Courses - Fall 2026
CMSC848A
Selected Topics in Information Processing; Trustworthy Machine Learning
Credits:
3
Grad Meth:
Reg
Must be in the Graduate Program in Computer Science. All other graduate students must request permission.
Trustworthy ML introduces concepts of trustworthiness in machine learning, drawn from computer science, systems engineering, human-computer interaction, psychology, and philosophy. Trustworthiness topics include robustness, uncertainty, fairness, transparency, values alignment, AI safety, etc. The course should be accessible to anyone with an introductory background in machine learning, such as would be acquired in CMSC 422, INST 737, or equivalent.
Trustworthy ML introduces concepts of trustworthiness in machine learning, drawn from computer science, systems engineering, human-computer interaction, psychology, and philosophy. Trustworthiness topics include robustness, uncertainty, fairness, transparency, values alignment, AI safety, etc. The course should be accessible to anyone with an introductory background in machine learning, such as would be acquired in CMSC 422, INST 737, or equivalent.
Flagship Institution of the University System of Maryland
University of Maryland, College Park, MD 20742, USA
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Phone:
301.405.1000
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