Modern engineering, data science, and industrial systems increasingly rely on optimisation to make faster, smarter, and more robust decisions. From designing complex processes and allocating resources to managing uncertainty and building intelligent systems, optimisation provides the mathematical and computational foundation for achieving better outcomes. As the workhorse behind modern machine learning and AI, optimisation drives everything from neural network training and hyperparameter tuning to automated decision-making and large-scale industrial planning. 

This course highlights the central role optimisation plays across engineering, data science, and machine learning, combining strong theoretical foundations with practical, hands-on experience. Participants will learn how modern optimisation techniques can be used to solve real-world problems, improve performance, and unlock more efficient and intelligent solutions across research and industry. 

Cancellation policy 

Written cancellations received by Monday 17 August 2026 are eligible for a partial refund (80%). No refunds will be given after Monday 17 August 2026. 

Substitutions may be made at any time, whilst a valid place is held. The organiser cannot accept liability for costs incurred in the event of a course having to be cancelled as a result of circumstances beyond its reasonable control.