AI Security Synthesis and Capstone

This unit synthesizes key takeaways from the Rise of the Machines pathway to consolidate AI security and cybersecurity fundamentals into applied practice. Over ~30 hours students will integrate threat analysis, mitigation planning, and ethical/legal considerations to prepare for capstone work, certification study, or entry-level roles in AI security.

Learning Objectives

• Analyze real-world AI-related security incidents and identify technical vulnerabilities, attack vectors, and contributing system failures
• Apply appropriate mitigation strategies and defensive configurations (e.g., access controls, model hardening, monitoring) to a simulated AI system to reduce identified risks
• Demonstrate the ability to develop and execute an incident response and recovery plan for an AI-enabled environment, including roles, timelines, and communication artifacts
• Evaluate ethical, legal, and policy implications of AI security decisions and present prioritized, evidence-based recommendations to technical and non-technical stakeholders