EXIN Artificial Intelligence Compliance Professional
Become the go-to expert in AI compliance. In just two days, gain the tools and insights needed to align AI with legal, ethical, and operational standards.
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Category
Artificial Intelligence (AI)
Certificate
EXIN Artificial Intelligence Compliance Professional
Level
Advanced
A Smart Choice for Serious AI Governance
This isn’t just another box-ticking certification. The EXIN AI Compliance Professional program is designed for professionals who must lead, enforce, or verify compliance with AI laws, policies, and standards across real-world operations.
From interpreting the EU AI Act to applying ISO/IEC 42001 and NIST AI RMF across lifecycles, this certification provides more than theory—it gives you tools, checklists, and templates you can apply right away.
Who Should Take This Course
- Compliance professionals and legal teams handling AI oversight
- Quality, risk, and data protection officers
- Engineers, developers, and product leads working on AI systems
- Managers guiding AI adoption and responsible innovation
- Anyone tasked with AI system lifecycle governance—from design to decommission
What You Will Learn
- Understanding the EU AI Act: Purpose, scope, classifications, and legal implications for AI in regulated sectors.
- Key Regulatory Insights: Deep dive into Articles 8, 9, and 10, risk categories, prohibited practices, and high-risk system requirements.
- Trustworthy AI Design: How to integrate privacy, transparency, and accountability into AI systems.
- Ethical & Human-Centric AI: Applying fairness, ethics, and human rights in AI development.
- Compliance in Practice: Actionable strategies, tools, and real-world steps for meeting AI Act requirements.
- Supporting Frameworks: Using ISO/IEC 42001, ISO 23894, NIST AI RMF, GDPR, and EU Ethics Guidelines in AI governance.
This certification ensures a strong foundation in legal, ethical, and practical compliance for responsible AI.
Why This Certification Matters
Unlike most certifications, this one teaches you how to use compliance frameworks across the entire AI lifecycle—from development to deployment and beyond. You leave with more than a certificate. You leave with a toolkit for real-world success.
Ready to Lead AI Compliance?
If your company builds, buys, or manages AI, this is the certification that equips you to keep it legal, ethical, and defensible.
Duration
2-days
Course Delivery
Classroom or Virtual Classroom
What’s included
- Training workbook containing all of the presentation materials, course notes and sample exams.
- Exam voucher
- Free refresher course**
Prerequisites
- Involves practical assignments
- EXIN Artificial Intelligence Essentials or EXIN BCS Artificial Intelligence Foundation is highly recommended.
About the Examination
Candidates must complete the Practical Assignments in order to take the exam.
- Practical Assignments:
- 3 group assignments (2 hours, 1.5 hours, 2 hours)
- Pass mark: at least 7 of 11 criteria (65%) cumulatively.
- Individual performance assessed
- Exam:
- Format: Closed-book, multiple-choice.
- Number of Questions: 40.
- Duration: 90 minutes.
- Pass Mark: 65%.
Exam Body
EXIN
** Terms & conditions applied.
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Concepts Covered
- Key definitions of Artificial Intelligence (AI) terminology
- Key milestones in the development of AI
- Types of AI
- Societal impact of AI
- Sustainability measures to reduce AI’s environmental impact
- Ethical concerns in AI, including bias and privacy
- Importance of guiding principles for ethical AI development
- Strategies to address ethical challenges in AI projects
- Role of regulations in AI
- Process of risk management in AI
- Common examples of AI applications
- Role of robotics in AI systems
- Machine learning
- Common machine learning concepts
- Supervised and unsupervised learning processes
- Key data terms relevant to AI
- Data quality characteristics and their importance in AI
- Risks associated with data handling and strategies to mitigate them
- Purpose and use of big data
- Data visualization techniques and tools
- Key generative AI terms
- Purpose and application of generative AI, including large language models
- Role of data in training AI within the machine learning process
- Opportunities for implementing AI in an organization
- Contents and structure of a business case
- Stakeholders for an AI project
- Project management approaches
- Risks, costs, and benefits associated with a proposed solution
- Ongoing governance activities required when implementing AI
- Roles and career opportunities emerging with AI
- Real-world applications of AI
- AI’s impact on society and the future of AI
- Consciousness and its impact on ethical AI
Training Schedules
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