Securing AI Systems: Fundamentals of AI Security and Risk Management

As artificial intelligence transforms industries, it also introduces unprecedented security risks and vulnerabilities that traditional defense frameworks cannot handle alone. Understanding how to protect AI models and the data powering them is now a critical skill for modern technology and security professionals. This text-only course provides a clear introduction to securing AI systems and implementing robust data protection strategies. You will progress from foundational concepts to practical risk-mitigation frameworks, enabling you to safeguard your organization's AI deployments against emerging threats. What you'll learn: - Understand foundational AI security concepts, including model vulnerabilities and data privacy risks. - Identify common AI threat vectors such as prompt injection, data poisoning, and model evasion. - Apply modern risk management frameworks to secure AI pipelines and model deployments. - Analyze the OWASP Top 10 vulnerabilities specifically tailored for Large Language Models. - Configure basic data protection and access control policies for AI training datasets. - Design responsible AI governance strategies to ensure compliance and ethical alignment. The course starts with essential terminology and the core concepts of machine learning security before moving into specific threat models, real-world vulnerability scenarios, and actionable mitigation strategies. You will engage with written explanations, conceptual breakdowns, and practical security checklists. This program is designed for IT professionals, security analysts, data protection officers, and beginners who want to understand the intersection of cybersecurity and artificial intelligence, with no prior experience in AI development required. Start building your foundational knowledge of AI security today.