IAPP AIGP AI Governance Professional Exam Prep

What you will be able to do

• Explain AI fundamentals and the technology the exam assumes
• Apply responsible AI principles and assess AI impacts
• Navigate AI laws and frameworks including the EU AI Act and NIST AI RMF
• Govern the AI lifecycle from planning through deployment and monitoring
• Implement, measure, and maintain an AI governance programme
• Pass a timed practice exam covering the AIGP domains

What is inside

5 modules, 20 lessons. Each module ends in a graded quiz.

1. 01

   AI Foundations and the Governance Landscape

   Covers the AIGP domain 'Understanding the Foundations of AI Governance'. You will learn the vocabulary the exam assumes, including how artificial intelligence, machine learning, deep learning and generative AI relate to one another, and how a system is actually built from data, training, evaluation and inference. The module then turns to the benefits and harms AI creates, the trustworthy AI characteristics that governance programs are built around, and the roles, stakeholders and drivers that make an AI governance function necessary.

   4 lessons · 15 quiz questions

2. 02

   AI Laws, Standards and Frameworks

   Covers the AIGP domain 'Understanding How Laws, Standards and Frameworks Apply to AI'. You will learn the structure of the EU AI Act, the fragmented United States federal, state and sectoral picture, the global regulatory map, and the way existing privacy, consumer protection, intellectual property and anti-discrimination law already binds AI systems. The module closes with the NIST AI Risk Management Framework, ISO/IEC 42001 and the OECD principles, and shows how to map voluntary frameworks onto hard legal obligations.

   4 lessons · 15 quiz questions

3. 03

   Governing AI Development: Lifecycle, Data and Models

   Covers the AIGP domain on governing the development of AI systems, from lifecycle mapping and stage gates through use case definition, feasibility and go/no-go decisions. You will learn how to govern data sourcing, quality, provenance and consent, and how to make defensible model selection, build versus buy and third party supply chain decisions. Every lesson ties the practice back to the evidence a reviewer, auditor or regulator will ask to see.

   4 lessons · 15 quiz questions

4. 04

   AI Risk, Testing and Documentation

   Covers the assurance half of the AIGP development domain: how to identify and assess AI risk, when an impact assessment is required, and what a defensible one contains. You will learn how bias enters a system, how to choose and run fairness and evaluation tests, and how to secure and harden AI systems against integrity, inference and privacy threats. The module closes on the artifacts that prove all of it happened, from model cards and datasheets to logs, versioning and audit evidence.

   4 lessons · 15 quiz questions

5. 05

   Governing AI Deployment, Use and Monitoring

   Covers the AIGP domain on governing the deployment and ongoing use of AI systems. You will learn how deployment readiness reviews, tiered approval workflows and acceptable use policies control what actually reaches production, and how human oversight, escalation and AI specific incident response keep a live system accountable to the people it affects. The module closes with post-deployment monitoring, drift detection, retirement and the structure of a durable AI governance program.

   4 lessons · 15 quiz questions