12 monthsProgramme duration
39,600 GBPTuition Fee/year
SepStarting Month
Programme overview
Main Subject
Architecture and Built Environment
Degree
MSc
Study Level
Master's
Study Mode
On Campus
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.
You develop advanced data science skills, such as coding, crowd-sourced data science, machine learning and data visualisation. You also 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.
Data science underpins much of modern science. By examining the topic through the lens of cultural heritage, we emphasise the human side of data science. Studying and applying data science methods to heritage helps you develop a broader with the ability to consider the needs of users, the public and a broad range of stakeholders, alongside the more technical aspects of data science.
Programme overview
Main Subject
Architecture and Built Environment
Degree
MSc
Study Level
Master's
Study Mode
On Campus
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.
You develop advanced data science skills, such as coding, crowd-sourced data science, machine learning and data visualisation. You also 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.
Data science underpins much of modern science. By examining the topic through the lens of cultural heritage, we emphasise the human side of data science. Studying and applying data science methods to heritage helps you develop a broader with the ability to consider the needs of users, the public and a broad range of stakeholders, alongside the more technical aspects of data science.
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