Skip navigation
Data Science at University of Essex - UCAS

There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. 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. Data science is a growing and important field of study with a fast-growing number of jobs and opportunities within the private and public sector. The application of theory and methods to real-world problems and applications is at the core of data science, which aims especially to use and to exploit big data. If you are interested in solving real-world problems, you like to develop skills to use smart devices efficiently, you want to use and to foster your understanding of mathematics, and you are interested and keen to use statistical techniques and methods to interpret data, MSc Data Science at Essex is for you. You study a balance of solid theory and practical application including:

  • Computer science
  • Programming
  • Statistics
  • Data analysis
  • Probability
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 mainly within our School of Mathematics, Statistics and Actuarial Science and our School of Computer Science and Electronic Engineering, but also benefit from input from our Essex Business School, and our Essex Pathways Department. 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 School of Mathematics, Statistics and Actuarial Science 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.
This course is available as either a full-time degree over one academic year, or as a part-time degree over two academic years. This course is aimed at candidates with a background in a mathematical or computational discipline. Candidates without strong programming and statistical skills are encouraged to consider our conversion course MSc Data Science and its Applications. Candidates wishing to convert from a non-STEM background are encouraged to consider MSc Applied Data Science.

Modules

You can tailor your learning experience with a choice of optional modules. More information about these can be found on the University of Essex website


Entry requirements

Entry requirements for this course can be found on the course finder on the University of Essex website – www.essex.ac.uk


Fees and funding

Tuition fees

England £10000 Year 1
Northern Ireland £10000 Year 1
Scotland £10000 Year 1
Wales £10000 Year 1
Channel Islands £10000 Year 1
Republic of Ireland £10000 Year 1
EU £21700 Year 1
International £21700 Year 1

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

Fees displayed are for 2024-25 entry. Fees for part-time courses are calculated pro-rata to the relevant full-time fee. Tuition fees may be subject to annual increases in each year of study in line with inflation.
Data Science at University of Essex - UCAS