.png){kind=small}
Second Major/Minor
in Geospatial Data Science
Objective
Exponential growth in new forms of data and transformational advances in analytical techniques are allowing society to understand human behaviours in real-time through intuitive and visually appealing ways. Our understandings of human behaviours are also reaching ever finer scales thanks to the collection of data at highly disaggregated levels, both geographically and temporally. Given that an estimated 80% of data contains geographic information, harnessing data within a spatial context using big data analytics can help generate insights in service of both public and commercial interests. The programme aims to emphasize domain knowledge and critical thinking in relation to social issues. Upon completion of the programme, students will be well-equipped with spatial data analytic skills along with an in-depth understanding of diverse social issues. They will also be prepared for careers in GIS and related technologies, which will enable them to pursue relevant certifications after gaining a few years of work experience.
Learning Outcome
The Geospatial Data Science Programme aims at providing students with:
-
Identify and describe new forms of data and transformational advances in spatial data capture, analytical techniques, geospatial applications, and visualization to understand human behaviors and present research outcomes in aesthetically captivating ways.
-
Carry out state-of-the-art spatial data analytic techniques combined with an in-depth understanding of diverse environmental and social issues (by means of field/laboratory/individual- and team-based learning, research projects, presentations and capstone experiences as relevant).
-
Critically dissect the ethical issues surrounding big data, spatial data, and the increasing use of algorithms in policymaking and governance applications and decisions.
-
To gain in-depth knowledge of how big data and spatial data can be applied to solve real world problems.
-
To understand the advantages and limitations of using big data and spatial data approaches.
-
To gain the academic foundation and requisite industry skills necessary to pursue professional certifications in GIS and related fields.
Programme Structure
Second Major/Minor in Geospatial Data Science (For students admitted in 2025-2026 intake and thereafter ONLY)
No. of Credits
Component
Major
Minor
(a)
Introductory courses
(i)
Disciplinary
(ii)
Pre-requisites*
6
12
6
-
(b)
Advanced courses
(i)
Compulsory courses
(ii)
Core courses
(iii)
Disciplinary electives
(iv)
Capstone experience
12
24
6-12
6-12
6
12
12
-
72
36
*
Candidates who opt to declare two major programmes offered by the Faculty of Social Sciences should avoid selecting overlapping pre-requisites
Candidates who wish to declare a MAJOR (72 credits) or MINOR (36 credits) in Geospatial Data Science must complete:
(a) Introductory courses
(18 credits for major; 6 credits for minor) - to be taken in Years 1-2
(i) One disciplinary course from the following list:
(ii) Candidates who major in the programme should take two pre-requisite courses from the following six units, but not more than one from a single unit (12 credits):
-
Faculty of Social Sciences
-
Geography
-
Politics and Public Administration
-
Psychology
-
Social Work and Social Administration
-
Sociology
(b) Advanced courses
(54 credits for major; 30 credits for minor) consist of the following components to be taken in Years 2-4.
(i) Compulsory courses (12 credits for major and 6 credits for minor)
Candidates who major in the programme should take two of the following compulsory courses, whereas candidates who minor in the programme should take one of the following compulsory courses:
(ii) Core courses (24 credits for major and 12 credits for minor)
Candidates who major in the programme should take 24 credits from the core course list below, whereas candidates who minor in the programme should take 12 credits of the following core courses. Once the compulsory and core requirements are fulfilled, other courses from this list may be taken to fulfil the elective requirement:
(iii) Disciplinary electives (6-12 credits for major; 12 credits for minor)
Candidates who major in the programme should take 6-12 credits of disciplinary elective courses from the advanced course list (also refer to the remarks in the core course list for elective requirements), whereas candidates who minor in this programme should take 12 credits of disciplinary elective courses.
In addition to the existing geography courses, students may now choose from the following cross-listed courses as disciplinary electives [pending approval from COMP; POLI; SOCI; SOWK]:
COMP2113
Programming technologies
6
credits
COMP2119
Introduction to data structures and algorithms
6
credits
COMP2501
Introduction to data science and engineering
6
credits
COMP3314
Machine learning
6
credits
COMP3516
Data analytics for IoT
6
credits
POLI3148
Data science in politics and public administration
6
credits
SOCI2030
Quantitative research methods
6
credits
SOWK3136
Application of big data analytics in social sciences
6
credits
(iv) Capstone experience (6-12 credits for major only, to be taken in Year 3/4)
(c) Course lists [pending approval from COMP; POLI; SOCI; SOWK]
Introductory Courses
Students who major or minor in this programme must have successfully completed one of the following disciplinary introductory courses
Advanced Courses
Level 2000 courses (foundation: offered on an annual basis)
COMP2113
Programming technologies
6
credits
COMP2119
Introduction to data structures and algorithms
6
credits
COMP2501
Introduction to data science and engineering
6
credits
SOCI2030
Quantitative research methods
6
credits
Level 3000 courses (advanced: offered on an annual or biennial basis)
COMP3314
Machine learning
6
credits
COMP3516
Data analytics for IoT
6
credits
POLI3148
Data science in politics and public administration
6
credits
SOWK3136
Application of big data analytics in social sciences
6
credits
Level 4000 courses (capstone experience courses for Geospatial Data Science majors only: offered on an annual basis; excluding GEOG4012 Advanced GIS and GEOG4013 Advanced remote sensing which, are not capstone courses and are instead core courses at the 4000 level)
For more information please see the full Regulations and Syllabus of the Faculty of Social Science at https://web.socsc.hku.hk/bachelors-regulations-and-syllabuses/.
For further questions please contact the Department of Geography Undergraduate Team at geogug@hku.hk.