ISACA AAIA Certification Prep
Welcome to the ultimate free study guide for the ISACA Advanced in AI Audit (AAIA) certification. This site pairs every YouTube lesson with a concise written summary and an exam-focused FAQ you can scan, search and revise from. Together the 55 episodes cover the entire AAIA syllabus across its three domains.
Watch the full series on the RooCloud YouTube channel and test yourself with chapter-wise multiple-choice questions and full-length practice exams at RooCloud.com.
The exam is organised into three domains: AI Governance and Risk (Episodes 1–17), AI Operations (Episodes 18–37), and 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.
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.