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The Bartlett Centre for Advanced Spatial Analysis

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Programme overview

The Spatial Data Science and Visualisation MSc teaches cutting-edge data analysis, mining, modelling and visualisation techniques for spatial systems. Students carry out their own research project, supported by academics, researchers and other students in one of the most exciting, interdisciplinary research teams in the field. The programme takes place within The Bartlett, UCL's Faculty of the Built Environment.

Key information

Programme starts

September 2018

Modes and duration

Full time: 1 year
Flexible: up to 5 years

Tuition fees (2018/19)

UK/EU:
£14,180 (FT)
Overseas:
£25,880 (FT)

Application dates

All applicants
Open: 16 October 2017
Close: 27 July 2018

Note on fees: The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Current Students website.

Location: London, Bloomsbury

Entry requirements

A minimum of a second-class Bachelor's degree in a relevant discipline from a UK university, or an overseas qualification of an equivalent standard.

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: Standard

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

International students

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.

Select your country:

About this degree

Students gain a grounding in the principles and skills of spatial research, data analysis and visualisation, agent-based models and virtual environments, and develop an understanding of research methodology for data collection and analysis. Subject-specific modules provide students with the opportunity to develop skills in spatial analysis and to contribute to current debates in the field. They will learn programming skills in Java/Processing, Python, R, JavaScript and SQL, and the ability to use a range of interactive geospatial and visualisation tools (ArcGIS, Unity, Mapbox and CityEngine).

The programme consists of four core modules (60 credits), a group mini-project (30 credits), two elective modules (30 credits), and a dissertation (60 credits).

Core modules

The core modules focus on technical skills, leading to applications in mapping, visualising and analysing spatial data.

  • Data Science for Spatial Systems
  • Geographic Information Systems and Science
  • Introduction to Programming
  • Quantitative Methods
  • Group Mini Project: Digital Visualisation

Elective modules

Students select two elective modules from a wide range available at UCL, subject to approval.

Dissertation/report

All students submit a dissertation of 10-12,000 words.

Teaching and learning

The programme is delivered through a combination of lectures, seminars, tutorials and practical-based workshops and classes. The interlinked laboratory research-based mini project with data collection focuses on ‘remote data mining’ rather than fieldwork in the traditional planning/geographical/architectural sense. Assessment is through group and individual projects and the dissertation.

Further information on modules and degree structure is available on the department website: Spatial Data Science and Visualisation MSc

Funding

Scholarships relevant to this department are displayed below.

Bartlett Masters Scholarship

Value:
£10,000 (1 year)
Eligibility:
UK, EU, Overseas
Criteria:
Based on financial need

Brown Family Bursary

Value:
£15,000 (1 year)
Eligibility:
UK
Criteria:
Based on both academic merit and financial need

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

Careers

Recent graduates of our related Spatial Data Science and Visualisation MRes have gone on to work as developers, in spatial analysis, and a number have continued to PhDs. Through our PhD partners, Knowledge Transfer Partnerships and substantial outreach, graduates will be able to take advantage of CASA's links to the world outside academia.

Employability

The Spatial Data Science and Visualisation MSc provides a unique skill set in computation mapping, visualisation and spatial research. Research-led skills are increasingly a key element in our understanding of complex spatial functions, particularly as vast amounts of previously unused data are becoming available either from changes in accessibility regulation or more widely as a result of new mass data collection methodologies.

Why study this degree at UCL?

The Centre for Advanced Spatial Analysis (CASA) is a research centre specialising in computational and mathematical approaches, with cutting-edge research in GIS, urban simulation, mapping, data visualisation, and 3D environments in cities and space.

Students on this programme will be exposed to a range of programming languages (Java/Processing, R, Python and MySQL), 3D visualisation packages, and be given a substantive grounding in GIS, programming structure, mathematical methods and data design.

The combination of skills involved in this programme is unique – graduates will be able to lead institutions and companies in new directions and be involved in changing cultures across the sector.

Department: Centre for Advanced Spatial Analysis

Student / staff numbers › 17 staff including 11 postdocs › 55 taught students › 19 research students
Staff/student numbers information correct as of 1 August 2017.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

The following REF score was awarded to the department: Centre for Advanced Spatial Analysis
81% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.

Application and next steps

Applications

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

Application fee: There is an application processing fee for this programme of £75 for online applications and £100 for paper applications. More details about the application fee can be found at www.ucl.ac.uk/prospective-students/graduate/taught/application.

Who can apply?

The programme is ideal for people interested in creating visualisations, maps, analyses and models to understand spatial systems. Our students come from both humanities and social and physical science backgrounds, from areas including geography, architecture, planning, software development, philosophy and landscape architecture.

The programme has computational and technical elements, but we do not require computing qualifications for entry; just enthusiasm and the desire to learn.

Application deadlines

All applicants
27 July 2018

For more information see our Applications page.

Apply now

What are we looking for?

When we assess your application we would like to learn:

  • why you want to study Spatial Data Science and Visualisation at graduate level
  • why you want to study Spatial Data Science and Visualisation 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.

Contact information

Page last modified on 12 February 2018 by UCL Student Recruitment Marketing