Foundations of AI Security

As AI becomes integrated into more applications, understanding how to protect these systems from malicious attacks is crucial. This course provides a comprehensive introduction to the fundamental concepts and practical strategies for securing artificial intelligence. By completing this course, you will develop a foundational understanding of AI security, enabling you to identify potential vulnerabilities and apply effective defense mechanisms to AI models and applications. You will be prepared to contribute to building more resilient and trustworthy AI systems. What you'll learn: * Understand core principles of AI security and common attack surfaces. * Learn to identify and mitigate adversarial attacks such as data poisoning and model evasion. * Apply defense mechanisms to secure AI models across their development and deployment lifecycle. * Explore techniques for building robust and resilient AI systems against manipulation. * Practice implementing foundational defenses against emerging threats like prompt injection. * Examine basic concepts of AI supply chain security and model integrity. This course begins with essential terminology and foundational concepts before progressing to practical defense strategies and an overview of current AI security challenges. All lessons are delivered through clear written explanations and code snippets, allowing you to focus on the material at your own pace. This course is designed for beginners in AI and cybersecurity with no prior experience in AI security. No advanced prerequisites are required. Start building more secure AI systems today.