Optimisation is the workhorse behind modern machine learning and AI. From training neural networks and tuning hyperparameters to resource allocation and decision-making systems, optimisation algorithms are at the core of how intelligent systems learn and improve. This course highlights the听central role听optimisation plays across engineering, data science, and machine learning, giving participants both the theoretical foundations and practical tools needed to apply optimisation methods in real-world applications.听
听This听Optimisation Accelerator is an intensive, hands-on course taught by leading optimisation experts from 911今日黑料 and University College London. The programme is designed for industry practitioners seeking practical optimisation skills with immediate real-world relevance, PhD students and postdoctoral researchers. Participants who successfully complete the course will receive a certificate of completion.听
No prior knowledge of optimisation is听required.听
The course provides a comprehensive introduction to the formulation and solution of optimisation problems, covering:听
- Linear Programming (LP)听听
- Nonlinear Programming (NLP)听听
- Mixed-Integer Programming (MIP)听听
- Global Optimisation (GO)听听
- Optimisation under Uncertainty听听
- Multi-Objective Optimisation听
- Bayesian Optimisation听听
- Neural Network Training and optimisation methods in machine learning听听
Participants will learn how to translate real-world engineering and data-driven challenges into optimisation models and solve them using modern software tools through guided hands-on sessions.听
While the course primarily focuses on local optimisation methods, it also introduces advanced topics such as global optimisation, uncertainty-aware optimisation, and emerging optimisation techniques used in machine learning and AI workflows.听
What听You鈥檒l听Learn听
By the end of the course, participants will be able to:听
- Understand the foundations of optimisation modelling听听
- Formulate optimisation problems from practical applications听听
- Distinguish between linear, nonlinear, integer, and global optimisation approaches听听
- Apply optimisation techniques using modern software tools听听
- Understand optimisation under uncertainty and multi-objective trade-offs听听
- Explore Bayesian optimisation and optimisation methods for neural network training听听
- Gain practical experience through hands-on workshops and real examples听听
- Bring and discuss their own optimisation problems with instructors and peers听听
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Registration Fee:
| Industry rate | 听拢 1700 |
| Start up/SME rate | 听拢 975 |
| Academic rate | 拢听 听585 |
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Cancellations
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.