Data Science (MSc)

All organisations face the challenge of how to analyse and use data. On this course, you'll learn data science concepts and how to support data-driven approaches to problem-solving within complex organisational and societal contexts. 

Course description

• Gain an in-depth understanding of the theory and practice of data science and its application in different organisational contexts. You'll be provided with a set of fundamental principles that support ethical extraction of information and knowledge from data. Case studies will help to show the practical application of these principles to real life problems.
• The programme is centred on three key aspects of data science fundamental data-related principles, supporting infrastructures and organisational context.
• You'll gain practical skills in handling structured and unstructured data, analysing and visualising data, data mining, as well as gaining hands-on experience of software tools used and their use in real-world settings. You'll gain the skills of a data manager who understands what the algorithms (e.g., for data mining or handling ‘big data’) can do and when to use them for the benefit of the organisation.
• Throughout the programme, there will be opportunities to gain hands-on experience using a variety of tools, such as R, Python and SPSS, Weka or Tableau/Spotfire and, although you're not required to have any knowledge of these tools before starting the course, it may be advantageous to read up on them in advance. You'll conduct in-depth research into your particular areas of interest for your dissertation.

Applying for this course

• We are no longer using a staged admissions process for this course. You can apply for this course in the usual way using our Postgraduate Online Application Form.

Modules

• A selection of modules is available each year - some examples are below. There may be changes before you start your course.
• You’ll need 180 credits to get a masters degree, with 90 credits from core modules, 30 credits from optional modules and a dissertation (including dissertation preparation) worth 60 credits.

Core modules:

• Data Visualisation
• Introduction to Data Science
• Data Mining
• Data Analysis
• Data and Society
• Database Design
• Research Methods and Dissertation Preparation
• Dissertation

Optional modules - two from:

• Researching Social Media
• Information Governance and Ethics
• Big Data Analytics
• Business Intelligence
• User-Centred Design and Human-Computer Interaction

The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

Teaching

• A variety of teaching methods are used combining lectures from academic staff and professional practitioners with seminars, tutorials, small-group work, and computer laboratory sessions. There is a strong emphasis on new ways of exploiting data to support decision-making for a range of domains and problems in an organisational context. In addition to the taught components, you will be expected to engage in independent study, reading and research in support of your coursework.
• Teaching consists of two 15-week semesters, after which you'll write your dissertation.

Assessment

• Assessments are designed to test your grasp of the theoretical principles, technologies and frameworks used to collect, store, analyse and exploit data; they may include essays, report writing, oral presentations, in-class tests and group projects.
• There is a dissertation of 10-15,000 words, which provides you with the opportunity to focus in depth on a topic of your choice with one-to-one supervision. Opportunities exist for both project and dissertation studies to be carried out with our collaborating organisations, which can provide the opportunity to tackle real-life problems.

Your career
Examples of organisations that have employed our graduates include:

• Deloitte LLP
• Huawei Technologies
• National Institute for Health Research
• Financial institutions in the UK and overseas
• HMRC (HM Revenue and Customs)
• Nationwide Building Society
• Santander PLC
• Queen Mary University of London

Our graduates are employed in roles such as:

• Data Scientist
• Data Analyst
• Development Engineer
• Machine Learning Engineer
• Market Data Analyst
• Optimisation Analyst
• Project Management
• Service Consultant