Artificial Intelligence Fundamentals Certificate Exam Prep
The Artificial Intelligence Fundamentals Certificate (AI Fundamentals) exam validates ai concepts, terminology, and use cases, data, machine learning, and model development, ai engineering, platforms, and operations, ai governance, risk, ethics, and trustworthiness. ExamPal publishes 40 premium questions and a 40-question free practice exam mapped across 5 blueprint domains. The local official-details index records: 60; 2 hours; Multiple choice; some lab/performance-based components may appear by form. Candidates should verify current registration, pricing, and scoring details with the official exam authority before booking.
Exam Details
Exam Overview
Administered by
ISACA
Exam Format
60; 2 hours; Multiple choice; some lab/performance-based components may appear by form
Passing Score
Verify current official exam guide
Exam Fee
$120 member / $144 non-member
Prerequisite
Review ISACA official page, resources page, candidate guide links, study guide listing.
Topics Covered
ExamPal covers all major topics tested on the Artificial Intelligence Fundamentals Certificate exam. Our questions are grounded in official study materials.
AI Concepts, Terminology, and Use Cases
Covers foundational AI concepts, major learning approaches, common models and techniques, business value, and practical use cases. This domain emphasizes understanding what AI is, how it is used, and how different AI methods map to business problems.
Data, Machine Learning, and Model Development
Covers the role of data, feature engineering, the machine learning lifecycle, model training and optimization, algorithm selection, performance evaluation, and NLP basics. This domain emphasizes how data and models are prepared, trained, assessed, and applied.
AI Engineering, Platforms, and Operations
Covers AI infrastructure, system components, operational considerations, and technical environments. This domain emphasizes deployment choices, monitoring, versioning, reproducibility, and the environments used to build and run AI systems.
AI Governance, Risk, Ethics, and Trustworthiness
Covers governance fundamentals, ethical principles, AI risks, risk management, and trustworthiness. This domain emphasizes oversight, responsible use, and the characteristics that make AI systems reliable and acceptable to stakeholders.
AI Assurance, Audit, and Responsible Adoption
Covers the auditor’s role in AI environments, audit considerations, assessment of AI outputs, and practices that support responsible adoption. This domain emphasizes assurance, validation, professional judgment, and human oversight in AI-enabled decision-making.
Exam Blueprint
What the Artificial Intelligence Fundamentals Certificate Exam Tests
The exam is divided into 5 domains. Here is what each domain covers and how much weight it carries on the test.
Domain 1 — AI Concepts, Terminology, and Use Cases
20% of examCovers foundational AI concepts, major learning approaches, common models and techniques, business value, and practical use cases. This domain emphasizes understanding what AI is, how it is used, and how different AI methods map to business problems.
- Task 1.1: Explain foundational AI concepts
- Define artificial intelligence
- Define machine learning
- Define deep learning
- Define generative AI
- Distinguish narrow AI from general AI
- Common AI capabilities
Key references: AI Fundamentals official exam guide · ExamPal shared topic tree
Domain 2 — Data, Machine Learning, and Model Development
30% of examCovers the role of data, feature engineering, the machine learning lifecycle, model training and optimization, algorithm selection, performance evaluation, and NLP basics. This domain emphasizes how data and models are prepared, trained, assessed, and applied.
- Task 2.1: Describe the role of data in AI systems
- Importance of data characteristics
- Data types
- Data preparation activities
- Task 2.2: Explain feature engineering and preprocessing
- Feature selection and extraction
- Common preprocessing techniques
Key references: AI Fundamentals official exam guide · ExamPal shared topic tree
Domain 3 — AI Engineering, Platforms, and Operations
15% of examCovers AI infrastructure, system components, operational considerations, and technical environments. This domain emphasizes deployment choices, monitoring, versioning, reproducibility, and the environments used to build and run AI systems.
- Task 3.1: Identify AI infrastructure and deployment options
- Deployment options
- Benefits of cloud AI
- Deployment considerations
- Task 3.2: Describe AI system components
- AI pipelines
- Key system components
Key references: AI Fundamentals official exam guide · ExamPal shared topic tree
Domain 4 — AI Governance, Risk, Ethics, and Trustworthiness
20% of examCovers governance fundamentals, ethical principles, AI risks, risk management, and trustworthiness. This domain emphasizes oversight, responsible use, and the characteristics that make AI systems reliable and acceptable to stakeholders.
- Task 4.1: Explain AI governance fundamentals
- Define AI governance
- Policies, roles, and accountability
- Governance before deployment
- Task 4.2: Identify ethical principles in AI
- Key ethical principles
- Ethical issues
Key references: AI Fundamentals official exam guide · ExamPal shared topic tree
Domain 5 — AI Assurance, Audit, and Responsible Adoption
15% of examCovers the auditor’s role in AI environments, audit considerations, assessment of AI outputs, and practices that support responsible adoption. This domain emphasizes assurance, validation, professional judgment, and human oversight in AI-enabled decision-making.
- Task 5.1: Explain the auditor’s role in AI environments
- Understand the AI lifecycle
- AI affects assurance activities
- Verify assumptions, controls, and outputs
- Task 5.2: Identify audit considerations for AI systems
- Audit scope and objectives
- Review areas for AI audits
Key references: AI Fundamentals official exam guide · ExamPal shared topic tree
Why study with ExamPal
Everything you need to prepare for and pass the Artificial Intelligence Fundamentals Certificate exam, in one app.
- 40 AI Fundamentals premium practice questions
- Free 40-question interactive practice exam
- 5 blueprint domains covered
- 40 glossary terms loaded from the shared terminology pack
- Detailed explanations and per-option rationales for study review
- Domain-level review paths with study guide, glossary, and static question pages
Artificial Intelligence Fundamentals Certificate Exam — Common Questions
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