Trustworthy Machine Learning An introduction to technologies that support building trustworthy machine learning systems. Topics include, but are not limited to, adversarial machine learning, privacy-preserving machine learning, transparency in machine learning, and fairness of machine learning. Not offered on a regular basis. Credit Hours: 4 Prerequisites: CSCI 4260/6260 or permission of department Level: Graduate
