Geography Core Courses

Understanding spatial processes, environments, and human–nature systems.

Geography Core Courses develop spatial thinking across physical, environmental, and human systems. Students learn to work with GIS, geospatial data, remote sensing, and 3D spatial technologies to observe, measure, and interpret real-world patterns. These courses ground analysis in geographic theory, empirical evidence, and multi-scale understanding.

Geography asks:

• What spatial patterns exist?
• Why do they emerge across places and scales?
• How can we measure and interpret them using spatial data?

• GI1101

  Geospatial Intelligence for Everyday Life (Gateway)

  This course aims to engage students with the role of geospatial intelligence in everyday life.

• GE2215

  Introduction to GIS

  This course focuses on the important concepts and the practical use of Geographic Information System (GIS) in problem solving in both the social and physical sciences.

• GE2234

  Geospatial Data Collection and Digital Mapping

  This course explores techniques for geospatial data collection, digital mapping, and processing. Students will understand photogrammetry and computing tools to produce accurate spatial data.

• GE3238

  GIS Design and Practices

  This course examines the range of considerations necessary to develop GIS, and is intended for geographers, planners, IT managers and computer scientists who have already acquired an introductory knowledge of the field.

• GE3252

  Cartography and Geovisualization

  This course covers the art, science, and ethics of mapmaking and map use. It aims to introduce students the design principles and techniques for creating maps with contemporary mapping tools.

• GE3217

  3D Data Acquisition and Digital Processing

  This course covers advanced techniques for acquiring and processing 3D data using lidar, laser scanning, photogrammetry, and drone-based imagery.

• Applications

  GE3216 / GE3259

  Applications of GIS & Remote Sensing /
  Applied Geographical Data Science

• Applications

  GE4214 / GE4240 / GE4241 / SPH3108

  Geospatial Mapping for Public Health /
  Remote Sensing of Environment /
  Spatial Decision-Making /
  Spatial Health

Computing Core Courses

Building analytical and computational tools for spatial intelligence.

Computing Core Courses equip students with programming, algorithmic thinking, and spatial modeling skills. Students learn to formalize geographic processes, build simulations, and apply machine learning to complex spatial data. These courses emphasize computational rigor, abstraction, and scalable analysis.

Computing asks:

• How can we formalize these patterns into models?
• How can we simulate dynamic spatial systems?
• How can we scale, optimize, or automate analysis?

• CS1010HS

  Programming Methodology

  This course introduces the fundamental concepts of problem-solving by computing and programming using an imperative programming language.

• BT1101HS

  Introduction to Business Analytics

  This course introduces students to the fundamental concepts and tools of analytics and data science applications in business and non-profit organisations.

• CS2030HS

  Programming Methodology II

  This course is a follow up to CS1010. It explores two modern programming paradigms, object-oriented programming and functional programming.

• CS2040HS

  Data Structure and Algorithm

  This course introduces students to the design and implementation of fundamental data structures and algorithms.

• CS2109HS

  Introduction to AI and Machine Learning

  This course adopts the perspective that planning, games, and learning are related types of search problems, and examines the underlying issues, challenges and techniques.

Integrative Problem-Solving Courses

Translating spatial knowledge into real-world intervention and design.

Integrative Problem-Solving Courses bring together geographic understanding and computational methods to address real-world challenges. Students apply spatial thinking and technical skills in project-based, interdisciplinary contexts such as urban systems, environmental change, and policy design. These courses develop the capacity to translate analysis into action — designing solutions that are technically sound, context-aware, and socially relevant.

• GI3101

  GeoAI for Good

  This course explores the applications of geospatial artificial intelligence (GeoAI) in addressing global challenges and support sustainable development. Students will learn how to leverage GeoAI to derive actionable insights from location-based data, with a focus on promoting positive social, environmental, and economic impacts.

• GI3102

  Spatial Social Network Applications

  This course explores the integration of geospatial and geocomputing techniques in analyzing and understanding spatial social networks. Students will learn how to apply spatial analysis, network science, and computational methods to study social interactions and behaviors within geographical contexts.

• GI4101

  GeoAI for Urban Applications

  This course explores GeoAI applications in urban environments. Students will learn to apply AI, machine learning, and data fusion techniques to geospatial data, addressing urban challenges such as transportation and land use planning.

• GI4102

  Computational Simulation for Social Science

  This course introduces computational simulation methods for social science research. Students will learn to design, implement, and analyse computer-based simulations using techniques such as agent-based modelling and system dynamics.

• Applications

  Capstone project or Industrial Attachment

  Students can choose between completing either an independent research integrating geography and computing or an industrial attachment (internship) with government or private industrial partners.