AI Risk Manager

• Domain 1: Fundamental principles and concepts of AI risk management
• Domain 2: AI risk identification and assessment
• Domain 3: AI risk measurement
• Domain 4: AI risk mitigation, governance, and incident response
• Domain 5: AI risk monitoring and continual improvement strategies

1. Establishing an AI risk management framework
2. Defining AI risk management objectives and scope
3. Identifying and assessing AI-related risks
4. Developing an AI risk mitigation and response strategy
5. Defining AI risk evaluation and acceptance criteria
6. Supporting compliance with industry frameworks and regulatory requirements
7. Monitoring, reviewing, and continuously improving the AI risk management program

Certification Rules and Policies

• Certification and examination fees are included in the price of the training course.
• Participants will be provided with training course materials containing over 400 pages of information, practical examples, exercises, and quizzes.
• An attestation of course completion worth 31 CPD (Continuing Professional Development) credits will be issued to the participants who have attended the training course.
• Candidates who have completed the training course but failed the exam are eligible to retake the exam once for free within a 12 month period from the initial date of the exam.

Educational Approach

• The training course combines theoretical knowledge with practical applications, using real-world examples to illustrate the identification and mitigation of AI risks.
• The course includes various interactive activities, such as scenario-based exercises and multiple-choice quizzes, designed to deepen understanding of AI risk management principles.
• Participants are encouraged to engage in discussions and collaborate during exercises and quizzes.
• The quizzes are structured similarly to the certification exam, helping participants familiarize themselves with the exam format and key concepts.