Develop essential data science & ai skills with expert instruction and practical examples.
Exam Updates:July 2025 - Added 100+ questions as per latest exam updateCourse Description:Are you preparing for the Artificial Intelligence Governance Professional (AIGP) certification or looking to deepen your understanding of AI governance. This course offers comprehensive practice tests to help you assess your knowledge and gain confidence in AI regulations, compliance frameworks, and ethical AI principles. What You'll Get:350+ Realistic Exam-Style Questions - Covering AI governance, risk assessment, regulatory compliance, and ethical AI best practicesScenario-Based Challenges - Practical, real-world questions to test your decision-making skillsDetailed Explanations - Learn the ‘why' behind each answer and strengthen your understandingUp-to-Date Content - Stay aligned with evolving AI policies, global regulations, and governance frameworksWho Should Take This Course.
Professionals preparing for AIGP certificationAI compliance officers, risk managers, and policymakersAI practitioners, security professionals, and business leadersAIGP Exam Details (Based on Official Guidelines):Exam Duration: 3 hours (with a 15-minute optional break)Minimum Passing Score: 300/500Question Format: 100 multiple-choice questions (including 30% case study-based questions)Scoring Method:85 scored questions, 15 unscored experimental questionsNo penalty for incorrect answersLatest AIGP Exam Syllabus Domains:Domain I - Understanding the Foundations of AI Governance(Questions/Examples in Practice Exams 1 and 2)Focuses on what AI governance is, including the common principles and pillars to build an AI governance program. Covers best practices regardless of industry, sector or size. Key areas: understanding AI and governance needs, communicating expectations, and establishing governance policies and procedures across the AI life cycle.
Domain II - Understanding How Laws, Standards, and Frameworks Apply to AI (Questions/Examples in Practice Exam 3)Covers existing data privacy laws, new AI-specific laws, standards, and frameworks (like the EU AI Act, OECD, NIST, ISO), and how they apply to AI. Includes understanding privacy, intellectual property, non-discrimination, consumer protection, and product liability in the AI context. Domain III - Governing AI Development(Questions/Examples in Practice Exam 4)Focuses on responsibilities related to designing, building, training, testing, and maintaining AI models.
Includes defining business context and use case, impact assessments, risk management, documentation, and data governance during AI development. Domain IV - Governing AI Deployment and Use (Questions/Examples in Practice Exam 5)Covers selecting, deploying, and using AI models responsibly, with emphasis on monitoring, maintenance, risk/issue management, post-market obligations, transparency, deactivation/localization, and communication plans. Applies to both proprietary and third-party AI models.
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