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Secure AI with Privacy and Access Controls

This course is part of multiple programs.

Instructors: Starweaver

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

4 hours to complete

Flexible schedule

Learn at your own pace

3 modules

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

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

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.

Module details

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

4 videosTotal 24 minutes

Welcome to the Course3 minutes
Introduction to AI Security and Privacy Risks6 minutes
Understanding AI Security and Privacy Regulations6 minutes
Real-World AI Security Incidents8 minutes

2 readingsTotal 10 minutes

Welcome to the Course: Course Overview5 minutes
About the ISO/IEC 42001 and the AI Risk Management Framework5 minutes

1 peer reviewTotal 20 minutes

Hands-On-Learning: AI Data Leak Risk Assessment and Remediation Planning20 minutes

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

3 videosTotal 31 minutes

Privacy-Enhancing Technologies and Data Protection7 minutes
Dynamic Access Control and Authorization in AI12 minutes
Continuous Monitoring, Incident Response, and Insider Threats12 minutes

1 readingTotal 10 minutes

Organization for Economic Cooperation and Development: Privacy Enhancing Technologies10 minutes

1 peer reviewTotal 20 minutes

Hands-On-Learning: Secure AI Agent Deployment in Healthcare20 minutes

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.