Data Science (Urban Analytics)

Entry requirements

High 2:1 honours degree (or overseas equivalent)

For this pathway, we would expect applicants to evidence an interest and/or experience in topics related to urban analysis. Examples are:

• Working experience in urban-themed topics (e.g. data analyses for spatial phenomena, public policies or real estate market analysis)
• Experience in working in spatial or GIS-based data analysis
• Evidence of training in urban-themed methods or topics (e.g. GIS).

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 – Urban Analytics 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 urban analytics, with optional course units exploring themes like land use, property valuation and town planning.

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.

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 of interdisciplinary teamwork.