A minimum of a second-class UK Bachelor's degree from a UK university or an overseas qualification of an equivalent standard is required.
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: Standard.
Further information can be found on our English language requirements page.
Months of entry
The Data Science for Cultural Heritage MSc (DSCH) provides an innovative opportunity to study data science through the exciting lens of cultural heritage. It is the first MSc to provide in-depth, practice-based data science training in a cultural heritage context, and aims to broaden the horizons of data science. The MSc will equip you to succeed as data scientist in diverse fields such as marketing, architecture, construction or media, as well as heritage and many more.
From historic buildings and sites to museums, cultural heritage provides an exciting 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, active learning experience and valuable cross-cutting and transferrable skills, including communication and interdisciplinary collaboration, that are in high demand in many industries and sectors.
Developed and delivered by leading academics at the UCL Institute for Sustainable Heritage, in collaboration with UCL Department of Statistical Science, industry and major national and international heritage institutions.
Fees and funding
Please see UCL website for full information about fees and costs for this programme.
Qualification and course duration
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.
Course contact details
- +44 (0)20 3370 1214