Securing AI Systems

Securing AI Systems is a hands-on course designed to help you safeguard machine learning applications against real-world threats. You will explore vulnerabilities such as adversarial attacks, data poisoning, and model theft, and then practice defense strategies through guided labs. By the end of the course, you will be able to secure AI pipelines, strengthen deployment environments, and implement monitoring and governance frameworks that ensure responsible AI use. This course is ideal for AI engineers, data scientists, cybersecurity professionals, and students aspiring to specialize in AI security. While prior knowledge of Python and basic machine learning concepts is recommended, all core security techniques will be taught step by step. Do not just build smarter AI. Build safer AI. Enroll now to gain the expertise needed to protect tomorrow’s intelligent systems,

• Identify AI security concepts, attack types, and mitigation strategies
• Implement defense measures, red-team simulations, and security controls
• Evaluate vulnerabilities, defense effectiveness, and incident responses
• Design secure AI systems with integrated security workflows

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work