CompliQuest

Course Overview

AI systems are powerful but vulnerable. Cybercriminals exploit their unique weaknesses, and the EU AI Act requires organisations to treat AI security as a legal obligation.

This course introduces you to the cybersecurity landscape through the lens of AI. You’ll uncover the hidden threats that can compromise AI systems, from classic exploits like
buffer overflows to AI-specific attacks such as data poisoning, adversarial inputs, and model inversion.

Real-world examples illustrate how attackers can intercept unencrypted data transmissions (man-in-the-middle attacks), manipulate training data to skew outcomes, or trick users through social engineering emails that lead to credential theft. 

We build on these scenarios to show how the GDPR’s requirement for appropriate technical and organisational measures and the AI Act’s security obligations converge. 

You’ll learn how to harden AI systems by securing the software supply chain, patching vulnerabilities in machine learning libraries, encrypting data in transit and at rest, and implementing strong access controls. We also cover the importance of privacy impact assessments for AI projects and how to document compliance. 

By the end of the course, you will be able to identify and mitigate AI-specific risks, design resilient architectures, and ensure that both the data and models you use remain trustworthy. 

Whether you build AI or oversee its deployment, you’ll gain practical skills to transform AI from a security liability into a robust asset.

Who Is This For?

This course is designed for professionals who work with, manage, or oversee AI systems and need to understand the cybersecurity risks and responsibilities involved in their development and use:

1. Cybersecurity & IT Risk Professionals – Strengthening your ability to assess and secure AI systems against emerging threats.
2. CIOs, CISOs & Technology Leaders – Gaining insight into how AI changes the threat landscape and how to manage associated risks.
3. AI & Data Science Teams – Learning how to integrate security best practices into model development and deployment.
4. Product Managers & Technical Leads – Ensuring AI-powered features are built with security and resilience in mind.
5. Compliance & Governance Teams – Understanding the security obligations tied to AI systems, especially in regulated sectors.
6. Procurement & Vendor Managers – Evaluating the cybersecurity posture of third-party AI systems and service providers.
7. Public Sector & Critical Infrastructure Leaders – Securing AI used in essential services from disruption or manipulation.
8. Risk Managers & Internal Audit Teams – Identifying and addressing vulnerabilities in AI-enabled business processes.
9. Anyone Involved in AI Deployment – Whether you're implementing, integrating, or overseeing AI systems, this course helps you recognize risks and apply security-first thinking.

Modules

• AI and Cybersecurity - Explore the unique security challenges that come with AI systems. This module covers how AI can introduce new vulnerabilities—from adversarial attacks and data poisoning to model inversion and misuse of generative tools. You'll learn core cybersecurity principles as they apply to AI, including system hardening, access controls, secure deployment practices, and incident response. By the end, you’ll know how to identify risks, protect AI assets, and build more resilient, trustworthy systems.