University of Hong Kong

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.

The course examines the close connection between music and science that has existed historically from Pythagoras on into modern times. The course introduces the essential physics of musical sound production and analysis in order to understand the elementary principles behind wind, string and percussion instruments and their characteristic timbre. The course examines the development of scales from fundamental principles to identify some of the subtle differences between Chinese and Western music. Contemporary music and science interactions focus on electronic music and the working principles of modern instruments such as the electric guitar. Finally the course looks at some scientific understanding of musical appreciation and the factors that make music pleasing. 

Do Google and Facebook understand us better than we do ourselves? Are we becoming lab rats every time we go online? Is the impartially designed algorithm for predicting the probability of recidivism truly fair for sentencing individuals? When big data analytics are routinely applied in our daily lives, the ability to audit the adopted algorithms becomes crucial. This course aims to build students’ big data literacy through three major areas of focus: (1) Defining what big data is; (2) Providing an overview of existing big data analytical techniques; and (3) Discussing opportunities and challenges of big data analytics in tackling social problems. 

This course introduces topics in computer and communication networks. Course topics include: network structure and architecture; reference models; stop and wait protocol; sliding window protocols; character and bit oriented protocols; virtual circuits and datagrams; routing; flow control; congestion control; local area networks; issues and principles of network interconnection; transport protocols and application layer; and examples of network protocols.

This course draws upon an understanding of organizational behavior to examine the techniques and practice of human resource management (HRM). It identifies the difference between personnel and HRM, describes the major functional areas within HRM, articulates the importance of a strategic HR perspective, identifies some of the key skills required for current HRM practice, explains how HR initiatives can add value to the bottom line, and teaches critical thinking when presented with current HR issues. Topics include the strategic role of HRM, job analysis and the legal environment in Hong Kong, HR planning and recruitment, employee testing and selection, interviewing, training and development, performance management and appraisal, career development, compensation and benefits, labor relations and disciplining, and employee safety and health. Assessment: class participation (20%), group project and presentation (50%), individual assignments and end-of-term test (30%).