Certified AI Trust and Risk Manager (C-AITRM) Certification Program by Tonex
The Certified AI Trust and Risk Manager (C-AITRM) Certification Program by Tonex equips professionals with the expertise to lead AI trust management initiatives. This program addresses the critical need to evaluate and mitigate risks across security, ethics, compliance, performance, and resilience dimensions in AI systems. Participants gain skills in aligning AI practices with global standards while ensuring robust, trustworthy deployment.
The course delves into LLM risk management, trustworthiness metrics, and regulatory compliance frameworks, fostering a holistic understanding of AI risks and mitigation. Special emphasis is placed on cybersecurity, helping professionals identify vulnerabilities in AI-driven systems and implement strategies to protect organizational assets. This ensures that deployed AI systems not only deliver value but also maintain resilience against cyber threats and ethical pitfalls.
Learning Objectives:
- Understand the foundations of AI trust management.
- Identify and mitigate risks in AI and LLM systems.
- Apply qualitative and quantitative risk scoring methods.
- Develop trustworthiness metrics for AI evaluation.
- Align AI risk management practices with NIST AI RMF.
- Navigate international AI standards and regulations.
Target Audience:
- Cybersecurity professionals
- Compliance managers
- AI program managers
- Risk officers
- Legal engineers
Program Modules:
Module 1: OWASP Top 10 for LLM Risk Integration
- Introduction to OWASP AI/LLM risks
- Data privacy concerns in LLMs
- Model inversion and prompt injection attacks
- Mitigating adversarial inputs
- Supply chain and dependency risks
- Secure development practices for LLMs
Module 2: AI Risk Scoring Systems (Qualitative, Quantitative)
- Fundamentals of risk scoring
- Qualitative vs. quantitative methods
- Developing scoring frameworks
- Incorporating impact and likelihood
- Case studies of AI risk scoring
- Reporting and communicating scores
Module 3: Trustworthiness Metrics: Accuracy, Robustness, Safety, Bias, Explainability
- Measuring model accuracy and reliability
- Evaluating robustness under stress
- Ensuring operational safety
- Detecting and mitigating bias
- Explainability and transparency tools
- Combining metrics for trust evaluation
Module 4: Creating a Risk Register for LLM Systems
- Purpose and structure of a risk register
- Identifying risk events and owners
- Categorizing risks across dimensions
- Tracking mitigations and status
- Updating and reviewing regularly
- Example registers and templates
Module 5: NIST AI RMF Alignment: Map, Measure, Manage, Govern
- Overview of NIST AI RMF
- Mapping organizational context
- Measuring AI risks effectively
- Managing risks across lifecycle
- Governance principles and practices
- Practical implementation steps
Module 6: Crosswalk: ISO/IEC 42001, EU AI Act, U.S. Executive Orders
- Understanding ISO/IEC 42001 for AI
- Key provisions of the EU AI Act
- S. Executive Orders on AI policy
- Comparative analysis of regulations
- Harmonizing compliance efforts
- Staying ahead of regulatory changes
Exam Domains:
- Principles of AI Trust and Risk Management
- Governance and Policy in AI Systems
- Ethical, Legal, and Social Implications of AI
- Resilience and Continuity Planning for AI
- AI Security and Cyber Threat Mitigation
- Risk Communication and Decision Support
Course Delivery
The course is delivered through a combination of lectures, interactive discussions, and project-based learning, facilitated by experts in AI trust and risk management. Participants will have access to online resources, including readings, case studies, and tools for practical exercises.
Assessment and Certification
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Certified AI Trust and Risk Manager (C-AITRM).
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified AI Trust and Risk Manager (C-AITRM) Certification Training exam, candidates must achieve a score of 70% or higher.
Take charge of building trustworthy AI systems. Enroll today and gain the skills to manage AI risks effectively while safeguarding your organization from cyber and compliance threats.