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
您将学到什么
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.
您将获得的技能
- Authorization (Computing)
- Data Loss Prevention
- Security Management
- Generative AI
- Cyber Governance
- Governance
- Incident Response
- General Data Protection Regulation (GDPR)
- Risk Management Framework
- Responsible AI
- Data Security
- Cyber Security Policies
- Security Awareness
- Information Privacy
- Data Ethics
- Personally Identifiable Information
- Role-Based Access Control (RBAC)
- Security Controls
- AI Security
- Threat Management
- 技能部分已折叠。显示 8 项技能，共 20 项。
要了解的详细信息
可分享的证书
添加到您的领英档案
作业
1 项作业
授课语言：英语（English）
最近已更新！
February 2026
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 AI Security: Security in the Age of Artificial Intelligence 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有3个模块
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.
涵盖的内容
4个视频2篇阅读材料1次同伴评审
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.
涵盖的内容
3个视频1篇阅读材料1次同伴评审
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.
涵盖的内容
4个视频1篇阅读材料1个作业2次同伴评审
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