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MSc Built Environment: Sustainable Heritage (Data Science)

  • DeadlineStudy Details:

    MSc 1 year full-time, 2 years part-time, 5 years flexible

Course Description

Digital technologies and data have a fundamental role in contemporary society, and cultural heritage is no exception. From historic buildings, sites, landscapes, museums and collections, the world of heritage provides an exciting setting to learn and apply data science skills. This Master’s degree route creates expert data scientists taught through the exciting multidisciplinary lens of cultural heritage.

The opportunities for using data science in different contexts are vast. Employers from increasingly diverse sectors now require people with skills in a range of state-of-the-art methods and technologies to understand, manage and exploit data. This degree pioneers a new way of teaching data science through application in the cross-disciplinary context of cultural heritage.

As a student on the Data Science route of the Sustainable Heritage MSc you will develop advanced data science skills, such as coding, crowd-sourced data science, machine learning and data visualisation. You will explore the complexities of acquisition, analysis and exploitation of the variety of data that is generated and used in heritage contexts, including data generated through analysis and measurement, imaging and surveying, citizen science, and digitally born data.

Entry Requirements

Normally a minimum of a second-class Bachelor’s degree from a UK university or an overseas qualification of an equivalent standard. Applicants with degrees of a lower classification but with considerable senior-level professional experience may also be accepted. Please note that a special qualifying examination may be set.

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Fees

For fees and funding options, please visit website to find out more.

Programme Funding

UCL offers a range of financial awards aimed at assisting both prospective and current students with their studies.

Student Destinations

This degree route has been developed with input from industry leaders from a diverse range of sectors, including architecture, heritage, social media and digital technologies. You will gain exposure to real data challenges from these industries to develop a skill-set in data science that will be highly transferable across these and many other sectors.

An applied focus and an emphasis on innovation, along with crossdisciplinarity, critical thinking, are the key qualities that will define the professional character of our graduates and will make you stand out from other data scientists.

There is an opportunity to work closely with a heritage organisation or practice during the route which is facilitated through the professional networks of the academic staff, including our guest lecturers, many of whom come from prestigious heritage organisations.

Module Details

Compulsory modules

  •  Dissertation: Sustainable Heritage
  •  Heritage Data Mapping and Visualisation
  •  Machine Learning for Heritage
  •  Introduction to Sustainable Heritage
  •  Policy Advice and Evidence for Heritage
  •  Statistics for Heritage Science
  •  Sustainable Heritage in Practice
  •  Introduction to Statistical Data Science

Optional modules

  •  Strategies for Sustainable Heritage Buildings and Collections
  •  Strategies for Sustainable Heritage Landscapes
  •  Crowd-Sourced and Citizen Data for Cultural Heritage
  •  Climate Change and Heritage
  •  Inclusive Urban Heritage

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