14-757 Introduction to Machine Learning with Adversaries in Mind

12 units, Carnegie Mellon University

This course serves as an introduction to machine learning (ML) techniques with an additional focus on evasion, poisoning and exploratory attacks, and defenses against these attacks. The course will cover the following ML problems and methods: classification, regression, dimensionality reduction, clustering, expectation-maximization, Markov models and neural networks. Students will complete programming problems on implementation, attack and defense of spam filters, image classifiers, network anomaly detectors, human activity classifiers, real estate pricing models, search engines, and more. Grading will be based on biweekly Python programming assignments.

Prerequisites: none listed

Offered: Spring 2027, Fall 2026, Spring 2026, Fall 2025

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