Course Description
Design secure AI/ML solutions
Artificial Intelligence (AI) is literally eating software as more and more solutions become ML-based. Unfortunately, these systems also have vulnerabilities; but, compared to software security, few people are really knowledgeable about this area. If it's impossible to secure AI against cyberattacks, there will be no AI-based technologies, such as self-driving cars, and yet another "AI winter" will soon be on us.
This course is almost certainly the first public, online, hands-on introduction to the future perspectives of cybersecurity and adopts a clear and easy-to-follow approach. In this course, you will learn about high-level risks targeting AI/ML systems. You will design specific security tests for image recognition systems and master techniques to test against attacks. You will then learn about various categories of adversarial attacks and how to choose the right defense strategy.
By the end of this course, you will be acquainted with various attacks and, more importantly, with the steps that you can take to secure your AI and machine learning systems effectively. For this course, practical experience with Python, machine learning, and deep learning frameworks is assumed, along with some basic math skills.
All the code and supporting files for this course are available on GitHub at:
https://github.com/PacktPublishing/Securing-Your-AI-and-Machine-Learning-Systems
About the Author
Course Structure
About the Provider
Course Provider Contact
Let Employers Find You
Upload/Update Your CVFeatured Courses