Securing AI Systems: Defending Artificial Intelligence against Cyber Threats

As artificial intelligence becomes central to modern technology, the need for robust security measures to protect these systems has never been more critical. This course provides a comprehensive introduction to the unique vulnerabilities of machine learning and provides a framework for building resilient, secure applications. You will move from understanding basic security concepts to identifying complex threats that specifically target intelligent systems. By the end of this course, you will be able to assess AI-related risks and implement best practices to safeguard both models and the data they process. What you'll learn: - Understand the fundamental concepts of AI security and the machine learning lifecycle. - Identify common vulnerabilities such as prompt injection, model inversion, and data poisoning. - Apply defense-in-depth strategies to secure data pipelines and model deployments. - Practice risk assessment techniques specifically designed for intelligent systems. - Explore modern security frameworks including the OWASP Top 10 for Large Language Models. - Analyze the privacy implications of training AI on sensitive data and how to mitigate leakage. The course begins with essential terminology and core security principles before moving into specific attack vectors and defensive countermeasures. You will explore how to integrate security into every stage of the development process through clear, written explanations and practical examples. This course is designed for beginners in security, developers, and data professionals who want to understand how to protect AI-driven technologies. No prior experience in AI security is required. Start building a more secure future for artificial intelligence today.