 | Review Board |
| Module 12 | Compliance Team |
| Module 13 | Committee Composition |
| Module 14 | Escalation path for AI incidents |
All hands-on labs run on Rocheston Rose X OS. Students practice practical ai governance workshop by implementing the controls discussed in class, with a focus on real-world deployment, monitoring, and validation.
- Lab 1: Execute hands-on tasks for governance, oversight & management of ai systems
- Lab 2: Execute hands-on tasks for why it matters
- Lab 3: Execute hands-on tasks for executive leadership
- Lab 4: Execute hands-on tasks for legal & compliance
- Lab 5: Execute hands-on tasks for engineering & data science
Upon successful completion of this course, students will receive an official RCCE Course Completion Certificate for Practical AI governance Workshop, verifiable through the Rocheston certification portal.
- Full access to all course materials and slide decks
- Hands-on lab access on Rocheston Rose X OS environment
- Access to Rocheston CyberNotes
- Access to Rocheston Zelfire — EDR/XDR SIEM platform
- Access to Rocheston Raven — online cyber range exercise platform
- Access to Rocheston Vulnerability Vines AI