15 642
Machine Learning Systems
Carnegie Mellon University · UGRD · Fall 2026
Catalog description
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: 15-503 Min. grade C or 15-513 Min. grade C or 18-213 Min. grade C or 18-600 Min. grade C or 18-613 Min. grade C or 14-513 Min. grade C or 15-213 Min. grade C
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