We provide virtual course about Certified Lead AI Risk Manager. Certified Lead AI Risk Manager is a professional training course designed to equip participants with the knowledge and skills needed to identify, assess, mitigate and manage risks associated with artificial intelligence (AI).
Course description:
The course covers both theoretical frameworks and practical applications, enabling organisations to adopt AI in a responsible, secure and compliant way. AI systems introduce new types of risk - from ethical and fairness concerns to security vulnerabilities and compliance challenges under emerging regulatory regimes.
This course provides a structured approach to AI risk governance based on recognised frameworks such as the NIST AI Risk Management Framework, the EU AI Act and real-world risk scenarios. Participants gain insights into AI risk identification, evaluation and treatment, and learn how to embed risk management practices into organisational processes for sustainable and safe AI adoption.
Course objectives:
Upon successful completion, participants will be able to:
• Understand fundamentals of AI risk and risk management approaches
• Identify and analyse risks such as bias, transparency challenges, ethical concerns and security threats
• Develop and implement mitigation strategies tailored to AI lifecycle risks
• Apply established AI risk governance frameworks to ensure compliance and ethical AI use
• Monitor and report AI risk status and support continual improvement strategies
Course outline:
Module 1 - Introduction to AI risk and governing frameworks:
• Participants are introduced to the fundamentals of AI risk - what it is, why it matters, and how it impacts organisations and decision-making. The session covers leading frameworks such as NIST AI Risk Management and the EU AI Act to provide a solid contextual base.
Module 2 - AI risk identification and analysis:
• This section focuses on identifying risks across the AI lifecycle - from development and deployment to monitoring and decommissioning. Techniques for risk identification, categorisation and prioritisation are explored, helping participants understand how different risks can manifest in practice.
Module 3 - Mitigation strategies and governance:
• Participants learn how to design and implement mitigation strategies that address AI risks effectively. This includes establishing governance mechanisms, defining responsibilities and creating incident response and security controls aligned with organisational needs.
Module 4 - Monitoring, reporting and improvement:
• This part of the course covers how to monitor AI performance and risk controls over time. Participants learn how to report risk findings to stakeholders and integrate processes that support continual improvement of AI risk practices.
Module 5 - Certification exam preparation:
• The course concludes with preparation for the certification exam, reviewing key learnings and providing guidance on what to expect for successful certification.
Target audience:
This course is suitable for professionals responsible for identifying, assessing or managing AI-related risks, including IT and security professionals, data scientists, AI developers, risk and compliance officers, consultants, legal and ethical advisors, and organisational leaders overseeing AI initiatives.
Prerequisites:
• Participants should have a fundamental understanding of AI concepts and a basic knowledge of risk management principles. Familiarity with AI governance frameworks such as the NIST AI Risk Management Framework or the EU AI Act is beneficial but not mandatory.
Language:
• English course material, norwegian speaking instructor
Course material:
The course fee includes printed course documentation and certification test
Certification:
After successfully completing the exam, you can apply for the credentials shown on the table below. You will receive a certificate once you comply with all the requirements related to the selected credential.