IAPP AIGP Certification – Complete Exam Preparation

The Artificial Intelligence Governance Professional (AIGP) certification, offered by the International Association of Privacy Professionals (IAPP), is currently the leading global certification focused on ensuring that Artificial Intelligence is developed and used responsibly, safely, ethically, and in compliance with emerging regulatory standards. As organizations increasingly adopt AI across business and government sectors, there is a growing demand for professionals who understand AI governance frameworks, ethical risk assessment, accountability structures, transparency guidelines, and compliance assurance practices.

This course provides a structured, step-by-step preparation pathway aligned with the IAPP AIGP Body of Knowledge and the Official AIGP Participant Guide (v2.1). Throughout the course, you will learn how AI systems work, where value is created, where risks emerge, and how to design and implement governance programs that ensure AI remains trustworthy, fair, transparent, secure, and aligned with organizational and societal expectations.

AIGP Certification Exam Overview

• Total Questions: Approximately 100 (85 scored + ~15 unscored pilot questions)

• Exam Duration: 165 minutes (2.75 hours)

• Passing Score: 300 (on a 100–500 scaled score)

• Format: Computer-based, scenario-driven multiple-choice

• Test Delivery: Remote online proctoring or Pearson VUE test centers

• Certification Validity: 2 years (continuing education credits required for renewal)

Exam Fee Structure (may vary by region and date)

• IAPP Members: ~USD $649

• Non-Members: ~USD $799

• Retake Fee: ~USD $475 (members) / ~USD $625 (non-members)

Note: Always confirm the latest fees on the official IAPP website before registering.

Knowledge Domains Covered in This Course

1. Foundations of AI Systems

   • Core AI and machine learning concepts, data workflows, and model behavior.

2. AI Governance and Organizational Structures

   • Governance frameworks, accountability roles, oversight mechanisms, and documentation practices.

3. Responsible AI Risk Management

   • Fairness, transparency, privacy risks, bias assessment, auditing frameworks, and risk mitigation techniques.

4. Policies, Controls, and Lifecycle Assurance

   • Policy creation, governance controls, monitoring, reporting, compliance procedures, and continuous improvement models.

How This Course Helps You Succeed

This course breaks down complex concepts into clear, practical learning through:

• Real-world case studies

• Scenario-based decision exercises

• Governance templates and examples

• Exam-style questions with rationales

By the end of this course, you will be fully prepared to confidently sit for the AIGP exam and capable of applying AI governance techniques within real organizational environments.