Data Science (MSc, PGDip)

In this conversion course you will learn how to interrogate existing data sets to solve problems and communicate your solutions with maximum visual impact to a range of audiences. Employers are looking for data scientists with arts and social sciences backgrounds as well as from the sciences. All you need is an interest in basic coding and maths skills. 

Course description

• The programme will suit you if you are keen to solve interesting real-world problems using a data-focussed approach, have effective communication skills and an interest in computer programming. You don’t need to have high level maths or computing skills to enrol on the programme, although if you have a degree in either mathematical sciences or computing you will be able to develop your specialist skills further.
• The programme requires a willingness to develop your understanding of mathematics and we will provide access to resources and a range of support to develop your skills. You will have access to materials tailored to the maths need of each module, either within the module teaching itself, for from other University resources such as our Centre for Academic Achievement.
• Similarly, we have resources to give you familiarity with Python and R, the two high-level computer languages used on the course. We will provide you with a suitable laptop to help you on your data journey.
• The programme will give you the skills to use cutting-edge data science tools to solve important problems in a wide range of areas (science, business, the arts and culture, government). The programme focus is just as much on the skills of creative and ethical problem solving as it is on developing technical skills.
• We recognise that all of us will need to work with artificial intelligence tools in the future, and for the benefit of humanity data science teams must include experts with a diverse range of skills, experience and background. Also, recent developments in programming tools coupled with intelligent use of AI assistance mean that it is not necessary to have a degree in computer science or mathematics to develop powerful data-driven solutions in a professional and ethical manner.
• Many data science models are already built wholly or partly by artificial intelligence. We’ll teach you to use the output of artificial intelligence tools (such as large language models like ChatGPT and modern program development environments) in an effective and professional way, enabling you to quickly design and implement data science workflows appropriate for a wide range of tasks. We place as much emphasis on choosing models that are appropriate for a particular circumstance and validating model outputs and auditing consequences of model use as on the coding for the model.
• These higher level skills are the ones most in demand by employers. We also recognise that in many applications complex machine learning models are not required: most of the work (and most of the value) is in cleaning, joining, and querying existing data sets, visualising the results, and communicating the information extracted in an impactful way.
• With this qualification, you could find yourself working in data journalism or museums, environmental NGOs, public services or businesses – there is a need for data scientists in every sector of the economy.

Careers and employability

• The leading employers for data scientists tend to be in the finance, retail and ecommerce sectors. Businesses in these sectors are keen to better understand their audience groups to target their focus on relevant products and offerings.
• However, there are opportunities in an increasingly wide range of jobs: recent adverts include posts in the arts and heritage (including the National Gallery), UNICEF, publishing and the UK Parliament. Jobs are also available with: government departments, NHS, universities and research institutes.
• The individual can be promoted to more senior data science roles within a given company, which may involve line management of junior data scientists. Promotion from junior to senior data scientist can take between two to five years.

Core modules

• Overview of Data Science Practice
• Fundamentals of Data Science
• Statistics for Data Science
• Modelling Data
• Information Visualisation
• Creative Problem Solving
• Data Science Research Project

Modules shown represent choices available to current students. The range of modules available and the content of any individual module may change in future years.

Teaching and learning

• Teaching will be a mixture of lectures, tutorials and computer-based practical classes. The emphasis will be on problem-based learning with a significant amount of activity being group work (including the final dissertation).