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Computer Security and Machine Learning

This course will expose students to a cutting-edge area at the intersection of machine learning and computer security, called adversarial machine learning. This burgeoning area studies how to make machine learning models robust to attack. The starting point is the realization that, while machine learning has made great strides in recent years, the resulting models can be quite easy to confuse and attack. The course will introduce students to the traditional techniques used in training machine learning models, and why the resulting models are easily confused. Along the way we will discuss techniques in computer security that are used to attack and defend computer systems. Students will learn how to reason about the security of computer systems and will investigate techniques for building robust machine learning models.

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Session One
-
Accepting Waitlist Applications
Grade(s)
10-11
at the time of application
Age(s)
15-17
on the first day of session
Prerequisite(s)

Proficient in programming (1 year of high school computer science or equivalent).