VECTOR | [3-0-0:3] |
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DESCRIPTION | This course introduces fundamental knowledge and practice of basic statistics in quantitative social science research, with a focus on how quantitative methods are used to assemble, describe, and draw inferences from bodies of numerical data. The course serves as an additional foundation for more advanced methodology courses (such as UGOD 5020). The course covers two modules. The first is about descriptive statistics and fundamentals of statistical inference. Topics include frequency distribution, probability theory, random variable and probability distributions, estimation, hypothesis testing, t-test, Analysis of Variance (ANOVA), and contingency table analysis. The second is about linear regression techniques, which are widely used in social science research. The course materials are explored through the analyses of real data sets using STATA. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6175) | 02-SEP-2024 - 06-DEC-2024 We 03:00PM - 05:50PM | Rm 227, E1 | ZHANG, Zhuoni | 15 | 10 | 5 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | The course aims to provide a comprehensive understanding of the city and the system of cities, the challenges faced by cities, especially the rapidly-developing large cities, and the key tools for interventions in response to critical pressures linked to economic development, urbanization, globalization, migration, social inclusion, climate change, resource efficiency, technology etc. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6196) | 02-SEP-2024 - 06-DEC-2024 Mo 09:00AM - 11:50AM | Rm 134, E1 | KAN, Ge Lin WANG, Binzhe ZHAO, Wufan ZHOU, Muzhi | 50 | 27 | 23 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | This course builds on the knowledge of the linear regression models to introduce students advanced statistical methods to analyze survey, administrative and other types of data of interest to quantitative social scientists. The introduction of statistical methods is integrated into research contexts and designs from a holistic framework and bridge quantitative social science and computational social science (data science). Topics include measurement, prediction, causal inference, natural experiment and program evaluation (difference-in-differences, panel data, instrumental variables, regression discontinuity), applied to both survey and big data. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6193) | 02-SEP-2024 - 06-DEC-2024 We 09:00AM - 11:50AM | Rm 228, E2 | YUEN, Cheuk Yi Kelvin | 30 | 26 | 4 | 0 |
VECTOR | [3-0-1:3] |
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DESCRIPTION | This course introduces students to the basic concepts and methods in Geographic Information System (GIS), and their applications in urban design and governance, environmental and infrastructure sustainability, and smart city management. This course integrates social science and informatics perspectives, and is suitable for students with various backgrounds. In addition to learning traditional GIS data, spatial analytical techniques, and GIS software, this course also develops skills of manipulating spatially detailed urban sensing Big Data (about urban activities, environmental qualities, and mobility patterns). |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6250) | 02-SEP-2024 - 06-DEC-2024 Tu 01:30PM - 04:20PM | Rm 227, E1 | CAO, Rui | 15 | 10 | 5 | 0 | |
LA01 (6251) | 02-SEP-2024 - 06-DEC-2024 Tu 04:30PM - 05:20PM | Rm 227, E1 | CAO, Rui | 15 | 10 | 5 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | The course introduces students to different methods of collecting data in the social sciences for urban analysis, focusing on sampling surveys designs and analysis in urban settings. Since alternative data sources (e.g., passive measurement, social media and administrative data) become increasingly available in recent years, the course will also cover other modes of data acquisitions such as using new technology on wearables, sensors, and apps in urban research settings, and exploration of cutting edge methods for collecting and analyzing web data, and how they can be used in combination with traditional survey data. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6170) | 02-SEP-2024 - 06-DEC-2024 TuTh 09:00AM - 10:20AM | Rm 103, E1 | ZHOU, Muzhi | 15 | 11 | 4 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | This course cuts across all major fields within urban planning and design and introduces the major theories, models, and methodological approaches that urban planners and policy makers use for urban planning and design. This course also critically examines the current practice of urban planning and governance in China at various geographical scales. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6195) | 02-SEP-2024 - 06-DEC-2024 Th 06:00PM - 08:50PM | Rm 103, E1 | LI, Chaosu | 15 | 5 | 10 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | This interdisciplinary course will provide students a systematic framework of the interplay between urban growth and the environment from economic perspectives.By walking them through the state-of-the-art research in urban and environmental economic studies from both developing and developed countries., it will familiarize students with popular empirical strategies in applied economics and relevant fields to solve the most pressing environmental challenges accompanied with fast-urbanized cities. By the end of the class, students will be equipped with toolkits to evaluate policy questions in transportation, pollution and health, climate change, energy transition, housing market, and environmental justice. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6197) | 02-SEP-2024 - 06-DEC-2024 Mo 01:30PM - 04:20PM | Rm 101, W2 | YANG, Lin | 15 | 9 | 6 | 0 |
VECTOR | [2-1-0:3] |
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DESCRIPTION | As urban areas continue to grow and become more complex, the amount of data generated by cities has increased exponentially. This presents significant challenges in terms of managing and interpreting urban data to address various urban issues or challenges. In response to this, our course is designed to equip students with the skills needed to visualize urban data, enabling them to gain a better understanding of city structure and dynamics. Moreover, this course will provide students with the knowledge and tools needed to conduct sustainable planning and design towards a sustainable society. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6186) | 02-SEP-2024 - 06-DEC-2024 We 09:00AM - 10:50AM | Rm 201, E3 | JIANG, BIN | 15 | 5 | 10 | 0 | |
T01 (6190) | 02-SEP-2024 - 06-DEC-2024 We 11:00AM - 11:50AM | Rm 201, E3 | JIANG, BIN | 15 | 5 | 10 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | This course focuses on applying machine and deep learning methods for remote sensing and covers a variety of practical applications of remote sensing image processing in complex urban environments. Through a mixture of theoretical and hands-on sessions, students will gain a deeper understanding of advanced image analysis methods and will be able to apply new concepts and approaches to enhance their problem-solving abilities in the interdisciplinary field using multi-source geo-information. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6199) | 02-SEP-2024 - 06-DEC-2024 We 06:00PM - 08:50PM | Rm 201, E3 | ZHAO, Wufan | 15 | 10 | 5 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | This course studies the role of entrepreneurship in the modern economy. Theories and empirics of startups as a driver of job creation, growth and development, and business cycles will be discussed. The course also examines the effects on venture growth, wealth accumulation, inequality, and innovation in a society. Finally, examples of entrepreneurial public policies will be demonstrated and assessed. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6194) | 02-SEP-2024 - 06-DEC-2024 We 03:00PM - 05:50PM | Rm 103, E1 | YUEN, Cheuk Yi Kelvin | 15 | 12 | 3 | 0 |
VECTOR | [3-0-0:3] |
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DESCRIPTION | GeoAI is an interdisciplinary field of Geography/GIScience and Artificial Intelligence (AI), aiming to harness AI techniques to address diverse environmental and societal challenges related to geospatial domain. The course will introduce fundamental concepts, methods, and tools of GeoAI, and show how emerging urban spatio-temporal data and GeoAI technologies can be applied to address urban challenges, improve urban governance and management, and enhance the overall livability and sustainability of cities. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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L01 (6252) | 02-SEP-2024 - 06-DEC-2024 Mo 06:00PM - 08:50PM | Rm 201, W4 | CAO, Rui | 15 | 9 | 6 | 0 |
VECTOR | [1-3 credit(s)] |
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DESCRIPTION | Independent study in a designated subject under direct guidance of a faculty member to provide students the advanced knowledge and research skill sets on urban governance and design related topics. Required readings, tutorial discussions, and submission of report(s) will be used for assessment. The course may be repeated for credit if different topics are studied. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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R01 (6443) | TBA | TBA | TBA | 20 | 2 | 18 | 0 |
VECTOR | [0 credit] |
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DESCRIPTION | Advanced seminar series presented by postgraduate students, faculty, and guest speakers on selected topics in urban governance and design. This course is offered once a year. Graded P or F. |
Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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T01 (6198) | 02-SEP-2024 - 06-DEC-2024 Th 10:30AM - 11:20AM | Rm 149, E1 | CAO, Rui | 30 | 30 | 0 | 0 |
DESCRIPTION | Master's thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
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Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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R01 (6405) | TBA | TBA | TBA | 999 | 20 | 979 | 0 |
DESCRIPTION | Original and independent doctoral thesis research supervised by co-advisors from different disciplines. A successful defense of the thesis leads to the grade Pass. No course credit is assigned. |
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Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
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R01 (6406) | TBA | TBA | TBA | 999 | 4 | 995 | 0 |