The NIST AI Risk Management Framework (AI RMF)
What you'll learn
- Understand the AI RMF structure
- Identify and map AI risks
- Measure AI system performance
- Implement effective risk management
- Enhance transparency and accountability
Requirements
- Basic understanding of AI concepts
- Familiarity with risk management principles
- No specific tools required
- Open to all skill levels
Description
The "NIST AI Risk Management Framework (AI RMF)" course is designed to equip professionals with the knowledge and tools needed to navigate the complexities of AI risk management effectively. This course delves into the NIST AI RMF, providing a thorough understanding of its principles, functions, and practical applications. Students will explore the MAP, MEASURE, and MANAGE functions, learning how to identify, assess, and mitigate AI risks throughout the AI lifecycle.
Participants will gain insights into the importance of trustworthiness in AI systems, covering key characteristics such as validity, reliability, safety, security, resilience, accountability, transparency, explainability, interpretability, privacy enhancement, and fairness. The course emphasizes the need for a holistic approach to AI risk management, integrating these characteristics to develop robust and trustworthy AI solutions.
Through real-world examples and case studies, including HealthAI, students will see the practical application of the AI RMF in various contexts. The course also covers the importance of continual monitoring and improvement, ensuring that AI systems remain aligned with organizational goals and societal values as they evolve.
This course is ideal for AI practitioners, risk managers, data scientists, and organizational leaders who are involved in the development, deployment, or oversight of AI systems. No prior experience with the NIST AI RMF is required, making it accessible to beginners and valuable to seasoned professionals alike. Join us to master the art of AI risk management and ensure the development of safe, reliable, and ethical AI systems.
Who this course is for:
- AI Developers and Engineers: Understand and mitigate AI risks.
- Data Scientists and Analysts: Learn about transparency, fairness, and privacy.
- Project Managers and Team Leads: Integrate risk management in AI workflows.
- Compliance Officers and Legal Professionals: Ensure AI compliance with regulations.
- Business Leaders and Executives: Manage AI risks responsibly and sustainably.
- Researchers and Academics: Study practical AI risk management frameworks.
- IT Professionals: Enhance AI system performance and security.
- Policy Makers and Regulators: Develop informed AI governance policies.
Instructor
PhD in computer science and IT manager with 35 years technical experience in various fields including IT Security, IT Governance, IT Service Management , Software Development, Project Management, Business Analysis and Software Architecture. I hold 80+ IT certifications such as :
ITIL 4 Master, ITIL 3 Expert
ISO 27001 Auditor, ComptIA Security+, GSEC, CEH, ECSA, CISM, CISSP, CISA
PGMP, MSP
PMP, PMI-ACP, Prince2 Practitioner, Praxis, Scrum Master
COBIT 2019 Implementor, COBIT 5 Assessor/Implementer
TOGAF certified
Lean Specialist, VSM Specialist
PMI RMP, ISO 31000 Risk Manager, ISO 22301 Lead Auditor
PMI-PBA, CBAP
Lean Six Sigma Black Belt, ISO 9001 Implementer
Azure Administrator, Azure DevOps Expert, AWS Practitioner
And many more.