Isaca Aaia (Advanced In Ai Audit) Certification Mastercalss

Master AI Auditing Concepts, Frameworks & Controls Aligned with ISACA’s AAIA Certification

What you'll learn

Understand the core concepts of AI technologies and their impact on audit and assurance.

Apply risk management principles to assess AI systems across their lifecycle.

Evaluate governance, ethical considerations, and regulatory requirements for AI.

Plan, execute, and report on AI audits using ISACA’s AAIA-aligned methodologies.

Prepare effectively for the AAIA certification exam with real-world examples and practice questions.

Requirements

A basic understanding of audit, risk, or IT governance concepts.

Familiarity with AI or machine learning terminology is helpful but not mandatory.

No prior AI audit experience required—this course is beginner-friendly.

Description

Are you looking to become a Certified Artificial Intelligence Auditor (AAIA)?The AAIA certification, offered by ISACA, is a globally recognized credential that validates your expertise in auditing AI systems for risks, controls, compliance, and ethical governance. As AI adoption accelerates, organizations urgently need professionals who can assess AI solutions with confidence, accountability, and a structured audit approach.This course is based on ISACA’s official AAIA framework and is designed to help you master the audit lifecycle of AI systems efficiently. Through comprehensive modules, real-world examples, and exam-focused guidance, this course serves as a one-stop solution to prepare you for the AAIA exam and your role as an AI auditor.What You’ll Learn:AI Auditing Fundamentals – Grasp core concepts of AI technology, systems, and their implications for audit.AI Risk & Control Frameworks – Learn how to identify, assess, and mitigate AI-specific risks and evaluate controls.Governance, Ethics & Regulation – Understand ethical AI practices, emerging regulatory trends, and governance expectations.Audit Planning & Execution for AI – Master end-to-end audit processes tailored for AI environments—from scoping to reporting.Exam Preparation & Practical Application – Apply your learning through real-life scenarios, sample questions, and actionable tips.Who Should Enroll?This course is ideal for IT auditors, risk professionals, compliance managers, internal auditors, AI specialists, data scientists, and governance consultants looking to audit, assess, or oversee the responsible use of AI.Step confidently into the future of AI assurance. Enroll today to prepare for the ISACA AAIA certification and become a trusted AI audit professional!

Overview

Section 1: AI Models, Considerations and Requirements

Lecture 1 Introduction

Lecture 2 Types of AI

Lecture 3 AI/ML Models

Lecture 4 Alogorithms

Lecture 5 AI Lifecyle

Lecture 6 Business Considerations

Section 2: AI Governance and Program Management

Lecture 7 AI Strategy

Lecture 8 AI Roles & Responsibilities

Lecture 9 AI Related Policies and Procedures

Lecture 10 AI Training Awareness

Lecture 11 Program Metrics

Section 3: AI Risk Management

Lecture 12 Introduction

Lecture 13 Risk Identification

Lecture 14 Risk Assessment

Lecture 15 Risk Monitoring

Section 4: Privacy and Data Governance Programs

Lecture 16 Introduction

Lecture 17 Data Governance

Lecture 18 Privacy Considerations

Section 5: Leading Practices, Ethics and Considerations

Lecture 19 Introduction

Lecture 20 Standards, Frameworks and Regulations

Lecture 21 Ethical Considerations

Section 6: Data Management Specific to AI

Lecture 22 Introduction

Lecture 23 Data Collection

Lecture 24 Data Classification

Lecture 25 Data Confidentiality

Lecture 26 Data Quality

Lecture 27 Data Balancing

Lecture 28 Data Scarcity

Lecture 29 Data Security

Section 7: AI Solution Development Methodologies

Lecture 30 AI Solution Lifecycle

Lecture 31 Privacy and Security by Design

Section 8: Change Management Specific to AI

Lecture 32 Change Management Considerations

Section 9: Supervision of AI Solutions

Lecture 33 AI Agency

Section 10: Testing Techniques for AI Solutions

Lecture 34 Introduction

Lecture 35 Conventional Software Testing Techniques

Lecture 36 AI - specific Testing Techniques

Section 11: Threats and Vulnerabilities Specific to AI

Lecture 37 Introduction

Lecture 38 Types of AI Related Threats

Lecture 39 Controls for AI Related Threats

Section 12: Incodent Response Management Specific to AI

Lecture 40 Introduction

Lecture 41 Prepare

Lecture 42 Identify and Report

Lecture 43 Assess

Lecture 44 Respond

Lecture 45 Post-Incident Review

Section 13: Audit Planning and Design

Lecture 46 Introduction

Lecture 47 Identification of AI Assets

Lecture 48 Types of AI Controls

Lecture 49 AI Audit Use Cases

Lecture 50 Internal Training for AI Use

Section 14: Audit Testing and Sampling Methodologies

Lecture 51 Introduction

Lecture 52 Designing an AI Audit

Lecture 53 AI Adit Testing Methodologies

Lecture 54 AI Sampling

Lecture 55 Testing AI Outcomes

Lecture 56 Sample AI Audit Process

Section 15: Audit Evidence Collection Techniques

Lecture 57 Introduction

Lecture 58 Data Collection

Lecture 59 Walkthroughs and Interviews

Lecture 60 AI Collection Tools

Section 16: Audit Data Quality and Data Analytics

Lecture 61 Introduction

Lecture 62 Data Quality

Lecture 63 Data Analytics

Lecture 64 Data Reporting

Section 17: AI Audit Outputs and Reports

Lecture 65 Introduction

Lecture 66 Reports

Lecture 67 Audit Follow-up

Lecture 68 Quality Assurance

IT auditors, internal auditors, and risk professionals seeking to expand into AI assurance.,Compliance officers and governance specialists responsible for overseeing AI systems.,AI developers, data scientists, and ML engineers who want to understand audit and regulatory expectations.,Professionals preparing for the ISACA AAIA certification to advance their career in AI auditing and assurance.