Foundations of AI Security and Generative AI Defense

The rapid rise of generative AI tools has completely transformed the cybersecurity landscape, introducing both powerful new capabilities and sophisticated security risks. Understanding how to secure these AI technologies and defend against AI-powered threats is now a critical skill for any modern professional. In this course, you will transition from a security beginner to a practitioner who understands the core intersection of artificial intelligence and cybersecurity. You will learn to identify vulnerabilities unique to large language models, assess risks associated with AI adoption, and implement practical defense strategies to safeguard your organization's data. What you'll learn: - Learn the fundamental terminology of artificial intelligence and machine learning security. - Understand the unique vulnerability landscapes of generative AI, including prompt injection and data poisoning. - Analyze how threat actors utilize AI tools to automate attacks and craft highly convincing social engineering campaigns. - Apply the OWASP Top 10 framework for Large Language Model applications to real-world scenarios. - Configure governance policies and privacy controls to safely integrate AI technologies into business workflows. - Practice identifying and mitigating security risks in AI-generated code and outputs. The course begins with foundational definitions of AI security concepts before guiding you through practical threat modeling, vulnerability analysis, and modern defense frameworks. You will progress through structured text-based lessons and conceptual exercises designed to build your defensive security mindset. This course is designed for beginners in cybersecurity, IT professionals, and anyone curious about how generative AI impacts security, with no prior AI or programming experience required. Start reading today to build a strong foundation in securing the next generation of technology.