Certified Responsible AI Governance & Ethics Professional (C|RAGE)

When AI fails, leadership is accountable. C|RAGE certifies professionals who can stand behind AI decisions. Be EN-RAGED by the chaos — lead the mandate for responsible AI governance.

Course Curriculum

Module 01: AI Foundations and Technology Ecosystem

Core principles, evolution, and components of AI
Real-world AI applications across industries
AI project life cycle, MLOps, and DataOps
AI technology stack, infrastructure, and deployment models

Module 02: AI Concerns, Ethical Principles, and Responsible AI

Key ethical, societal, privacy, and security concerns in AI
Fundamental AI ethics principles and global standards
Responsible AI usage practices for safe and accountable AI
Responsible AI development life cycle and governance integration

Module 03: AI Strategy and Planning

Setting AI vision and assessing organizational readiness
Prioritizing use cases and developing an AI roadmap
Modernizing data, technology, and infrastructure
Managing AI pilots, scaling strategies, culture, and performance

Module 04: AI Governance and Frameworks

AI governance concepts, operating models, and roles
Defining AI governance policies, decision rights, and controls
Applying global AI governance frameworks and life cycle governance
AI asset management, documentation, human oversight, and tooling

Module 05: AI Regulatory Compliance

Global and sector-specific AI regulatory requirements
Accountability, liability, and user rights in AI systems
Operational compliance, reporting, and audit readiness
Continuous compliance monitoring and legal risk management

Module 06: AI Risk and Threat Management

AI threat landscape, vulnerabilities, and adversarial attacks
AI risk identification, assessment, and prioritization methods
AI risk management frameworks and standards
Threat modeling and attack surface analysis for AI systems

Module 07: Third-party AI Risk Management and Supply Chain Security

Third-party AI risk categories and supply chain threats
AI vendor due diligence, evaluation, and contract governance
Regulatory obligations and vendor compliance requirements
Continuous vendor monitoring, assurance, and incident response

Module 08: AI Security Architecture and Controls

AI security architecture principles and frameworks
Secure AI design patterns and defense-in-depth strategies
Secure coding, model protection, and deployment controls
Runtime security, API protection, and continuous monitoring

Module 09: Building Privacy, Trust, and Safety in AI Systems

Privacy-enhancing technologies and data protection techniques
AI privacy risk assessment and mitigation strategies
Transparency, explainability, and trust-building mechanisms
Ethical design, fairness assurance, and trust monitoring

Module 10: AI Incident Response and Business Continuity

AI-focused incident response frameworks and workflows
AI incident detection, containment, recovery, and reporting
AI business continuity and disaster recovery planning
Testing, simulations, and continuous readiness improvement

Module 11: AI Assurance, Testing, and Auditing

AI assurance principles, frameworks, and governance models
AI testing strategies across data, models, and systems
Validation, verification, bias, fairness, and robustness testing
AI auditing methodologies, evidence management, and reporting

What You'll Learn

How to build and implement enterprise AI governance frameworks
How to identify, assess, and mitigate AI-specific risks across the life cycle
How to map AI programs to NIST AI RMF, ISO/IEC 42001, and global regulations
How to put ethical, fair, and transparent AI practices into operation
How to lead AI oversight across legal, privacy, security, and risk teams
How to manage third-party AI risk and supply chain security
How to design secure AI architectures and conduct AI testing/auditing
How to build AI incident response and business continuity plans 

Prerequisites

Exam Details

Duration

3 hours

Passing Score

70–80%

Format

100 multiple-choice questions (MCQs)

Delivery Method

ECC Exam Portal

Who Should Take This Course

GRC and risk management leaders (Risk Managers, Heads of GRC/ERM)

Compliance and regulatory professionals (Compliance Managers, Regulatory Affairs Directors)

Privacy and data governance leaders (CPOs, DPOs, Data Governance Managers)

Audit professionals (Internal/Technology Audit Managers)

TrainAI