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AIGP Certification Prep (Latest) with AI Governance Toolkit

Name: AIGP Certification Prep (Latest) with AI Governance Toolkit
Rating: 4.6 (6 reviews)

200+ practice questions, 5 Case Studies, Visual AI Governance Walkthrough Demo, 23 downloadable governance templates

Created byNeha Khandelwal

Last updated 8/2026

English

What you'll learn

See Governance in Action First: Watch a live AI Release Readiness Platform walkthrough — the complete governance workflow, before you study a single concept
Dive into 5 Real-life Case Studies to govern AI systems in Healthcare, HR, Education, Legal and Finance verticals
Navigate Global AI Laws: Gain expert knowledge of the EU AI Act, GDPR Article 22, ADA, FCRA, SR 11-7, and emerging regulatory trends across the US, South Korea
Implement Industry Frameworks: Learn to apply the NIST AI RMF four functions and ISO/IEC 42001 to build a certifiable, trustworthy AI management system
Govern the Full AI Lifecycle: Manage AI from planning through decommissioning, including data governance, model training and rigorous testing protocols
Mitigate AI-Specific Risks: Identify and counter adversarial attacks, data poisoning, model drift, algorithmic bias and the unique risks of agentic AI
Lead Organisational Strategy: Establish an AI Governance Committee, draft Acceptable Use Policies, and manage shadow AI adoption using 23 ready-to-use templates
Pass the AIGP Exam: Master the IAPP Body of Knowledge v2.1 with 200+ scenario-based practice questions and two full mock exams for first-attempt success

Course content

17 sections • 120 lectures • 5h 51m total length

Introduction2:05
Why AIGP Certification is required ?1:27
Who this Certification is for ?1:33
What is AIGP and who runs it ?1:30
AIGP Exam Facts You Should Know1:39
AIGP Exam Syllabus1:27
The Course Map1:36
DEMO - End to End AI Governance Workflow8:45
Before you learn the theory, see how it works in practice. A visual walkthrough of a working AI Release Readiness Platform showing the complete governance journey — from use case registration and regulatory mapping through release gates, live monitoring and automatic reassessment when a policy threshold is crossed. Every concept you learn in Modules 1 through 4 has a home in this workflow.

Introduction to Module 11:52
Master what AI is and why it needs governance. This module covers AI definitions (ISO 22989), the four types of machine learning, the AI hierarchy from machine learning through deep learning, discriminative vs generative models, AI agents and multi-agent systems, the seven AI characteristics that create governance needs, ten AI risks, four levels of harm, six responsible AI principles, seven governance roles, three governance models, cross-functional collaboration, the AI policy framework, and third-party AI governance. You will understand how to set up a complete governance programme before any AI development begins.
By the end of this module, you will be able to:
Define AI and distinguish it from conventional software
Identify all four ML types and their governance implications
Understand AI Techniques and Agentic AI
Map the seven AI characteristics to the ten AI risks
Establish governance roles, models and cross-functional collaboration
Create AI policies covering privacy, security, IP and data governance
Govern third-party AI through the four-stage control framework
Templates included: AI Governance Policy, Acceptable Use Policy, Committee Charter, Risk Tolerance Statement, Pre-Procurement Checklist

D1A -Normal System Vs AI System1:51
D1A- AI System Definition - ISO 229892:09
D1A - ML System Definition1:08
Quiz — AI Definitions and ISO 22989
D1A - AI Hierarchy2:04
D1A - AI Capability Spectrum2:28
D1A - AI Hierarchy and Governance Complexity1:49
Quiz - AI Types, Hierarchy and Characteristics
D1A - AI Techniques - Fine Tuning Vs RAG1:57
D1A - Agentic Architectures2:16
D1A - ML Types2:56
D1A - AI Model Function Types2:45
D1A - ML Algorithms And Feature Engineering6:09
Quiz - ML Types, Model Functions and Feature Engineering
D1A - AI Characteristics2:28
D1A - Outdated Assumptions from Traditional Systems2:12
D1A - Case Study - Amazon Hiring Algorithm2:03
D1A - AI Risks5:28
D1A - AI Harms2:38
D1A - Responsible AI Principles4:13
D1A - AI Characteristics Risks Principles Mapping2:07
Quiz - AI Risks, Harms and Responsible AI Principles

D1B,C - Operationalizing AI Governance - When Nobody Owns the AI1:45
D1B,C - AI Governance Roles2:03
D1B,C - Operational Roles2:06
D1B,C - AI Governance Models2:15
Quiz - AI Governance Roles and Models
D1B,C - Cross Functional Collaboration1:11
D1B,C - AI Governance Committee2:20
D1B,C - Policy Gap That Governance Missed2:05
D1B,C - AI Governance Lifecycle2:05
D1B,C - Updating Existing Policies2:13
D1B,C - Third Party AI Risk Control2:47
Quiz - AI Lifecycle, Policies and Third-Party Risk
Module End Knowledge Check
Module End Quiz - Scenario Based Questions

Module 2 : Introduction0:36
Navigate every law, standard and framework the exam tests. This module covers the EU AI Act (risk tiers, prohibited practices, high-risk requirements with article numbers, conformity assessment, four roles, GPAI obligations, FRIA, penalties), GDPR (principles, special categories, automated decision-making, DPIA), privacy laws across jurisdictions (CCPA, DPDPA, PDPL), non-discrimination laws (Title VII, ADA, ECOA, Fair Housing Act, Equality Act, Employment Equity Act), consumer protection, product liability, IP and copyright with indemnification, US sector laws (FCRA, HIPAA, COPPA, FTC Act, SR 11-7), AI-specific laws (South Korea, Colorado, Texas, Italy, Vietnam, US federal policy, emerging global laws), and standards (OECD Principles, OECD Classification Framework, NIST AI RMF, ISO 42001, 42005, 22989).
By the end of this module, you will be able to:
Classify any AI system into the correct EU AI Act risk tier
Identify every applicable law for a given AI deployment scenario
Distinguish FRIA from DPIA and know when each is required
Explain the obligations of Providers, Deployers, Importers and Distributors
Apply GDPR automated decision-making rights to AI scenarios
Identify the three ways AI can violate the ADA
Negotiate the ten governance-critical terms in vendor agreements
Map governance activities to the NIST AI RMF four functions
Explain why ISO 42001 is the only certifiable AI management system
Templates included: Regulatory Applicability Matrix, FRIA Template, DPIA Addendum, Vendor Agreement Checklist

D2C - What is EU AI Act ?2:02
D2C - EU AI Act : Four Risk Tiers2:04
Quiz - EU AI Act Overview and Risk Tiers
D2C - EU AI Act : Prohibited AI2:00
D2C - EU AI Act : High Risk AI2:32
D2C - EU AI Act : Limited and Minimal Risk AI1:50
Quiz - EU AI Act Risk Tier Categories
D2C - EU AI Act : High Risk AI Obligations2:18
D2C - EU AI Act : General Purpose AI (GPAI) Obligations2:35
Quiz - EU AI Act Obligations
D2C - EU AI Act : Organizational Roles2:34
D2C - EU AI Act : Penalties and Enforcement0:58
D2C - South Korean Basic AI Law0:31
D2C - US State AI Laws2:22
Quiz - Roles, Enforcement and Global AI Law

D2A - Universal Privacy Principles2:54
D2A - GDPR Scope and AI Relevance1:58
Quiz - Privacy Principles and GDPR Scope
D2A - GDPR Article 91:27
D2A - GDPR Article 221:31
D2A - GDPR Data Protection Impact Assessment (DPIA)2:21
Quiz - GDPR Articles 9 and 22
D2A - California Consumer Privacy Act (CCPA)1:59
Quiz - DPIA and CCPA
D2A - India and Saudi Arabia Privacy Acts1:51
D2A - Privacy Laws Comparison0:34
Quiz - Global Privacy Laws

D2B - AI and Non Discrimination Laws2:27
D2B - Jurisdiction Specific Non-Discrimination Laws2:10
D2B - Americans With Disability Act (ADA)2:07
Quiz - AI and Non-Discrimination Law
D2B - Consumer Protection Law2:11
D2B - IP and Copyright Laws1:50
D2B - Laws Working Together1:44
Quiz - Consumer Protection, IP and Law Overlaps
D2B - Product Liability Law & AI2:12
D2B - US Sector Laws2:35
D2B - SR 11-7 Model Risk Management For Banking2:55

Module 3 - Introduction0:25
Govern the full AI development lifecycle from planning through release. This module covers the iterative lifecycle, the six-step planning sequence, three impact assessments, the five-step risk management process with the probability/severity matrix and mitigation hierarchy, benchmarking and pre-deployment pilots, four ethical design pillars, human oversight models (in/on/out-of-the-loop), Three Lines of Defence, design documentation, AI-specific cybersecurity threats, data governance (formats, lifecycle, Article 10 quality dimensions, lineage and provenance, synthetic data, privacy-preserving techniques), TEVV framework, model training, hyperparameter tuning, seven testing types, the confusion matrix, precision/recall/F1/accuracy, overfitting and underfitting, release readiness, continuous monitoring, model drift, incident management, and post-deployment transparency.
By the end of this module, you will be able to:
Plan an AI system following the six-step governance sequence
Calculate risk scores and apply the mitigation hierarchy correctly
Assess data quality against all five Article 10 dimensions
Apply the TEVV framework to structure testing and validation
Interpret a confusion matrix and prioritise the right metric for each scenario
Prepare all three release readiness components (model card, conformity, checklist)
Monitor deployed AI across four dimensions and respond to drift
Manage AI incidents through the eight-element policy framework
Templates included: Use Case Assessment, Risk Register, Data Governance Checklist, Data Lineage Documentation, Model Card, Testing Plan, Pre-Release Governance Checklist, Incident Management Policy

Requirements

No prior AI technical knowledge or certifications are required.

Description

Most AIGP courses teach you how to pass an exam. This course teaches you how to pass the exam AND govern AI in practice.

Every concept in this course is aligned to the IAPP AIGP Body of Knowledge v2.1 (effective 2 February 2026). All four domains are covered comprehensively with real-world examples, exam alerts on every topic, and practical governance frameworks you can apply immediately.

But here is what makes this course different from every other AIGP course on Udemy.

You do not just learn what a Fundamental Rights Impact Assessment is. You download a ready-to-use FRIA template and watch it being completed in a healthcare case study. You do not just learn the ten terms that should be in a vendor agreement. You download a Vendor Agreement Checklist and see exactly when and how it is used when a bank contracts with an AI provider. You do not just learn the six stages of incident response. You watch a real incident unfold in a hospital setting and see the Incident Management Policy activated step by step.

Before you learn a single concept, you will see a complete AI governance workflow in action through a live platform walkthrough — from use case registration and regulatory mapping through release gates, live monitoring and automatic reassessment when a policy threshold is crossed. Every concept you learn in Modules 1 through 4 has a home in that workflow.

This course includes 23 downloadable governance templates spanning the full AI lifecycle, from your first AI Governance Policy through to the final Decommissioning Checklist. These can serve as reference for your governance toolkit.

No other AIGP course offers this. Study guides teach you theory. Templates give you practice. This course gives you both.

What is included:

Comprehensive video lectures covering all four AIGP domains
Live AI Governance Platform walkthrough — see the end-to-end workflow before you learn the theory
23 downloadable governance templates — ready to use at work
200+ scenario-based practice questions including two full 100-question practice exams
200 pages of downloadable study materials (study notes, exam quick reference, BoK navigation guide, case study notes)
5 end-to-end industry case studies (healthcare, financial services, education, recruitment, legal)
In-section quizzes after every lecture to check understanding
Exam alerts on every topic showing exactly what the exam tests
Template-to-case study mapping showing when to use each template in the governance lifecycle

Your AIGP exam preparation is fully covered. Your first day as an AI governance professional is too.

WHAT YOU'LL LEARN :

1. Master AI Foundations: Understand AI system types, the four ML types, discriminative vs generative models, and the AI hierarchy that underpins every governance decision
2. See Governance in Action First: Watch a live AI Release Readiness Platform walkthrough — the complete governance workflow, before you study a single concept
3. Navigate Global AI Laws: Gain expert knowledge of the EU AI Act, GDPR Article 22, ADA, FCRA, SR 11-7, and emerging regulatory trends across the US, South Korea, Italy and Vietnam
4. Implement Industry Frameworks: Learn to apply the NIST AI RMF four functions and ISO/IEC 42001 to build a certifiable, trustworthy AI management system
5. Govern the Full AI Lifecycle: Manage AI from planning through decommissioning, including data governance, model training and rigorous testing protocols
6. Mitigate AI-Specific Risks: Identify and counter adversarial attacks, data poisoning, model drift, algorithmic bias and the unique risks of agentic and multi-agent systems
7. Lead Organizational Strategy: Establish an AI Governance Committee, draft Acceptable Use Policies, and manage shadow AI adoption using 23 ready-to-use templates
8. Pass the AIGP Exam: Master the IAPP Body of Knowledge v2.1 with 200+ scenario-based practice questions and two full mock exams for first-attempt success

WHO THIS COURSE IS FOR

Professionals preparing for the IAPP AIGP certification exam
AI governance, risk and compliance professionals who need practical templates they can use at work immediately
Privacy professionals expanding into AI governance
Legal and compliance professionals advising on AI regulations
Data protection officers responsible for AI systems processing personal data
Risk managers adding AI risk to their portfolio
IT and security professionals governing AI infrastructure and deployment
Business leaders and executives responsible for AI strategy and oversight
Anyone who wants to understand how to govern AI systems responsibly, whether or not they plan to take the exam

COURSE REQUIREMENTS (Prerequisites)

No technical background required. This course explains AI concepts from the ground up.
No legal background required. Every law is explained in plain language with practical examples.
A willingness to learn how AI governance works across technology, law, ethics and operations.

Who this course is for:

This course is well-suited for anyone working in the field of AI, trying to understand AI governance landscape.
Compliance, legal, and risk management professionals adding AI governance to their expertise
Senior leaders accountable for organisational AI governance programmes
AI program managers, product managers, and technical leads responsible for AI system governance
Audit and assurance professionals conducting AI governance reviews
HR and people analytics professionals deploying AI in employment contexts
Privacy professionals extending into AI governance

AIGP Certification Prep (Latest) with AI Governance Toolkit

What you'll learn

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Course content

Introduction8 lectures • 20min

Module 1 — Understanding the foundations of AI governance1 lecture • 2min

D1.A Understand what AI is and why it needs governance18 lectures • 49min

Domain 1B&C - Operationalizing AI Governance and AI Governance Lifecycle Stages10 lectures • 21min

Domain II : Understanding how laws, standards and frameworks apply to AI1 lecture • 1min

Module 2 : D2C - Understand the main elements of AI-specific laws11 lectures • 22min

Module 2 - D2A : Understand how existing data privacy laws apply to AI8 lectures • 15min

Module 2 : D2B - Understand how other types of existing laws apply to AI.9 lectures • 20min

Module 2: D2D - Understand the industry standards and tools that apply to AI7 lectures • 16min

Module 3 : Domain III — Understanding how to govern AI development1 lecture • 1min

Requirements

Description

Who this course is for: