CompliQuest

Course Overview

Building AI systems without following international standards is like constructing a building without permits. Eventually, regulators will shut you down, and the costs will be enormous. This essential masterclass cuts through the jargon to show you exactly how standards like ISO/IEC 42001 and EU AI Act requirements work in the real world, transforming intimidating regulatory frameworks into step-by-step processes that any organization can follow. You'll discover how to create AI governance that protects your business while proving to regulators, customers, and partners that your AI systems are trustworthy and legally compliant.

Learn the secrets of successful AI governance: building accountability systems that work under pressure, implementing risk controls that catch dangerous AI behavior before it causes damage, and creating documentation that satisfies even the toughest auditors. Through hands-on examples, you'll gain the confidence to deploy AI systems that meet international standards while delivering real business value. Walk away with a valuable certificate and the practical knowledge to turn AI compliance from a headache into a competitive advantage.

Who Is This For?

This course is designed for professionals working with AI systems in governance, compliance, and risk management roles, including:

1. AI governance leads and compliance officers – ensuring AI aligns with international standards and legal frameworks
2. Risk managers and auditors – overseeing AI risk assessments, impact analyses, and continuous monitoring.
3. IT and data managers – responsible for applying standards to datasets, infrastructure, and documentation.
4. Legal advisors – ensuring AI deployments are consistent with the EU AI Act and other regulatory requirements.
5. Business and supply chain partners – integrating AI standards into procurement and operational practices.

Modules

• A Systematic Approach to AI Risk Management and Continuous Improvement – Learn how to apply international AI standards in a structured way to manage risks and keep improving over time. This module explains how to set clear policies, define roles, and keep your AI systems safe, compliant, and trustworthy
• AI Model Compliance – Explore how to ensure AI models follow data protection rules and keep information private. This module covers data minimisation, technical and organisational safeguards, and resilience testing so you can spot risks early and demonstrate compliance.
• Testing AI Model Anonymity – This module walks you through membership inference, model inversion, and data extraction attacks, showing how attackers work and how you can defend against them.
• Data Governance – See how to manage the full lifecycle of AI data responsibly. This module explains how to document sources, keep data quality high, anonymise sensitive information, and prepare datasets so your AI projects stay transparent, fair, and legally sound. 
• Quality Management System – Learn how to structure AI development and use. This module covers writing policies, assigning responsibilities, managing resources, and verifying systems, while also creating clear reporting channels for employees, suppliers, and users. 
• Implementing AI Standards – Discover how to turn AI standards into action. This module shows you how to run a gap analysis, set objectives, build an implementation roadmap, train teams, and monitor systems – embedding event logging and continuous improvement from the start.