- We are top in the UK for career prospects [Guardian University Guide 2018]
- 5th in the UK overall [Guardian University Guide 2018]
- 7th in the UK for student satisfaction with 98% [National Student Survey 2016]
- We are in the UK Top 10 for teaching quality [Times & Sunday Times University Guide 2017]
- 12th in the UK overall and Top in Wales [Times & Sunday Times University Guide 2017]
- 92% in graduate employment or further study six months after leaving University [HESA data 2014/15]
- UK TOP 20 for Research Excellence [Research Excellence Framework 2014]
- Our Project Fair allows students to present their work to local industry
- Strong links with industry
- £31m Computational Foundry for computer and mathematical sciences will provide the most up-to-date and high quality teaching facilities featuring world-leading experimental set-ups, devices and prototypes to accelerate innovation and ensure students will be ready for exciting and successful careers. (From September 2018)
- Top University in Wales [Times & Sunday Times University Guide 2017]
This programme aims to equip students with a solid grounding in data science concepts and technologies for extracting information and constructing knowledge from data. Students will study the computational principles, methods, and systems for a variety of real world applications that require mathematical foundations, programming skills, critical thinking, and ingenuity. Development of research skills will be an essential element of the programme so that students can bring a critical perspective to current data science discipline and apply this to future developments in a rapidly changing technological environment.
Large data sets are now available in almost all modern activities, and the ever growing amount of data requires new and innovative technologies and well equipped data scientists. The demand for data scientists in the UK has grown exponentially in recent years. Despite rapid expansion by the universities in the past few years, it has been predicted by multitude studies that the industry will continue to experience supply shortage of data scientists.
The programme focuses on three core technical themes: data mining, machine learning, and visualisation. Data mining is fundamental to data science and the students will learn how to mining both structured data and unstructured data. Students will gain practical data mining experience and will gain a systematic understanding of the fundamental concepts of analysing complex and heterogeneous data. They will be able to manipulate large heterogeneous datasets, from storage to processing, be able to extract information from large datasets, gain experience of data mining algorithms and techniques, and be able to apply them in real world applications. Machine learning has proven to be an effective and exciting technology for data and it is of high value when it comes to employment. Students will learn the fundamentals of both conventional and state-of-the-art machine learning techniques, be able to apply the methods and techniques to synthesise solutions using machine learning, and will have the necessary practical skills to apply their understanding to big data problems. We will train students to explore a variety visualisation concepts and techniques for data analysis. Students will be able to apply important concepts in data visualisation, information visualisation, and visual analytics to support data process and knowledge discovery. The students also learn important mathematical concepts and methods required by a data scientist. A specifically designed module that is accessible to students with different background will cover the basics of algebra, optimisation techniques, statistics, and so on. More advanced mathematical concepts are integrated in individual modules where necessary.
The programme delivers the practical components using a number of programming languages and software packages, such as Hadoop, Python, Matlab, C++, OpenGL, OpenCV, and Spark. Students will also be exposed to a range of closely related subject areas, including pattern recognition, high performance computing, GPU processing, computer vision, human computer interaction, and software validation and verification. The delivery of both core and optional modules leverage on the research strength and capacity in the department. The modules are delivered by lecturers who are actively engaged in world leading researches in this field. Students will benefit from state-of-the-art materials and contents, and will work on individual degree projects that can be research-led or application driven.