This course introduces AI security and explores how AI technologies such as ChatGPT and DALL-E are transforming industries and the critical role of security in these implementations. You'll learn about myriad threats facing AI systems, including data poisoning and model inversion attacks, and learn to defend against these using the MITRE ATLAS framework. You'll cover the principles of secure AI development, emphasizing privacy-preserving techniques, model resilience, and adherence to emerging regulations. By the end of this course, you will have a comprehensive understanding of how to develop and secure AI systems ethically and effectively.
Practical Cybersecurity Fundamentals: Unit 5
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Practical Cybersecurity Fundamentals: Unit 5
This course is part of Practical Cybersecurity Fundamentals Specialization
Instructor: Pearson
Included with
Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
4 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Understand AI security fundamentals and the importance of securing AI implementations.
Identify and mitigate AI-specific threats using frameworks like MITRE ATLAS.
Master secure AI development practices, including privacy-preserving techniques and model resilience.
Navigate the ethical and legal landscape of AI, ensuring compliance with emerging regulations.
Skills you'll gain
Tools you'll learn
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in English
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This course is part of the Practical Cybersecurity Fundamentals Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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