ISACA AAIA Certification Prep
Welcome to the ultimate free study guide for the ISACA Advanced in AI Audit (AAIA) certification. Every chapter of the syllabus pairs a YouTube video lesson with a concise written summary and an exam-focused FAQ — designed for quick scanning, search and last-minute revision. The 55 episodes below cover all three AAIA exam domains.
New episodes are published on the RooCloud YouTube channel, and you can test yourself with chapter-wise multiple-choice questions and full-length practice exams at RooCloud.com.
The AAIA exam is organised into three domains:
- AI Governance and Risk — Episodes 1–17
- AI Operations — Episodes 18–37
- Auditing AI — Episodes 38–55
📝 Notes + videos are only half the prep
The written notes and video lessons in this guide are designed to be used alongside practice. Reinforce every chapter with chapter-wise MCQs and full-length mock exams at RooCloud.com — read or watch the lesson here, then test your recall and exam-readiness there.
Table of Contents
Domain 1: AI Governance and Risk
- Episode 1: Types of AI Explained: Reactive, Limited Memory, ANI, AGI, ASI
- Episode 2: Machine Learning & AI Models: Supervised, Unsupervised, Reinforcement
- Episode 3: AI Algorithms: Classification, Regression & Clustering
- Episode 4: The AI Life Cycle: All 7 Stages from Plan to Retire
- Episode 5: AI Business Considerations: Use Cases, ROI, Vendors & Hosting
- Episode 6: AI Strategy Explained: Build vs Buy vs Partner & Value Alignment
- Episode 7: AI Roles & Responsibilities: Governance, Build Teams & Oversight
- Episode 8: AI Policies & Procedures: Usage, Development & Deployment
- Episode 9: AI Training & Awareness: Talent, Skills & Competencies
- Episode 10: AI Program Metrics: Performance, Risk & Business Value
- Episode 11: AI Risk Identification: Threat Landscape & Risk Categories
- Episode 12: AI Risk Assessment: Appetite, Tolerance & Remediation
- Episode 13: AI Risk Monitoring & Continuous Improvement
- Episode 14: Data Governance for AI: Classification, Consent & Licensing
- Episode 15: AI Privacy Considerations: GDPR, CCPA & Data Ownership
- Episode 16: AI Standards & Regulations: NIST, ISO, COBIT & EU AI Act
- Episode 17: AI Ethics: Bias, Fairness, Transparency & Human Rights
Domain 2: AI Operations
- Episode 18: AI Data Collection: Consent, Fit for Purpose & Data Lag
- Episode 19: Data Classification for AI: Sensitivity, Tagging & Treatment
- Episode 20: Data Confidentiality in AI: Encryption, Access & Need-to-Know
- Episode 21: AI Data Quality: Accuracy, Completeness, Consistency & Timeliness
- Episode 22: Data Balancing for AI: Oversampling, Undersampling & SMOTE
- Episode 23: Data Scarcity: Augmentation, Transfer Learning & Active Learning
- Episode 24: AI Data Security: Encoding, Access, Backup & Integrity
- Episode 25: AI Solution Development Life Cycle: 7 Stages Explained
- Episode 26: Privacy & Security by Design for AI: Explainability & Robustness
- Episode 27: Change Management for AI Systems: Models, Data & Configuration
- Episode 28: AI Agency: Logging, Observability, HITL & Hallucinations
- Episode 29: Software Testing for AI: A/B, Unit, Integration & Black Box
- Episode 30: AI-Specific Testing: Model Cards, Bias & Adversarial Tests
- Episode 31: AI Threats: Data Poisoning, Prompt Injection & Model Theft
- Episode 32: Controls for AI Threats: Prompt Hardening & Adversarial Testing
- Episode 33: AI Incident Response — Prepare: Policies, IR Team & Tabletops
- Episode 34: AI Incident Response — Identify & Report: Detection & Triage
- Episode 35: AI Incident Response — Assess: Scope, Severity & Response Tier
- Episode 36: AI Incident Response — Respond: Containment, Eradication, Recovery
- Episode 37: AI Post-Incident Review: Lessons Learned & Control Updates
Domain 3: Auditing AI
- Episode 38: Identifying AI Assets: Inventory, Data Gathering & Documentation
- Episode 39: Types of AI Controls: Preventive, Detective & Corrective
- Episode 40: AI Audit Use Cases: LLMs, Generative AI & Process Improvement
- Episode 41: Internal Training for AI Auditors: Knowledge & Practical Skills
- Episode 42: Designing an AI Audit: Objectives, Scoping & Resources
- Episode 43: AI Audit Testing Methodologies: System & Financial Models
- Episode 44: AI Sampling Methods: Statistical vs Judgmental Approaches
- Episode 45: Testing AI Outcomes: False Positives, Outliers & Efficiency
- Episode 46: Sample AI Audit Process: Plan, Execute & Report
- Episode 47: AI Audit Data Collection: Structured, Unstructured, ETL & Scraping
- Episode 48: AI Audit Walkthroughs & Interviews: Design & Evidence Capture
- Episode 49: AI Collection Tools: Log Collection, Voice-to-Text & OCR
- Episode 50: AI Audit Data Quality: Optimization, Dimensions & Validation
- Episode 51: AI Data Analytics: Sentiment, Trend & Anomaly Detection
- Episode 52: AI Audit Data Reporting: Reports & Live Dashboards
- Episode 53: AI Audit Reports: Advisory, Charts, Visualizations & Heat Maps
- Episode 54: AI Audit Follow-up: Tracking, Automation & Verification
- Episode 55: AI Audit Quality Assurance: Methodology, Peer Review & Evidence
This study guide is produced by RooCloud. Watch the full series on YouTube, browse all courses at RooCloud @ GitHub, and practice with chapter-wise MCQs and full-length mock exams at RooCloud.com.