Spatio-temporal Analytics and Big Data Mining MSc

Options: PG Diploma


With the rapid development of smart sensors, smartphones and social media networks, spatio-temporal “big” data is more ubiquitous and richer than ever before. This new MSc is the only programme of its kind designed to meet the needs of professionals when dealing with large and complex spatio-temporal datasets in order to understand the space-time complexity in transport, security, mobility, health and resilience.


Mode of study

  • Full-time 1 year

Tuition fees

  • UK/EU Full-time: £10,450
  • Overseas Full-time: £21,700

Application date

  • All applicants: 1 August 2014

More details in Application section.


What will I learn?

Students will become familiar with the computational foundations of spatio-temporal analytics and data mining as well as acquiring the essential skills needed for dealing with big spatio-temporal data, including retrieving and mining big (open) data, web services and cloud computing systems, data management and cyber infrastructure, and web and mobile applications.

Why should I study this degree at UCL?

As one of the world’s top universities, UCL excels across the physical and engineering sciences, social sciences and humanities.

Spanning two UCL faculties, this interdisciplinary programme exploits the complementary research interests and teaching programmes of three departments (Civil, Environmental & Geomatic Engineering, Computer Science, and Geography).

Students on the Spatio-Temporal Analytics & Big Data Mining programme will be part of a vibrant, enthusiastic, and international research environment in which collaboration and free-ranging debate are strongly encouraged.


Students undertake modules to the value of 180 credits. The programme consists of 6 core modules (90 credits), 2 optional modules (30 credits) and a dissertation/report (60 credits).

A Postgraduate Diploma (120 credits) is offered.

Core Modules

  • GIS Principles and Technology
  • Mapping Science
  • Principles of Spatial Analysis
  • Spatial Data Management
  • Spatio-temporal Analysis and Data Mining
  • Web and Mobile GIS

Choose two options from the following:

  • Representations, Structures and Algorithms or Complex Networks and Web
  • Geographic Information System Design or Information Retrieval and Data Mining

Dissertation/report

All students undertake an independent research project which culminates in a dissertation of 15,000 words.

Teaching and Learning

The programme is delivered through a combination of lectures, seminars, and lab practicals. Assessment is through examination, coursework, practicals, disssertation, and poster presentation.

Further details available on subject website:


Scholarships available for this department

Commonwealth Shared Scholarship Scheme (CSSS)

This scholarship is to assist prospective Master's students from developing Commonwealth countries who are of excellent academic calibre but for financial reasons would not otherwise be able to afford to study in the United Kingdom. Students must not have previously studied for one year or more in a developed country and must hold the equivalent of a UK first- or upper second-class undergraduate degree. Students must have applied to study one of the 10 eligible Master's programmes. Students must return to their home country on completion of their degree.

SPDC Niger Delta Postgraduate Scholarship

For prospective Master's students from the Nigerian Delta States. Students must be applying for the Chemical Process Engineering MSc, the Civil Engineering MSc or the Mechanical Engineering MSc, and must not have aleady had the chance of studying in the UK or another developed country. Students must not be current or former employees of SPDC, the Royal Dutch Shell Group of Companies or Wider Perspectives Ltd, or be a the relative of a current employee, and must intend to return to Nigeria after completion of the degree. These awards are based on intellectual ability and leadership potential.

Brown Family Bursary

This award is based on financial need.

R.C. Vaughan Bursary

Founded in 1976 by Dr K.K. Gupta as a memorial to Mr R.C. Vaughan who was a Lecturer and Senior Lecturer in the Department of Civil and Environmental Engineering from 1940 to 1952

Further information about funding and scholarships can be found on the Scholarships and funding website.


Entry requirements

A first or upper second-class Honours UK Bachelor's degree in a relevant discipline (such as engineering, mathematics, computer science, environmental science, human or physical geography, geology, forestry, oceanography, or physics) or an overseas qualification of an equivalent standard. Applicants with relevant professional experience are also considered.

International equivalencies

Select your country for equivalent alternative requirements

English language proficiency level: Standard

How to apply

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.

The deadline for applications is 1 August 2014.

Who can apply?

The programme is best suited for those in employment seeking continuing professional development or those who are looking for a career as a data scientist.

What are we looking for?

When we assess your application we would like to learn:

  • why you want to study Spatio-temporal Analytics and Big Data Mining at graduate level
  • why you want to study Spatio-temporal Analytics and Big Data Mining at UCL
  • what particularly attracts you to this programme
  • how your personal, academic and professional background meets the demands of a challenging academic environment
  • 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.


Career

Graduates from this programme are expected to find positions in consultancy, local government, public industry, and the information supply industry, as well as in continued research. Possible career paths could include: data scientist in the social media, finance, health, telecoms, retail or construction and planning industries; developer of spatial tools and specialised spatial software; researcher or entrepreneur.

Employability

Graduates will be equipped with essential principles and technical skills in managing, modelling, spatial and spatial-temporal analysis, and visualising “big” spatio-temporal data, with emphasis on real development skills including: Java, JavaScript and R. Business Intelligence (BI) skills will also be taught via practical case studies and close collaborations with leading industrial companies and institutions. All these skills are highly valued in big data analysis.


Next steps

Contact

Miss Shani Crawford

T: +44 (0)20 3108 4046

Department

Civil, Environmental and Geomatic Engineering

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