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Security Risks in AI and Machine Learning: Categorizing Attacks and Failure Modes Preview

Security Risks in AI and Machine Learning: Categorizing Attacks and Failure Modes

With Diana Kelley Liked by 628 users
Duration: 1h 11m Skill level: Beginner Released: 2/23/2022

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Course details

From predicting medical outcomes to managing retirement funds, we put a lot of trust in machine learning (ML) and artificial intelligence (AI) technology, even though we know they are vulnerable to attacks, and that sometimes they can completely fail us. In this course, instructor Diana Kelley pulls real-world examples from the latest ML research and walks through ways that ML and AI can fail, providing pointers on how to design, build, and maintain resilient systems.

Learn about intentional failures caused by attacks and unintentional failures caused by design flaws and implementation issues. Security threats and privacy risks are serious, but with the right tools and preparation you can set yourself up to reduce them. Diana explains some of the most effective approaches and techniques for building robust and resilient ML, such as dataset hygiene, adversarial training, and access control to APIs.

Skills you’ll gain

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Meet the instructor

Learner reviews

4.7 out of 5

390 ratings
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  • Jaime Vazquez Jaime Vazquez

    Jaime Vazquez

    Compliance Manager

    5/5 April 16, 2025
    REcomiendo esta curso Identificar produndament que factores deben considerarse en tema de Seguridad y Gestion de Riegos
    Helpful · Report
  • Mungai Peter Ng'ethe Mungai Peter Ng'ethe

    Mungai Peter Ng'ethe

    TheAfricanPillar | Certified IT Security (GRC) Specialist | Digital Transformation Advocate | Corporate & Personal Branding Strategist | Coach, Host…

    5/5 March 28, 2025
    The content was explicit and exhaustive. I'll recommend it to anyone who wants to dive deep into the nuance of AI and ML Security.
    Helpful · Report

Contents

What’s included

  • Practice while you learn 1 exercise file
  • Test your knowledge 4 quizzes
  • Learn on the go Access on tablet and phone

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