Introduction to AI Security: Protecting Systems in the Age of Intelligence

As artificial intelligence transforms how we work and build, it also introduces entirely new security vulnerabilities that traditional defense systems are not prepared to handle. Understanding how to secure these intelligent systems is no longer optional—it is a critical skill for the future of technology. This comprehensive text-only course guides you through the fundamental principles of securing AI applications, helping you understand both the opportunities and the risks of modern models. By completing this course, you will transition from a beginner to a security-conscious practitioner capable of identifying vulnerabilities in AI implementations. You will learn how to protect sensitive data, secure machine learning pipelines, and defend against emerging exploits. What you'll learn: - Understand foundational AI security concepts, terminology, and threat vectors. - Identify modern vulnerabilities unique to large language models, including prompt injection and data poisoning. - Apply data privacy principles to ensure training data and user inputs remain secure. - Analyze the OWASP Top 10 framework for LLMs to recognize common security pitfalls. - Formulate basic threat modeling strategies specifically tailored for AI-driven software. The course begins with essential definitions of AI architectures and security baselines before guiding you through real-world threat scenarios and modern mitigation strategies. Through clear written explanations and structured analysis, you will build a solid foundation in secure AI deployment. This course is designed for absolute beginners, developers, and IT professionals looking to understand AI security with no prior security experience required. Start reading today to build safer, more resilient intelligent systems.