Taught course

Spatio-temporal Analytics and Big Data Mining MSc

Institution
UCL - University College London · Civil, Environmental and Geomatic Engineering
Qualifications
MSc

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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.

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.

Pre-Master's and Pre-sessional English

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

Months of entry

September

Course content

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

Fees and funding

Please see UCL website for full information about fees and costs for this programme.

Qualification, course duration and attendance options

  • MSc
    full time
    12 months
    • Campus-based learningis available for this qualification

Course contact details

Phone
+44 (0) 20 3370 1214