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Operation Research with Computational Optimization (MSc/PGDip)

Course Description

Programme description

This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Operational Research (OR) is an important skill that is in high demand.

This MSc will give an Operational Research perspective on computational optimization.

Programme structure

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses:

Computing for Operational Research and Finance
Fundamentals of Optimization
Fundamentals of Operational Research
Methodology, Modelling and Consulting Skills
Probability and Statistics
Stochastic Modelling

As part of your option course choices, Operational Research with Computational Optimization requires you to study a combination from:

Stochastic Optimization
Combinatorial Optimization
Nonlinear Optimization
Large Scale Optimization for Data Science.

Career opportunities

The skills you will learn are in demand by a vast range of high-profile organisations including consultancy firms, companies with operational research departments such as airlines or telecommunications providers, financial firms and the public sector.

Recent graduates have joined British Airways, the Government OR Service, Barclays, Deloitte, Capgemini and smaller specialised OR, finance and energy companies.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

Visit the Operation Research with Computational Optimization (MSc/PGDip) page on the University of Edinburgh website for more details!

Entry Requirements

At least a UK 2:1 degree, or its international equivalent, in a numerate discipline such as mathematics, engineering, computer science, physical or biological sciences, economics or business.

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