This module introduces the principles and practices of machine learning operations (MLOps), focusing on how machine learning models are developed, deployed, and managed in production-oriented settings. It covers the end-to-end lifecycle of artificial intelligence (AI) systems, including workflow automation, version control, testing, and monitoring, alongside computational aspects such as GPU acceleration and high-performance computing for efficient training and experimentation. Students gain practical experience with tools and frameworks commonly used in production environments to build reproducible, scalable, and maintainable AI workflows.

Detailed Description

Full programme information can be found in the Module and Programme Catalogue

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