Operational Research with Data Science
With the explosion of data available to analyse a vast range of activities, there is a growing demand for novel techniques and the ability to handle ever larger data sets. Many existing techniques lie naturally within areas of computational optimization and operational research.
The Operational Research with Data Science programme gives an opportunity to study these areas via the fundamentals of optimization and operational research and a range of optional courses in optimization, statistics, and data science.
The School's Optimization and OR group has worked on data science applications for many years and this is expected to develop with the School's role in the Alan Turing Institute and the increasingly data-driven world at large. Students of the OR with Data Science degree will benefit from being part of this rich environment.
Applications can now be made to study in 2019-20. Note that for entry to this programme, at least one course at university level in programming and in probability and statistical theory is essential.
In Semester 1, students must choose a certain number of credits from a given set of themed courses which, previously, has been 30 credits from the following courses
- Simulation (10 credits),
- Statistical Methodology (10 credits)
- Object-Oriented Programming with Applications (10 credits)
- Statistical Programming (10 credits)
- Incomplete Data Analysis (10 credits)
- The Analysis of Survival Data (10 credits)
- Machine Learning and Pattern Recognition (20 credits)
- Introductory Applied Machine Learning (20 credits)
- Bioinformatics 1 (10 credits )
In Semester 2, students must choose a certain number of credits from given sets of themed courses.