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612-51 Exam Topics and Domains
612-51 is organized into 11 weighted domains. Expect to work with Anthropic Claude, Apache Airflow, AWS SageMaker, Azure AI, and more.
AI Foundations and Technology Ecosystem
Core Principles, Evolution, and Components of AI
Understand core principles, evolution, and components of AI
Real-World AI Applications Across Industries
Apply real-world AI applications across industries
AI Project Life Cycle, MLOps, and DataOps
Apply AI project life cycle, MLOps, and DataOps
AI Technology Stack, Infrastructure, and Deployment Models
Apply AI technology stack, infrastructure, and deployment models
AI Concerns, Ethical Principles, and Responsible AI
Key Ethical, Societal, Privacy, and Security Concerns in AI
Understand key ethical, societal, privacy, and security concerns in AI
Fundamental AI Ethics Principles and Global Standards
Understand fundamental AI ethics principles and global standards
Responsible AI Usage Practices
Apply Responsible AI usage practices for safe and accountable AI
Responsible AI Development Life Cycle and Governance Integration
Apply Responsible AI development life cycle and governance integration
AI Strategy and Planning
AI Vision and Organizational Readiness
Set an AI vision and assess organizational readiness
Use Case Prioritization and AI Roadmap Development
Prioritize use-case and develop an AI roadmap
Data, Technology, and Infrastructure Modernization
Modernize data, technology, and infrastructure
AI Pilots, Scaling, Culture, and Performance Management
Manage AI pilots, scaling strategies, culture, and performance
AI Governance and Frameworks
AI Governance Concepts, Operating Models, and Roles
Understand AI governance concepts, operating models, and roles
AI Governance Policies, Decision Rights, and Controls
Define AI governance policies, decision rights, and controls
Global AI Governance Frameworks and Life Cycle Governance
Apply global AI governance frameworks and life cycle governance
AI Asset Management, Documentation, Human Oversight, and Tooling
Manage AI asset management, documentation, human oversight, and tooling
AI Regulatory Compliance
Global and Sector-Specific AI Regulatory Requirements
Understand global and sector-specific AI regulatory requirements
Accountability, Liability, and User Rights in AI Systems
Understand accountability, liability, and user rights in AI systems
Operational Compliance, Reporting, and Audit Readiness
Apply operational compliance, reporting, and audit readiness
Continuous Compliance Monitoring and Legal Risk Management
Implement continuous compliance monitoring and legal risk management
AI Risk and Threat Management
AI Threat Landscape, Vulnerabilities, and Adversarial Attacks
Understand AI threat landscape, vulnerabilities, and adversarial attacks
AI Risk Identification, Assessment, and Prioritization
Apply AI risk identification, assessment, and prioritization methods
AI Risk Management Frameworks and Standards
Apply AI risk management frameworks and standards
Threat Modeling and Attack Surface Analysis for AI Systems
Conduct threat modeling and attack surface analysis for AI systems
Third-Party AI Risk Management and Supply Chain Security
Third-Party AI Risk Categories and Supply Chain Threats
Understand third-party AI risk categories and supply chain threats
AI Vendor Due Diligence, Evaluation, and Contract Governance
Conduct AI vendor due diligence, evaluation, and contract governance
Regulatory Obligations and Vendor Compliance Requirements
Apply regulatory obligations and vendor compliance requirements
Continuous Vendor Monitoring, Assurance, and Incident Response
Implement continuous vendor monitoring, assurance, and incident response
AI Security Architecture and Controls
AI Security Architecture Principles and Frameworks
Understand AI security architecture principles and frameworks
Secure AI Design Patterns and Defense-in-Depth Strategies
Apply secure AI design patterns and defense-in-depth strategies
Secure Coding, Model Protection, and Deployment Controls
Implement secure coding, model protection, and deployment controls
Runtime Security, API Protection, and Continuous Monitoring
Apply runtime security, API protection, and continuous monitoring
Building Privacy, Trust, and Safety in AI Systems
Privacy-Enhancing Technologies and Data Protection
Understand privacy-enhancing technologies and data protection techniques
AI Privacy Risk Assessment and Mitigation
Apply AI privacy risk assessment and mitigation strategies
Transparency, Explainability, and Trust-Building Mechanisms
Apply transparency, explainability, and trust-building mechanisms
Ethical Design, Fairness Assurance, and Trust Monitoring
Implement ethical design, fairness assurance, and trust monitoring
AI Incident Response and Business Continuity
AI-Focused Incident Response Frameworks and Workflows
Understand AI-focused incident response frameworks and workflows
AI Incident Detection, Containment, Recovery, and Reporting
Conduct AI incident detection, containment, recovery, and reporting
AI Business Continuity and Disaster Recovery Planning
Develop AI business continuity and disaster recovery planning
Testing, Simulations, and Continuous Readiness Improvement
Apply testing, simulations, and continuous readiness improvement
AI Assurance, Testing, and Auditing
AI Assurance Principles, Frameworks, and Governance Models
Understand AI assurance principles, frameworks, and governance models
AI Testing Strategies Across Data, Models, and Systems
Apply AI testing strategies across data, models, and systems
Validation, Verification, Bias, Fairness, and Robustness Testing
Conduct validation, verification, bias, fairness, and robustness testing
AI Auditing Methodologies, Evidence Management, and Reporting
Apply AI auditing methodologies, evidence management, and reporting
How do I earn this certification?
Passing 612-51 earns the Certified Responsible AI Governance & Ethics Professional (C|RAGE) certification. It sits in the AI Governance (Govern pillar of ADG framework) track.
- AI Governance Professional (AIGP) Privacy-focused AI governance certification from the International Association of Privacy Professionals
- ISO/IEC 42001 Lead Implementer Specific focus on implementing the AI Management System standard
- IEEE CertifAIEd Professional Certification IEEE-backed certification for responsible AI system design
Practice with Precision
The PlanetCert Simulator mirrors the real exam environment with authentic questions and timed pressure.
How to study for this exam?
The most effective way to prepare for 612-51 is by using the PlanetCert Simulator to practice questions and review detailed explanations.
Who should take this exam?
- 3 years of cybersecurity experience (per training prerequisite)
- Minimum 2 years work experience in InfoSec domain (per exam eligibility)
- Attendance at official EC-Council CRAGE training (alternative to experience requirement)