15 442

Machine Learning Systems

Carnegie Mellon University · UGRD · Fall 2026

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The goal of this course is to provide students an understanding and overview of elements in modern machine learning systems. Throughout the course, the students will learn about the design rationale behind the state-of-the-art machine learning frameworks and advanced system techniques to scale, reduce memory, and offload heterogeneous compute resources. We will also run case studies of large-scale training and serving systems used in practice today. This course offers the necessary background for students who would like to pursue research in the area of machine learning systems or continue to work in machine learning engineering. Prerequisites: ( 21-128 Min. grade C or 15-151 Min. grade C or 21-127 Min. grade C) and 21-241 Min. grade C and ( 11-485 or 10-701 or 15-281 or 10-315 or 10-301 ) and ( 15-213 Min. grade C or 15-513 Min. grade C or 18-600 Min. grade C or 18-213 Min. grade C)

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Class #carnegie_mellon-15442Fall 2026UGRD12 credits
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