Data Science (Computer Science Data Informatics)

Entry requirements

High 2:1 honours degree (or overseas equivalent)

We require that all applicants have a strong background in Computer Science reflected, for example, in solid programming and software development skills. We typically expect a First or strong Upper Second class honours degree, or the overseas equivalent, in Computer Science, or in a joint degree with at least 50% Computer Science content. We may consider a lower proportion where a student has performed consistently strongly in their computer science modules. Applicants with extensive Computer Science industrial experience and an honours degree in Computer Science, or its overseas equivalent, may also be considered for admission.

In your application, you should demonstrate aptitude, knowledge and/or interest in three areas:

• data analytics and/or statistics;
• computational subjects; and
• pathway specific requirements.

These can be demonstrated by course units taken at undergraduate level and high school level, or professional experience.

Months of entry

September

Course content

Whether you’re trying to make sense of a football match, a general election or a business’ financial performance, data is vital. Our Data Science – Computer Science Data Informatics master’s will teach you invaluable skills for today’s economy such as:

• Data analysis
• Project design
• Computational methods
• Data stewardship.

This pathway focusses particularly on the data techniques and uses that are most relevant to computer science.

The course welcomes applicants from a range of STEM, business and humanities backgrounds. Working with the rest of your student cohort will enrich your understanding of the uses and potential of data.

Upon course completion, you’ll have developed a highly valued skillset, enhancing your employability across countless sectors.

Aims

This innovative MSc in Data Science course is an opportunity for graduates from a broad range of disciplines to develop data science skills.

Our goal is to help you develop into an agile, skilled data scientist, adept at working in a variety of settings and be able to meet the challenges and rewards of interdisciplinary teamwork.