Artificial intelligence (AI) is increasingly used in critical industries like healthcare and finance, but it faces significant security challenges from adversarial attacks and vulnerabilities.
The Threat Landscape of AI Systems” explores these security threats, including theft, poisoning, and model inversion. This course series provides learners with essential knowledge and tools to understand AI systems and defend against adversarial exploits.
Navigating Security Threats and Defenses in AI Systems Free Course
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Learn About:
- Understand the fundamental ethical principles and guidelines that govern the development and deployment of AI.
- Explore ways to integrate fairness, transparency, accountability, and inclusivity into AI systems.
- Acquire the skills to identify security risks and threats specific to AI systems, including adversarial attacks and data breaches.
Requirements:
- Familiarity with key concepts, terminology, and basic AI and machine learning principles.
- Understanding of how AI models are trained, validated, and deployed.
- Basic knowledge of data collection, preprocessing, and analysis techniques.
