Bachelor of Science in Data Science and Analytics University of Essex - Colchester Campus, UK

Data is the lifeblood of our society. From medicine to government offices, and market research to the environment, the collection and analysis of data is crucial to understanding how to improve, create and guide products and services across the globe.

Harvard Business Review recently described the job of Data Scientist as “the sexiest job of the 21st century”. Data science is about doing some detective work and carrying out the investigations needed to inform important decisions and to predict new trends. Technology is growing and evolving at an incredible speed, and both the rate of growth of data we generate and the devices we use to process it can only increase.

At Essex, we help you to understand how utilising the speed and processing-power of computers can assist in using data to make better decisions. You discover the new methods and the smart, unusual questions needed to make sense of both numerical and textual data. Your course balances solid theory with practical application through exploring topics including:

• Mathematical skills
• Computer science and programming
• Statistics and operations research
• Artificial intelligence, databases and information retrieval
• Ethical issues around the use and processing of data
• Specialist skills in the areas of big data, data analytics and data science

A successful career in data science requires you to possess truly interdisciplinary knowledge, so we ensure that you graduate with a wide-ranging yet specialised set of skills in this area. You are taught within our Department of Mathematical Sciences and our School of Computer Science and Electronic Engineering.

Data scientists are required in every sector, carrying out statistical analysis or mining data on social media, so our course can open the door to almost any industry, from health, to government, to publishing.

Our Department of Mathematical Sciences is genuinely innovative and student-focused. Our research groups are working on a broad range of collaborative areas tackling real-world issues. Here are a few examples:

• Our data scientists carefully consider how not to lie, and how not to get lied to with data. Interpreting data correctly is especially important because much of our data science research is applied directly or indirectly to social policies, including health, care and education.
• We do practical research with financial data (for example, assessing the risk of collapse of the UK’s banking system) as well as theoretical research in financial instruments such as insurance policies or asset portfolios.
• We also research how physical processes develop in time and space. Applications of this range from modelling epilepsy to modelling electronic cables.
• Our optimisation experts work out how to do the same job with less resource, or how to do more with the same resource.
• Our pure maths group are currently working on two new funded projects entitled ‘Machine learning for recognising tangled 3D objects’ and ‘Searching for gems in the landscape of cyclically presented groups’.
• We also do research into mathematical education and use exciting technologies such as electroencephalography or eye tracking to measure exactly what a learner is feeling. Our research aims to encourage the implementation of ‘the four Cs’ of modern education, which are critical thinking, communication, collaboration, and creativity.