Securing AI Data and Applications

About this course

Secure AI systems and data using enterprise-grade governance, zero-trust architecture, and compliance frameworks. This course teaches you to govern GenAI data safely, implement zero-trust security models, secure applications against evolving threats, and evaluate cloud systems against standards like NIST and SOC 2. You will analyze breach scenarios, design role-based access controls, create infrastructure-as-code policies, and establish secure coding guidelines that prevent vulnerabilities at scale. Build practical skills in incident response, automated policy enforcement, threat modeling, and compliance evaluation. By the end of this course, you will be able to secure AI systems and data confidently, enforce enterprise-grade policies, anticipate and mitigate threats, and demonstrate readiness for senior security roles in AI-driven organizations.

What you will learn

• Analyze data access patterns and security incidents to design role-based controls that balance AI innovation with governance requirements
• Create zero-trust architectures and infrastructure-as-code policies that prevent breaches through continuous verification and automated enforcement
• Evaluate application security postures using threat modeling, penetration testing, and dependency analysis to prioritize remediation efforts
• Assess cloud security controls against industry frameworks like NIST, SOC 2, and compliance requirements for regulatory readiness