AMLS is a 6 ECTS module, applicable to the master study courses computer science, computer engineering, information systems management, and electrical engineering, as well as the study areas data and software engineering, cognitive systems, and distributed systems and networks. Machine learning (ML) applications profoundly transform our lives, and many domains such as health care, finance, media, transportation, production, and information technology itself. In a narrow sense, ML systems are software systems underpinning theses ML applications. However, in a broad sense, ML systems comprise the entire systems from ML applications, over the compiler/runtime stack, to the underlying heterogeneous hardware devices. This module covers the architecture and essential concepts of modern machine learning (ML) systems for both local and large-scale machine learning. These architectures include systems for data-parallel execution, parameter servers, ML lifecycle systems, and the integration of ML into database systems. The covered topics focus both on a microscopic view of internal compilation, execution, and data management techniques, as well as a macroscopic view of end-to-end ML pipelines.