Course Description
Programme Core Courses
1. HPM501 Housing Economics and Finance
This course will provide students with a fundamental knowledge of the economic principles influencing the housing and property market. At the end of this course, student should have a good understanding of the basic determinants of the demand for and supply of land and housing services and factors that influencing housing tenure decisions. The course will further cover the rationale for government intervention and the forms of intervention. In terms of property finance, the course will introduce the fundamental methods and techniques of property valuation and the principles of budgeting for property management. The enhanced curriculum includes portfolio analysis, asset performance metrics, and risk management strategies for property portfolios.
2. HPM502 Contemporary Issues in Housing Management
This course will provide students with knowledge of housing management in the public and private sector. It will introduce appropriate conceptual and theoretical frameworks to examine how housing systems are managed in the context of a rapidly changing social, economic and political environment. Students will learn to employ these concepts and theories in the analysis of the operations and governance of housing systems.
3. HPM503 Building Studies for Housing Management
This course will impart practical knowledge on properties of basic construction materials, common defects of building fabrics and the rectification strategies, to provide a sound basis for the decision-making processes of building improvement works. Students are expected to learn how to analyse the key features of building services system and the impact of the overall building design. Emphasis will be given to environmentally sustainable practices and the smart technology applications in housing and property management. The enhanced curriculum includes Building Information Modelling (BIM), smart building technologies, digital twin applications, and innovative data collection methods using wearable devices for accessibility analysis.
4. HPM504 Digital Facility and Asset Management
This course will provide students with an understanding of facility and asset management in local and global settings with enhanced focus on smart technologies and digital transformation. Building upon traditional facility management theory, the course integrates cutting-edge digital tools including Building Information Modelling (BIM), Internet of Things (IoT) sensors, and drone-based asset documentation. Students will examine contemporary issues in facilities audit, building performance assessment, and the opportunities of smart facility and asset management. The course covers asset information, performance measurement, service quality management, and life cycle perspective with emphasis on digital transformation applications.
5. HPM601 Legal Studies for Housing Management
This course will provide students with the basic knowledge about the legal principles and laws related to housing development and management in Hong Kong. It covers various topics including land administration, planning and building control and management of multi-owned developments. Aside from legal obligations relevant to housing development and management, the course will also allow students to understand the relevant aspects of legal knowledge related to the housing management profession, including negligence and employment law. It will introduce the general principles of alternative dispute resolution for conflict resolution.
6. HPM602 Smart Practices in Housing Management
In the course, students will be introduced to the necessary knowledge and practice on the skills and techniques relating to the working environment of housing management, with enhanced emphasis on smart technologies, digital innovations, low-altitude economy, and AI/robotics applications. Leadership, interpersonal, communication, and team-working skills workshops will be part of this course. Students will learn about AI-powered property operations, robotic process automation, drone applications in property management, PropTech integration, and data-driven asset decisions.
7. MCG511 Housing Policy and Development
This course will provide students with an understanding of housing policies in the local and global settings. It will examine the relationship between the housing system and social policies. It also examines how affordable housing is delivered by both government and non-profit actors in the national, local, and community levels. Particular attention would be drawn to how economic, political, legal, and social forces shape the housing policy and housing stock. Students are expected to learn how to analyse the policies and programmes that are currently in place, and evaluate their effects on the quality and affordability of housing.
Programme Elective Courses
1. MCG501 Cities and Social Change
The course provides an introduction to the key drivers of urban social change. It examines how processes of globalisation, demographic change, mobility, economic change and shifting social norms impact on urban development and on the social structure and composition of cities. The course has an international perspective but with a particular orientation towards urban change in East Asia.
2. MCG505 Smart and Sustainable Cities
This course introduces students to Smart Cities, their construction, organisation, and management under the framework of UN Sustainable Development Goals (SDGs). It explores how these new conceptions of the city, as data driven and technologically convenient are utopian, but also problematic. One of the chief concerns about Smart Cities, is how they must become sustainable in terms of environmental impact, technological innovation, and social life. This course explores how cities can be both smart and sustainable, and the risk vectors of such a strategy.
3. CDS527 Big Data Analytics#
This course provides an understanding of the concept and challenge of big data. The focus is on the data analytic techniques to tackle the V’s (volume, velocity, variety, veracity, valence, and value) in big data and how these impacts data collection, monitoring, storage, analysis and reporting. The following topics across the big data domain will be introduced: distributed file systems; big data analysis techniques; high-performance processing algorithms for big data; big data search and query technologies. An example (Apache Spark) of big data management system to manage and process large-scale data is introduced in the course. Real world big data analytics applications in domains like business will also be elaborated. Students will actively participate in the delivery of this course through assignments, portfolio development, and projects.
4. CDS556 Urban Computing and Spatio-Temporal Analytics#
This course introduces how data science techniques are integrated with geographic information systems (GIS) to analyse spatial and temporal data. Students learn to leverage tools like Python, R, and specialised GIS software to perform spatial analysis, visualise geospatial data, and derive insights for various applications, including urban planning, environmental monitoring, and location-based services. The curriculum covers topics such as spatial data acquisition, geostatistics, machine learning for spatial data, and remote sensing. Through hands-on projects and case studies, students gain practical skills in managing and interpreting geospatial datasets to solve real-world problems.
#CDS527 Big Data Analytics and CDS556 Urban Computing and Spatio-Temporal Analytics will be added as elective courses, effective from the 2026-27 intake.
Capstone Project
1. HPM603 Research Methods and Capstone Project
This two-term course will provide students with an opportunity to learn about social science research methods and apply the knowledge and skills in a housing related research project. In the first term, students will be guided through the research process, including research question formulation, literature review, research design, data collection and analysis. With guidance from assigned advisors, students are expected to prepare research proposals on a housing topic at the end of the first semester. Starting from the second term, students will implement their research proposals under the supervision of the advisors. In the research project, students must gather primary data or analyse secondary data in response to a well-defined research question.