Overview

Data is everywhere. As the volume and complexity of data collected continues to grow, there is increasing demand for expertise in data science to support the analysis and visualisation of all this information.

Gaining useful insights from data involves logical thinking, technical skills and deep knowledge of the domain the data comes from. Graduates from Law, Finance, Marketing, Business, Creative Arts, Social Sciences, Linguistics, Health Sciences, Sports Science, Psychology, Geography, Biological Sciences and Engineering (to name a few) are best placed to analyse data from their own discipline and bring a unique perspective (and set of questions) to a data science team.

The MSc Data Science is designed to support students with little previous experience of data analysis or computer programming to gain new skills such as working with databases; statistical thinking; programming in high-level languages; modelling; applying data science tools and packages; machine learning; information retrieval; data visualisation; and addressing the challenges of big data.

These complement existing knowledge and skills from your undergraduate study or work experience, such as formulating questions, building arguments, writing reports, delivering presentations, creative problem solving, and a curiosity about data. Features of the course include working with other students with different backgrounds, experience and perspectives, and gaining broad experience of working with a variety of types of data to address diverse and interesting questions.

Course information

Data Science is a broad multidisciplinary field encompassing everything from cleaning and managing data to data visualisation and deploying predictive models.

The course supports students from diverse backgrounds to develop the necessary foundations of data science in computer programming, data analysis and statistical thinking, before building more specialised knowledge and skills in information retrieval, data management, machine learning, and the technological challenge of dealing with big data. Throughout the course there are many opportunities for you to build on your existing knowledge and experience from your undergraduate degree or workplace, and gain experience in the analysis of data of a variety of kinds and sizes.

The course maintains a balance between hands-on technology-dependent practical skills using modern software, knowledge and understanding of specialist methods and algorithms in learning from data, mathematical language and foundations, and broader issues around data ethics, data protection and communication with stakeholders of all kinds. In particular, the course covers: programming and software development in a high-level programming languages such as Python and R; data analytics, statistical modelling and programming with data; mathematical foundations of data science such as modelling, linear algebra, and probability; data management systems for structured and unstructured data; big data management, distributed databases and data visualisation; information retrieval and analysis of textual data; machine learning algorithms for learning from data; and a range of data science applications, tools, projects and current issues.