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Spatio-temporal Analytics and Big Data Mining MSc

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

Covid-19 programme updates

Due to COVID-19, there may have been updates to this programme for the 2020 academic year. Where there has been an update, these are indicated with a red alert and a link which will provide further information.

Key information

Programme starts

September 2020

Modes and duration

Full time: 1 year

Application dates

All applicants
Open: 1 November 2019
Close: 11 August 2020
Notification
Due to the large number of applications received, this programme is no longer accepting applications for 2020/21 entry. We apologise for any inconvenience caused. Applications for 2021/22 entry will open later in the year.

Tuition fees (2020/21)

UK/EU:
£13,640 (FT)
Overseas:
£28,530 (FT)


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 Students website.

Optional qualifications: This degree is also available as a PG Diploma with fees set accordingly.
Location: London, Bloomsbury

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.

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 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.

Students undertake modules to the value of 180 credits.

The programme consists of three core modules (45 credits), five optional modules (75 credits) and a dissertation/report (60 credits).

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

Upon successful completion of 180 credits, you will be awarded a 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.

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.

Compulsory modules

Please visit the Spatio-Temporal Analytics and Big Data Mining MSc programme page for further compulsory module details.

  • Geospatial Science
  • Spatial Analysis and Geocomputation
  • Spatial-Temporal Data Analysis and Data Mining


Optional modules

Choose five options from the below list. Terms are indicated in brackets. Visit the Spatio-Temporal Analytics and Big Data Mining MSc programme page for further optional module details.

  • Geospatial Programming (T1)
  • Spatial Databases and Data Management (T1)
  • Applied Machine Learning (T2)
  • Mining Social and Geographic Datasets (T2)
  • Sensors and Location (T2)
  • Urban Simulation (T2)
  • Web and Mobile GIS - Apps and Programming (T2)

Students may choose one elective module (any UCL Master's level module) in place of one optional module in Term 2, subject to approval from the programme director.

Covid-19 module updates
Due to COVID-19, there may be updates to the modules for your chosen programme of study this year. Some modules may not be available or may need to be moved to a later term or year of study.  We have included these updates below:   Geospatial Programming (CEGE0096) will run in Term 1 and Machine Learning for Data Science (CEGE0004) will run in Term 2. These updates are relevant for 2020-21 academic year only.  The full list of modules will be available in the module catalogue from late August.  From the first week of September, you will be invited to complete module selection from Portico, our student record system. There may need to be additional updates or changes to modules during the academic year to allow for new guidance from the UK Government and Public Health England. Your department shall keep you updated of these changes as they become available.  

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 laboratory practicals. Assessment is through examination, coursework, practicals, dissertation, and a poster presentation.

Covid-19 contact hours on campus
In Term One, while campus will be open, all the learning activity for the core content of your modules will take place online – including lectures, tutorials, seminars and assessments. By “core content” we mean everything you need to learn to complete the module successfully. In addition to these online contact hours, we will be offering some face-to-face educational activities for students on campus, and we will provide alternative online activities for those students unable to join us on campus. These activities, which will include contact with academic staff, will be relevant to your programme of study may include seminars, academic and employability skills workshops, small-group or individual tutorials, lab and practice-based teaching. UK Government safety guidelines will limit the amount of ‘in person’ activity we can offer and while it will vary from programme to programme, is likely to be no more than 1-2 hours per week. This will vary across departments, particularly if your programme includes laboratory/practical/studio/workshop sessions. You will be updated with more specific details as they are available and your timetable will indicate which sessions will be on campus and which will be available online.
Covid-19 assessment updates
There may be changes to the format of assessments for modules in this programme due to COVID-19. These will be summarised for each module on the module catalogue from 17 August 2020.   If any changes to assessments need to be made during the academic year due to updates in government guidance, these will be communicated to you as soon as possible from your department.    
Communicating further Covid-19 mitigation plans
We are continuing to follow UK Government guidance, as well as the expertise of our researchers, including specialists in health, education, human behaviour and infection prevention, to make sure UCL is as safe as possible during the COVID-19 pandemic. If it becomes necessary to make further changes to your programme as a result of new guidance/regulations, UCL and your department will communicate these as soon as this becomes clear. We will keep you up-to-date with our plans throughout term one, so you have the information you need to be able to take decisions that are right for your circumstances. Please ensure that you keep in touch with your department by regularly checking your UCL emails, Moodle courses, the Coronavirus FAQs for Students page and any UCL online groups or social media you follow.

Additional costs

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

Accessibility

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

Funding

Scholarships relevant to this department are displayed below.

Brown Family Bursary

Note:
This scheme is now closed for 2020/21
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

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, 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.

Why study this degree at UCL?

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.

Department: Civil, Environmental & Geomatic Engineering

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.

There is an application processing fee for this programme of £80 for online applications and £105 for paper applications. Further information can be found at: www.ucl.ac.uk/prospective-students/graduate/taught/application.

Who can apply?

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.

Application deadlines

All applicants
11 August 2020

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 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.

UCL is regulated by the Office for Students.

Page last modified on 13 August 2020