AI Security Architecture, Controls, and Defensive Operations

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This comprehensive course equips learners with the knowledge and skills to secure AI systems effectively, covering threat modeling, security controls, access management, data protection, monitoring, and attack mitigation. You’ll explore practical frameworks like OWASP ML Security Top 10, MITRE ATLAS, and CVE AI guidelines, gaining hands-on insights into implementing robust AI defenses. Through structured modules, learners will understand model evaluation, guardrails, endpoint access, encryption, auditing, and monitoring practices essential for safeguarding AI deployments. The course also examines real-world attack vectors including prompt injection, model inversion, supply chain threats, and adversarial manipulations, teaching you how to anticipate, detect, and mitigate risks. Designed for IT professionals, security engineers, and AI practitioners, this course assumes foundational knowledge in cybersecurity principles and AI systems, offering a structured path from basic controls to advanced defensive strategies. By the end of the course, you will be able to design, implement, and manage comprehensive AI security architectures, apply controls and compensating measures, secure data and access, and utilize AI-enabled tools to protect systems from complex attack vectors.

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