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Spatio-temporal Analytics and Big Data Mining MSc

London, Bloomsbury

With the rapid development of smart sensors, smartphones and social media, 'big' data is ubiquitous. This MSc teaches the foundations of GIScience, databases, spatial analysis, data mining and analytics to equip professionals with the tools and techniques to analyse, represent and model large and complex spatio-temporal datasets

UK students International students
Study mode
UK tuition fees (2023/24)
£18,000
Fees to be confirmed
Overseas tuition fees (2023/24)
£35,000
Fees to be confirmed
Duration
1 calendar year
2 calendar years
Programme starts
September 2023
Applications accepted
All applicants: 17 Oct 2022 – 31 Mar 2023

Applications closed

Entry requirements

A minimum of an upper second-class 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.

The English language level for this programme is: Level 1

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

Students will be equipped with computational foundations and skills needed for big data analytics including visualisation, prediction, clustering and simulation with statistical and machine learning approaches, as well as retrieving and mining big (open) data, web services and cloud computing, web and mobile applications, all by practising with real case data and open software.

Who this course is for

The programme is best suited to those in employment seeking continuing professional development or recent graduates who are looking for a career as a data scientist.
Read about what it takes to study for a Master's at UCL

What this course will give you

As one of the world'¿s top universities, recently rated 8th in the QS World University Rankings 2020, UCL excels across the physical and engineering sciences, social sciences and humanities.

UCL Civil, Environmental & Geomatic Engineering is an energetic and exciting multidisciplinary department with a tradition of excellence in teaching and research. Students on the Spatio-Temporal Analytics and Big Data Mining MSc will be part of a vibrant, enthusiastic, and international research environment in which collaboration and free-ranging debate are strongly encouraged. 

Students will benefit from the department’s excellent research and industry links, including attending our industrial and research seminar series, and carrying out a research project with one of our many industrial partners.

Read about what you'll get out of a graduate programme

The foundation of your career

Graduates will be equipped with essential principles and technical skills in managing, modelling, spatial and spatial-temporal analysis, visualising and simulating 'big' spatio-temporal data, with emphasis on real development skills including: Java, JavaScript, Python 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.

Employability

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.

Teaching and learning

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

A Postgraduate Diploma, consisting of five core modules (75 credits) and three optional modules (45 credits), taken full-time over nine months is also offered.

Modules

You will be equipped with computational foundations and skills needed for big data analytics including visualisation, prediction, clustering and simulation with statistical and machine learning approaches, as well as retrieving and mining big (open) data, web services and cloud computing, web and mobile applications, by practising with real case data and open software.

You undertake modules to the value of 180 credits. The programme consists of three compulsory modules, five optional modules and a dissertation/report. 

Compulsory modules








Optional modules








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 are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Spatio-temporal Analytics and Big Data Mining. Upon successful completion of 120 credits, you will be awarded a PG Dip in Spatio-temporal Analytics and Big Data Mining.

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.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2023/24) £18,000 Fees to be confirmed
Tuition fees (2023/24) £35,000 Fees to be confirmed

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

The costs associated with course materials such as books will vary depending upon which modules the student will select. Some modules may also charge for field trips. Students may need special protective clothing for laboratory work such as a lab coat and safety boots. There may be additional costs specific to the student's project.

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

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

See all the ways you can fund your studies

Brown Family Bursary

Deadline: 8 June 2023
Value: £15,000 (1 year)
Criteria Based on both academic merit and financial need
Eligibility: UK

Next steps

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.

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 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.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Got questions? Get in touch

Civil, Environmental and Geomatic Engineering
Civil, Environmental and Geomatic Engineering

cege-pg-admissions@ucl.ac.uk

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