Artificial Intelligence brings transformative benefits but also unprecedented privacy, security, and compliance risks. Recent incidents (i.e. Samsung, McDonald’s, OpenAI, Slack) and regulatory actions show what happens when these risks are ignored. This course teaches learners to secure AI systems by implementing privacy-by-design, least privilege, DLP, and dynamic access controls and to map these controls to global regulations. Through case studies, policy drafting, and hands-on labs, learners develop the skills to assess risks, deploy controls, and respond to incidents in real AI environments. No advanced programming or AI expertise is required. All you need is basic IT/security knowledge.
Secure AI with Privacy and Access Controls
Secure AI with Privacy and Access Controls
This course is part of AI Security: Security in the Age of Artificial Intelligence Specialization
Instructors: Starweaver
Access provided by ExxonMobil
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
4 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Analyze real-world AI security, privacy, and access control risks to understand how these manifest in their own organizations.
Design technical controls and governance frameworks to secure AI systems, guided by free tools and industry guidelines.
Assess privacy laws' impact on AI, draft compliant policies, and tackle compliance challenges.
Skills you'll gain
- Risk Management Framework
- Generative AI
- Data Security
- Responsible AI
- Threat Management
- Authorization (Computing)
- General Data Protection Regulation (GDPR)
- Security Controls
- Data Loss Prevention
- Data Ethics
- Governance
- Cyber Governance
- Personally Identifiable Information
- Security Management
- Security Awareness
- Incident Response
- Information Privacy
- Cyber Security Policies
- AI Security
- Role-Based Access Control (RBAC)
- Skills section collapsed. Showing 8 of 20 skills.
Details to know
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Assessments
1 assignment
Taught in English
Recently updated!
February 2026
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This course is part of the AI Security: Security in the Age of Artificial Intelligence Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 3 modules in this course
This module examines the security and compliance challenges of generative AI, using real-world cases like data breaches and prompt injection attacks. Learners practise incident response, risk classification, and remediation strategies, explore key privacy laws and frameworks, and gain skills to identify, mitigate, and prevent AI risks while ensuring organizational compliance and resilience in AI adoption.
What's included
4 videos2 readings1 peer review
This module provides a comprehensive overview of AI agent access control in healthcare, focusing on RBAC, ABAC, policy-as-code, and privacy-enhancing technologies. Participants learn to configure secure policies, protect sensitive data, monitor threats, and apply real-world privacy solutions, culminating in hands-on development, deployment, and documentation of robust security and compliance controls for AI systems.
What's included
3 videos1 reading1 peer review
This module prepares learners for AI compliance and security audits through interactive scenarios, governance frameworks, and practical tools. It covers policy drafting, audit readiness, evidence management, and secure AI deployment. Learners gain skills in risk assessment, regulatory gap analysis, and ethical governance, equipping them to navigate evolving AI compliance and security challenges in regulated industries.
What's included
4 videos1 reading1 assignment2 peer reviews
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