AI and Cybersecurity: Securing the Future of Tech

As artificial intelligence transforms industries, it also introduces unprecedented security risks and attack vectors. Understanding how to secure machine learning models and defend against AI-powered threats is now an essential skill for modern technology professionals. This course provides a comprehensive introduction to the intersection of AI and cybersecurity, guiding you through core concepts, vulnerability assessments, and defensive strategies. You will learn to recognize unique risks associated with Large Language Models (LLMs), implement robust security frameworks, and protect data privacy in AI-driven environments. What you'll learn: - Understand the fundamentals of AI-related security risks, including adversarial attacks and data poisoning. - Identify critical vulnerabilities in Large Language Models (LLMs) such as prompt injection and insecure output handling. - Apply modern threat modeling techniques specifically tailored for machine learning pipelines. - Explore zero-trust principles and secure deployment strategies for AI applications. - Analyze real-world case studies of AI-driven cyber threats and defensive countermeasures. The course begins with foundational definitions and key terminology of both cybersecurity and artificial intelligence. You will then progress through written guides and structured scenarios exploring vulnerabilities, risk mitigation, and secure design patterns. This course is designed for beginners, developers, and aspiring security analysts who want to understand the security implications of AI. No prior background in cybersecurity or advanced machine learning is required. Start reading today to build a strong foundation in securing the next generation of intelligent systems.