Our MSc Data Science programme is designed by the School of Computer Science and the School of Mathematical Sciences to provide students with advanced computational and mathematical skills to tackle increasingly complex data analysis tasks and devise methods for analysing, presenting, and deriving insights from large data sets.
Opportunities for data driven innovation have been broadly recognised by industry, public sector and different scientific fields. As a data scientist, you will be able to work on a wide range of problems, analysing complex and diverse collections of data.
This course offers multiple pathways, preparing you for a highly-skilled career in industry or research.
If you have a background in computer science or mathematical sciences, this course provides a selection of advanced modules that can ensure your further growth.
If you have a background in other subjects, the course provides a selection of modules that enable you to acquire knowledge in mathematics and computer science starting with required fundamentals.
The subjects you will cover reflect the ongoing research and practices in data analytics and computation undertaken at both schools:
- statistical modelling and inference
- uncertainty quantification
- multivariate statistics
- time-series and forecasting
- machine learning
- advanced algorithms and data structures
- data modelling and analysis
- simulations and optimisation for decision support
- parallel and distributed computing
The course aims to bring you to the forefront of research and application methods, equipping you to take leading roles with demands of principled and theoretically sound approaches to problem solving by leveraging state-of-the-art computation techniques.
You can pursue one of four different pathways, depending on your background in computer science and mathematical sciences. You can take a selection of modules suitable for students with strong computer science background or an alternative one, and similarly, you can chose a selection of modules for students with strong mathematical sciences background or an alternative one.