Objectives
This course familiarizes students with advanced spatial data science techniques and literature in the emerging field of digital geography. Topics examined include spatiotemporal data mining, geospatial simulation, spatial statistics and machine learning techniques, and spatial data quality. Upon completion of the module, students will be expected to be able to apply these spatial data science techniques to their field(s) of interest, and critically assess the analysis outcomes and implications to human everyday life and the physical environment. Students are required to undertake an independent project, and their work will be presented in a seminar format.
Who Should Attend
The programme is suitable to applicants who already have a Bachelor’s degree, which can be undertaken full-time and part-time.
Entry Requirements
Applicants for the Graduate Certificate coursework programme should have a bachelor’s degree. Candidates with other qualifications and experience may be considered on a case by case basis, subject to approval by the Faculty/School.
Lesson Delivery
a.) Facilitated Learning- 3 hours weekly b.) Other work- 7 hours weekly
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Please note that the mode of delivery is subject to change in light of the COVID-19 situation.
Courses marked ‘online’ may have compulsory face-to-face sessions such as laboratory or hands-on components and details should be sought from the schools or departments before learners register for them.
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Last updated: 22 April 2025
