MSc in Data Science with Specialization in Smart Governance
Collaborate with FSS
All courses are compulsory:
SSGC7298 Project Report
Project report gives the students an opportunity to apply the knowledge obtained from their previous studies in data science and field of specialization based on their interest. Students, guided and supervised by individual instructor on a person-to-person basis, are required to independently and individually complete a research project on smart governance that subject with a report of no less than 4,000 words in length. Mini conferences would be organized by the academic year-end and students were required to deliver their projects which would be graded.
Choose 4 required elective courses from the following:
SSGC7201 Civic Data Acquisition and Analysis
To promote studies using computational methods in social sciences, this course focues on machine learning techniques and their applications in social sociences. By introducing principal ideas in statistical learning, the course will help students to understand the conceptual underpinnings of methods in data mining, how classical concepts of research design in the social sciences can be implemented in new data sources, and how these new data sources might require social scientists to update their thinking on research design. The course focuses more on the usage of existing software packages (mainly in R) than developing the algorithms by the students. Students will be required to work on projects to practice applying the existing software.
SSGC7202 Big Data and Smart Governance
This course is designed to teach students analytical techniques of dealing with open government data and other (usually big) data that are related to smart governance. We will focus on two types of data: text data and geo-spatial data.
Digitalized text represents an important source of data for social scientists. This is particularly true in political science, where a large amount of political information, otherwise difficult to analyze, is embodied in historical and contemporary speeches and documents that can be converted into digitalized text with increasing ease. Another source of text-based data come from online contents.
SSGC7203 Analysis of Media and Opinion Data
This course introduces students to the theories and techniques of data analysis for monitoring and understanding media behavior and public opinion.
While theories of statistics, communication, media effects, and public opinion will be reviewed, the emphasis is on hands-on analysis and presentation of data. The objectives are two-folds 1) facilitate data-based policy making and decision making in government and cooperate settings; 2) facilitate data-based theory building in both applied and academic settings.
SSGC7204 Making Sense of Smart Governance
Smart Governance is an essence for the development of smart city that stressing on the public-private collaboration for city management through the use of Information and Communication Technologies (ICTs). This course introduces the concept, main theories, and updated studies of smart governance, as well as integrate a course project with several assignments to offer practical skills training. After the first introductory lecture on smart governance, the course covers four key topics of SG: 1) major theories of governance in political science and public administration; 2) the practice of using IOT technologies to design and implement solutions for smart and sustainable governance in the context of China and beyond; 3) experimental social science techniques including survey experiment, field experiment, quasi-experiment (e.g., PSM, DID, RDD, IV), and natural experiment.
EDUC7044 Quantitative Social Science Research with Big Data
This course is designed to be part of the emerging field of quantitative/computational social sciences. The goal is to equip students with data science approach to answer social science questions. This course will introduce principles and skills of quantitative social science research. Students will receive an update of the major tools and ideas used in the field and be guided toward their first data-driven research project throughout this course.