Machine Learning for Industrial Transformation and Innovation

This module is a graduate treatment of how Artificial Intelligence (AI) and Machine Learning (ML) power the shift towards data-driven, autonomous and adaptive decision-making in Industry 4.0 systems. Modern decision-support architectures that leverage intelligent algorithms have the flexibility to collect and analyze information that is relevant to the decision-making situation, offer personalized advice, recommend an optimal beam of actions and adjust to a rapidly changing environment. From expert systems and tree-inductive techniques to natural language processing and evolutionary computation, this module offers an integrated approach to decision analysis based on the principles of AI. Students will study modern decision-support systems suitable for critical business areas where AI is transforming professional practice, including smart manufacturing, production planning, asset management, energy systems and intelligent infrastructure. By completion, students will gain a deep understanding of the functionality and comparative advantages of modern AI techniques over classical operations research methods and will be able to identify and explore potential synergies between the two - often perceived as opposing- approaches to decision-making. The acquired knowledge and hands-on experience will enable participants to design intelligent, adaptive, and data-driven solutions that can meet contemporary and future industrial challenges.