Library / Artificial Intelligence
AI Governance Practice Tests — NIST, ISO, OWASP, ATLAS
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About this course
Artificial Intelligence is rapidly transforming industries — and organizations need people who understand how to govern it safely, responsibly, and in alignment with global standards. This course gives you a practical, beginner-friendly way to build confidence in AI Governance through five scenario-based practice tests.
Across 50 original questions, you’ll explore real-world scenarios related to AI risk, safety, governance controls, red teaming, system oversight, and mitigation. Each question includes a clear explanation so you not only learn the correct answer, but also understand why it matters in real AI systems.
This course is aligned with several of the most important AI Governance and security frameworks, including:
- NIST AI Risk Management Framework
- ISO/IEC 42001 AI Management System Standard
- OWASP Top 10 for LLM Applications
- MITRE ATLAS adversarial attack knowledge base
- MAESTRO agentic AI failure-mode patterns
The practice tests are designed to help you build pattern recognition, develop governance intuition, and get familiar with common AI risks such as hallucinations, cascading failures, data leakage, indirect prompt injection, supply chain poisoning, model drift, and excessive autonomy.
This course is ideal for beginners, cybersecurity learners, GRC professionals, AI safety enthusiasts, and anyone who wants a structured and practical way to learn AI Governance concepts through scenario-based question practice.
By the end of this course, you’ll have stronger awareness of AI risks, a clearer understanding of governance controls and lifecycle processes, and greater confidence discussing AI Governance in real-world contexts.
I provide free external resources to support hands‑on IAM learning. All my courses include access to a free PBQ generator that lets you create your own exam‑style performance‑based questions for SC‑300, IAM Fundamentals, Governance, CyberArk, and more.
To find it, search GitHub for
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Udemy: 2026-09-27 · Coursera: 2026-09-27
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