Data Science for Cultural Heritage MSc

London, Bloomsbury and London, Hackney Wick (Here East)

UCL's Data Science for Cultural Heritage MSc provides an innovative opportunity to study data science through the exciting lens of cultural heritage. It is the first MSc in the world to provide in-depth, practice-based data science training in a cultural heritage context. The MSc will equip you to succeed as a data scientist in fields such as heritage science, the built environment, digital technologies and media, analytics, and software.

UK students International students
Study mode
UK tuition fees (2022/23)
£16,500
£8,250
Programme fees on a modular (flexible) basis.
Overseas tuition fees (2022/23)
£29,400
£14,700
Programme fees on a modular (flexible) basis.
Duration
1 academic year
2 academic years
5 academic years
Programme starts
September 2022
Applications accepted
All applicants: 18 Oct 2021 – 31 Mar 2022

Applications open

Entry requirements

A minimum of a second-class UK Bachelor's degree from a UK university or an overseas qualification of an equivalent standard is required. This MSc is highly interdisciplinary. You will have a background in engineering, computer science, applied mathematics or other related science and want to apply these skills within cultural heritage. Alternatively, you might have a background in arts, culture, or heritage and want to develop technical skills in data science.

English language requirements

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

The English language level for this programme is: Good

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level. International Preparation Courses

Further information can be found on our English language requirements page.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

This programme pioneers a new way of teaching data science through application in a cross-disciplinary context. You will explore the complexities of acquisition, analysis and exploitation of the variety of data that is generated and used in heritage contexts. You will develop advanced data science skills, such as crowd sourced data science, machine learning or imaging data analysis.

Who this course is for

This course is highly interdisciplinary. You will have a background in engineering, computer science, applied mathematics or other related science and want to apply these skills within cultural heritage. Alternatively, you might have a background in arts, culture, or heritage and want to develop technical skills in data science.

What this course will give you

From historic buildings and sites to museums, cultural heritage provides an exciting and complex setting to learn and apply data science through real applications that combine science and engineering with social sciences and humanities.

This cross-disciplinary programme will give you a balance of advanced data science skills and active learning experience.  You will gain valuable transferrable skills, such as communication and interdisciplinary collaboration. These skills are in high demand in many industries and sectors.

This Master'¿s has been developed and delivered by leading academics at the UCL Institute for Sustainable Heritage, in collaboration with UCL Department of Statistical Science.

To ensure the programme is industrially relevant, we have an advisory board. Members of our advisory board come from major national and international institutions including the Turing Institute, British Library, ARUP, and Historic England. They also contribute your teaching and supervision, as well as providing datasets and research ideas.

UCL Institute for Sustainable Heritage is part of The Bartlett School of Environment, Energy and Resources, home to specialist institutes in energy, environment, resources and heritage. The Bartlett Faculty brings together scientific and professional specialisms required to research, understand, design, construct and operate the buildings and urban environments of the future.
 

The QS World University Rankings (2021) ranks The Bartlett, our faculty, as #1 for Architecture/Built Environment studies in the UK and #2 in the World. The Bartlett's research received the most world-leading ratings for research on the Built Environment in the UK in the most recent Research Excellence Framework.

The foundation of your career

Transdisciplinarity, an applied focus, an emphasis on innovation and 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.

You will develop advanced data science skills, as well as many transferrable skills such as coding, presentation and communication skills, working with different stakeholders, problem contextualization or public engagement techniques.

Employability

Data science is in high demand in many and diverse industries. As a graduate of MSc DaSCH you will be ideally placed to gain employment as a data scientist, in particular in those sectors that foster transdisciplinarity and break barriers between technology and humanities or social sciences.

The programme has been developed with input from industry leaders from a diversity of sectors, including architecture, heritage, social media and digital technologies. You will gain exposure to real data challenges from these industries and will develop skills in data science that are highly transferable across these and many other sectors. Additionally, you will also develop skills as a researcher which will prepare you for a career in academia should you be interested.

Teaching and learning

The programme is taught using various strategies including lectures, tutorials, problem-based learning, project work, coursework and reports.

You will get hands-on experience working with realistic data-sets and within heritage contexts, which will include field trips.

Skills-based learning will be delivered through small-group exercises promoting peer-to-peer learning and learning through research.

A Postgraduate Diploma of five compulsory modules (75 credits) and three optional modules (45 credits) is offered.

Modules

Full-time

The MSc Data Science for Cultural Heritage will comprise four broad learning streams: the cultural heritage context, data science for cultural heritage, specific data skills, and research skills. You will take taught modules worth a total of 120 credits and a dissertation worth 60 credits.

1) You will take a compulsory foundation module alongside students from other Masters programmes at ISH. You will explore the heritage context within a truly multidisciplinary environment, providing a theoretical framework for the concepts of heritage and heritage values. A number of dedicated sessions will focus on Heritage Data Typologies and will explore the types of heritage data, understood as data as and for heritage, as well as the role of data in the heritage context and its potential as part of future cultural heritage. This will allow you to explore how the types of data that are used for heritage documentation, are required to manage heritage institutions or visitor engagement, or are stored as part of future cultural heritage.

2) Following this, you will undertake compulsory modules through which you will acquire data science skills within a cultural heritage context, including data analysis, and data mapping and visualization.

3) You will take three optional skills-based modules each focusing on particular techniques of heritage data acquisition and analysis.

4) To complete the taught modules, you will undertake one additional compulsory module in heritage data analysis and mapping, storage, repurposing, use and preservation. This will draw on the data and techniques explored in previous modules.

5) You will complete a dissertation module (60 credits). 

Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability is subject to change.

Students undertake modules to the value of 180 credits, comprising 120 taught credits and a 60-credit dissertation. Upon successful completion of 180 credits, you will be awarded an MSc in Data Science for Cultural Heritage. Upon successful completion of 120 credits, you will be awarded a PG Dip in Data Science for Cultural Heritage.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk. Further information can also be obtained from the UCL Student Support & Wellbeing team.

Online - Open day

Graduate Open Events: Applying for Graduate Study at UCL

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2022/23) £16,500 £8,250
Tuition fees (2022/23) £29,400 £14,700

Programme fees on a modular (flexible) basis.

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees.

Additional costs

You will require your own laptop. Recommended specifications can be provided on request.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Funding your studies

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

Any additional funding is offer by our faculty, The Bartlett, are advertised on their scholarships page.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Scholarships relevant to this department are displayed below.

Bartlett Promise Scholarship - Master's

Applications Open: 1 March 2022. Deadline: 31 May 2022
Value: Tuition fees plus £15,364 maintenance/yr (Duration of programme)
Criteria Based on financial need
Eligibility: UK

Next steps

There is an application processing fee for this programme of £90 for online applications and £115 for paper applications. Further information can be found at Application fees.

When we assess your application we would like to learn:

  • why you want to study Data Science for Cultural Heritage at graduate level
  • why you want to study Data Science for Cultural Heritage at UCL
  • what particularly attracts you to the chosen programme
  • how your academic and professional background meets the demands of this challenging programme
  • where you would like to go professionally with your degree

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.

Please note that you may submit applications for a maximum of two graduate programmes in any application cycle.

We recommend that you submit your application as soon as possible. The programme may remain open if places are still available after 31 March 2022 and will be closed as soon as it is full or by 30 June 2022.

UCL is regulated by the Office for Students.

This page was last updated 28 Sep 2021