University of Hong Kong

This course examines the practical applications of immunology and microbiology in biological research, clinical analysis and disease diagnosis. It covers application of antigen-antibody interaction in advanced research such as chromation; immunoprecipation assay, co-immunoprecipitation and dual immunofluorescence analysis; principles of flow cytometry and its application; tumor immunology and immunotherapy such as FDA-approved checkpoint inhibitor immunotherapy and chimeric antigen receptor (CAR) T-cell therapy; microbial pathogens and associated diseases, host immune response, antimicrobial agents and multidrug resistance, epidemiology and prevention of microbial infections; and clinical laboratory analysis in haematology, chemical pathology, and clinical microbiology.

This course examines how to better understand data, present clear evidence of the findings to the intended audience, and tell engaging data stories that clearly depict the points made though data graphics. 

This course examines tourism as a lens to explore key issues of globalization and economic development and to demonstrate how tourism, a global phenomenon, influences local people’s lives. Course objectives are to 1) introduce key concepts relevant to tourism and globalization; 2) apply theoretical frameworks to the analysis of contemporary issues of the globalization of tourism, and the complex  relationships that link local, regional, national and international processes and patterns of tourism development; 3) explore the relationships between the forces of globalization, multinational tourism corporations, and the state and civil society; and 4) interrogate the economic, political and social ramifications of the systemic sources of power and inequality which are reflected in and sustained by international tourism. Finally, this course will also consider the future of tourism with regard to new sectors and trends such as ecotourism, adventure tourism, and the effects of social media and the Internet, along with what travel will look like in a post-COVID-19 world both in and beyond Hong Kong.

This course examines basic technical knowledge on electronic commerce and financial technology. It introduces different e-commerce models: B2C and B2B model and overview different enabling technologies e-Commerce and FinTech such as the location base technology, RFID, GPS, e-payment, server-side and channel security, Near Field Communication, QR Code, augmented reality and other latest technologies deploying in the industry. By the end of the course, the latest trend and the way forward of e-commerce and Fintech in Hong Kong and overseas will be discussed.

This course examines advanced topics and techniques in database systems, with a focus on the system and algorithmic aspects. It will also survey the recent development and progress in selected areas. Topics include: query optimization, spatial-spatiotemporal data management, multimedia and time-series data management, information retrieval and XML, data mining.

This course is for foreign students with no previous knowledge of Chinese. It covers four main areas: speaking, listening, reading and writing which require pinyin-word processing and actual writing of Chinese characters. The pinyin-word processing is emphasized for this course to enable students to break the restrictions of the number of characters they can actually write and allow them to communicate in Chinese soon. The course is at first conducted in English and gradually adds Chinese as students' vocabulary increases. Students master the Pinyin system and frequently used sentence structures and expressions. 

This course examines statistics for students who aspire to major in Statistics or Risk Management. It focuses on the roles of statistics as a scientific tool with applications to a wide spectrum of disciplines, and as a science of reasoning which has revolutionized modern intellectual endeavours. It lays a panoramic foundation for a formal study of statistics at the university level. 

This course examines the main elements of natural language processing (NLP), text analytics, and text mining, providing students with a foundation in collecting, managing, and analyzing textual data with financial and economic applications in mind, such as FinTech. Examples of potential applications include understanding and responding to sentiment in financial newspapers and social media, using social media to improve performance in asset/investment management, due diligence, Fed watching, monitoring of company events, and detecting insider trading. Although students write their own computer programs in this course, they are not required to implement most algorithms from scratch. Instead, the focus of this course is on how to use existing state-of-the-art open-source software libraries and how to apply them in a financial context. This course consists of three parts. In the first part, we work with real-world textual data sets to obtain proficiency in collecting, importing, organizing, and cleaning textual data from sources related to finance and economics. Among others, we cover web scraping, textual corpora, text processing, tokenization, stemming, and stop word removal. In the second part we delve into a more detailed analysis of NLP, text analytics, and machine learning with a particular focus on FinTech. For instance, we examine bag-of-words, word weighting schemes, document classification, document clustering, sentiment analysis, and topic models. The third part consists of summarizing, displaying, and visualizing results obtained from NLP and text analytics for applications in finance and economics.

This course examines the basic concepts and modern software architectures on distributed and parallel computing. Topics include: computer network primitives, distributed transactions and two-phase commits, webservices, parallelism and scalability models, distributed consistency models, distributed fault-tolerance, actor and monads, Facebook photo cache, Amazon key-value stores, Google Map-reduce, Spark, and TensorFlow.