Data Science and Analytics
Transform information into insight
The demand for expertise in managing and interrogating big data sets to improve decision-making, drive policy and make scientific breakthroughs, far outstrips supply.
Data Science at the University of Exeter, offers a broad range of programmes that equip students with both the technical skills to understand, manage and store large data sets together with the flexibility to apply powerful analytics to data across any area of industry, business or field of research.
Our nexus of researchers, educators and students from across all disciplines work alongside a variety of private and public sector organisations, towards the common goal of harnessing the power of data to transform information into insight.
Our educational programmes are tailored to meet the needs of students with specific career trajectories, while providing exciting opportunities for joint project work and collaboration with industry.
This inter-disciplinary course is suited to anyone wishing to gain a practical understanding of Data Science and its applications for a variety of industries. Teaching covers the fundamental mathematical and computational techniques used to deliver insights and gain insights from data sources. You will learn to handle complex data sets, learning multiple methods of analysis and efficient approaches to visualisation and presentation. You will also study social contexts, governance and ethical considerations.
The degree blends our core MSc in Data Science with optional modules in Strategy, Accounting, Leadership and Operations. These modules are taught by the University’s Business School.
This professional programme has been designed in partnership with world leading, global data companies and is uniquely taught at their offices in the UK and overseas. Featuring intensive week-long residentials, this programme is ideal for working professionals, enabling graduate level career development, without the risk of leaving your job. A strong coding and technical background is essential for this programme.
Training in the interrogation and interpretation of large data sets with a focus on how these insights can be applied to global uncertainties and societal/policy challenges, with opportunities to specialise in public policy, social research, criminal justice and security. Students will typically come from a social sciences or humanities background.
Our specialist facilities and support include:
- High powered computing infrastructure
- Linux & Ubuntu operating systems & dedicated servers
- Python & R for coding
- R for data handling and analysis
- Computer lab, shared facilities and tools for our Data Science community
Our specialists have a broad range of expertise, both in computing and applied data analysis. Our data science expertise includes machine learning, statistical pattern recognition, multi objective optimisation, computational statistics and applied statistical modelling.
We have particular strengths in
- computer vision
- social network analysis
- text and image analysis
- open source databases and metadatabases
- statistical solutions
- data handling
- hypothesis testing and inference.
Applied Data Analysis
Our academics have applied these techniques to generate insights across a wide variety of disciplines including policy, health, economics, biotechnology, citizen science, big data, environmental monitoring, sport and neuroscience.
Our external partners include private and public sectors organisations such as:
- Met Office – big data storage
- Evolva – biotechnology development
- Natural England – modelling and analysis for the reintroduction of species
Centres of excellence
The University has a number of centres of excellence, bringing together data scientists, students and business partners to focus on particular areas of expertise.
Centre for Biomedical Modelling and Analysis - brings together scientists from quantitative disciplines including mathematics, computer science and physics with those from biology, biomedicine and clinical sciences to enable breakthroughs in biomedical and clinical research
Q-Step Centre for Applied Data Analysis - integrates the use of cutting-edge quantitative methods with the study of substantive issues. Students learn by observing and engaging in real data-analysis with an innovative and hands-on approach. Offers data analysis workshops and work placements.
Centre for Ecology and Conservation – ecologists, evolutionary biologists and conservation biologists join forces to solve the key issues of environmental change, biodiversity and natural capital, and the modern extinction crisis.
Bioinformatics hub - a team of data experts in bioinformatics, metabolomics and proteomics, tomography and image analysis, computing and statistics. The team provides analytical support for biomedical research and a range of training.
Big Data is the world's natural resource for the next century, but it’s nothing unless you refine it.
Data is going to be the basis of competitive advantage, but it’s not the data alone, it’s the analytics around it.
Ginni Rometty, CEO, IBM