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DataCamp

AI Security and Risk Management

via DataCamp

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Overview

Learn the fundamentals of AI security to protect systems from threats, align security with business goals, and mitigate key risks.


Discover the essentials of safeguarding AI systems in this introductory course on AI security and risk management. Learn to align security efforts with business goals, mitigate risks, and tackle key security challenges. You will explore specific AI security issues, assess risks from multiple perspectives, and understand threats related to AI model development and usage. Designed for professionals seeking to protect their organizations, this course offers practical, actionable practices to become an AI security champion. By the end, you'll be equipped to stay ahead in the fast-evolving world of AI security.

Syllabus

  • AI's Security Landscape
    • The purpose of this chapter is to establish a strategic understanding of AI security, identify the unique security risks associated with AI, examine how AI can be a security change agent, and consider the need to treat all players equally.
  • Risk Management Fundamentals
    • This chapter focuses on the operational side of AI security and risk management, diving deeper into different types of risks, secure development practices, and risk assessment. We will first examine risks broken down by internal and external risk categories and then learn about practices aimed at mitigating them.
  • Strategic Integration of AI Security
    • Bringing AI security into alignment with organizations' strategic goals is the focus of this chapter. It covers the importance of connecting security efforts to tangible business value, ensuring security isn't an afterthought but a strategic asset. In addition, it talks about the importance of fostering a security-aware culture within an organization and the importance of keeping up to date with evolving risks and opportunities in the constantly changing world of AI.

Taught by

Angeline Corvaglia

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