Course description

Course description

It is the goal of the programme to have a comprehensive and dynamic curriculum in order to meet the challenges and opportunities of the fast developing Internet world.  Therefore the courses, both in terms of range and syllabus, are updated and revised continuously.  The list of courses is not final and therefore subject to change.  Please note that occasionally we may decide not to offer a particular course in one year or to add some new ones.

Course Code Course Title Course Description


Legal issues in artificial intelligence and data science

This course introduces students to the growing legal, ethical and policy issues associated with artificial intelligence, data science and the related issues security and assurance.  In particular, the relationship of AI and data science to personal autonomy, information assurance and privacy are analyzed and legislative responses studied.  Class participation, research, writing, and oral/electronic presentations are integral components of the course.

The course contributes to the following goals: written communication and life-long learning.  It includes coverage of the following goals: problem analysis, problem solving and teamwork.


Computational intelligence and machine learning

This course will teach a broad set of principles and tools that will provide the mathematical, algorithmic and philosophical framework for tackling problems using Artificial Intelligence (AI) and Machine Learning (ML).  AI and ML are highly interdisciplinary fields with impact in different applications, such as, biology, robotics, language, economics, and computer science.  AI is the science and engineering of making intelligent machines, especially intelligent computer programs, while ML refers to the changes in systems that perform tasks associated with AI.  Ethical issues in advanced AI and how to prevent learning algorithms from acquiring morally undesirable biases will be covered.

Topics may include a subset of the following: problem solving by search, heuristic (informed) search, constraint satisfaction, games, knowledge-based agents, supervised learning (e.g., regression and support vector machine), unsupervised learning (e.g., clustering), dimension reduction learning theory, reinforcement learning, transfer learning, and adaptive control and ethical challenges of AI and ML.


Banking in Web 3.0 – Metaverse, DeFi, NFTs and beyond

The course introduces students to new concepts of Banking with Web3.0 Technologies.  Firstly, it will review the evolution from traditional banking towards decentralized finance and token economies.  It will then assess the opportunities for new customer experiences with virtual reality and in the Metaverse as well as examine the opportunities and risks of NFTs (non-fungible tokens).  The course will thoroughly examine the different types of Digital Assets, Digital Currencies and special forms like Central Bank Digital Currencies (e-CNY, e-HKD).  A critical factor in the evolution towards Web3-Finance are the required regulations, a proper risk management and compliance of products and processes.  The course will elaborate on these with the help of case studies and contemporary scenarios at the time of the lecture.


Introduction to financial computing

This course introduces the students to different aspects of financial computing in the investment banking area.  The topics include yield curve construction in practice, financial modelling and modern risk management practice, etc.  Financial engineering is an area of growing demand.  The course is a combination of financial product knowledge, financial mathematics and computational techniques.  This course will be suitable for students who want to pursue a career in this fast growing area. 


Legal protection of digital property

This course introduces computer professionals to the various legal means of protecting digital property including computer software, algorithms, and any work or innovation in digital form.  Focus is on the main issues in protecting digital property arising from developments in information technology, and their legal solutions.  Topics covered include, but are not limited to, the following: 1) copyright protection of software and websites, 2) patent protection of software and algorithms, 3) protection of personal data.

Mutually exclusive with: COMP3311/CSIS0311 Legal aspects of computing and ECOM6004 Legal aspects of IT and e-commerce


Legal aspects of I.T. and e-commerce

This course provides an introduction to some of the main legal problems generated by recent developments in information technology and e-commerce, and their possible solutions.  Topics to be covered are selected from, but not limited to, copyright, domain name disputes and other intellectual property issues on the Internet, contractual issues of on-line trading, public key infrastructure and electronic transactions, privacy and data protection. 

Mutually exclusive with: COMP3311/CSIS0311 Legal aspects of computing and COMP7901 Legal protection of digital property


Supply chain and e-logistics management

The course is designed to prepare you to apply business strategies, analytical methodologies and information technology in supply chain management.  Traditionally industries have focussed on operation evaluation and performance improvement of mainly the manufacturing process; however, the deficiency of supply chain coordination results in severe downgrade of business competitiveness.  With advent of information technology, computers not only improve manufacturing operation and management and also strategic decision-making as well.  This course focuses on the systems approach to the planning, analysis, design, development, and evaluation of supply chain and e-logistics management. 


E-commerce technologies

This course provides an overview of technologies currently used in electronic commerce and an introduction to some technologies likely to play a major role in future.  Topics include (but are not limited to) Internet & e-commerce infrastructure, e-commerce presence & development life cycle, web design & implementation, mobile technology, Internet & e-commerce security, electronic payment systems, blockchain & cryptocurrencies, AI & machine learning, smart city & IoT, e-commerce technology trends.



This course considers how to create customer centric strategies for e-businesses.  Marketing focuses on the interaction between the producer and the consumer.  This focus remains unchanged in e-marketing, but our ability to foster this interaction with technology has been dramatically increased.  The Internet provides new forms of communications like web sites, e-mail, social media, and mobile communications.  However, these technologies do not necessarily replace traditional marketing vehicles like mass media, direct mail, and telephone marketing, but instead augment them to improve the customer experience.  The basic premise of this course is that these technologies can be used to fulfill the goal of a customer-centered marketing strategy.  

The goal for this course is to develop a set of principles so that managers can effectively develop and implement e-marketing strategies.  A core framework that we will use in this course is an interactive marketing strategy.  Interactive marketing goes by many names, including customer relationship management (CRM).  E-marketing allows companies to interact with consumers on an individual basis and create customized products and services using personalized knowledge about a consumer.  As part of this course we develop a compatible set of quantitative techniques to implement interactive marketing strategies.  Throughout the course we explore examples and cases to understand how e-marketing is evolving in practice.


Electronic payment systems

The course covers banking systems, e-payment security, foreign exchange, Internet banking, mobile payments, credit and stored-value cards, Octopus, micropayments, peer-to-peer payments, cryptocurrencies, blockchain, large-scale B2B payments, faster (instant) payments, seamless shopping and the future of money.  Particular attention is given to Hong Kong and Mainland China banking and payment systems.


Topics in electronic commerce

This course covers advanced topics in areas in electronic commerce that are relevant at the time.  Leaders in the field, expert practitioners and distinguished scholars in the field around the world will be invited to participate in this course.


E-financial services

This course provides students with the fundamentals of financial services in the context of e-Commerce and mobile devices.  Payment systems in general and various payment transaction systems in particular will be examined.  Similarly, eFinance has brought new concepts into e-Brokerage, e-Insurance, e-Lending and other fields.  The course covers technology, operations, customer experience as well as demonstrates how regulations and security aspects are impacted by developments like Bitcoin and Blockchain.  Studies of established banks as well as new FinTech Players serve as examples and reinforcements for many of the concepts.


E-business transformation

eCommerce has shortened business transaction cycles, expanded market reach, and allowed companies to build and manage customer relationship more effectively.  Companies need to transform their business model periodically with an eye to improving their operational effectiveness, entrenching their strategic position, and ultimately sustaining their competitive advantage.

As change is inseparable from life, and thus strategic advantage by definition transient, transformation and innovation are inseparable from business survival.  In order to thrive, businesses have to manage their processes effectively, revisit their value propositions periodically, and at times change their business model entirely.  Innovation and transformational initiatives, however, are difficult to implement and prone to failure as companies must grapple with a whole host of strategic, organizational, psychological and increasingly global issues.

This course builds on the basic principles of cognitive science, business and economics to examine the role of change as a strategic necessity.  It provides a roadmap for transforming companies into inter-networked enterprises where proprietary and shared infrastructures are used to link customers, suppliers, partners and employees to create superior economic value.  You will learn how the Internet can provide firms with the necessary infrastructure needed to align their business strategy with IT strategy, streamline front-end and back-end processes, manage relationships and partnerships, and adapt to emerging global issues such as outsourcing and offshoring.  In the process you will learn about the nature of change and business complexity and gain a better appreciation of the nature of organizational failure.

The course pays special attention to the adverse effects of cognitive biases in the transformation process by looking into the inner workings of the brain to understand, among other things, why we prefer the status quo and generally resist change, why we regularly act rationally irrational, why we cannot usually break away from our entrenched mental models to think creatively.



The dissertation project is to provide an opportunity for the student to dive in depth into either a business case and/or a technology development in the e-commerce and Internet computing, and apply their body of knowledge learned in the programme to implement the business plan and/or the relevant technology to demonstrate its feasibility in a real or simulated business environment.  This would involve substantive research into the chosen business plan and/or technology, implement and evaluate the proposed business plan or technology.  Finally consolidate the findings and conclusion in the dissertation, and demonstrate the project result.


Case study project

The case study project is to provide an opportunity for the student to dive in depth into either a business case or a technology development in the e-commerce and Internet computing, and apply their body of knowledge learned in the programme to understand and critically analysis the particular case.  This would involve substantive research into the “Subject”, collect appropriate data by suitable means, research into reports and publicly available information, and consolidate their findings and conclusion in a case study report.


Dynamic digital capabilities

This course covers the fundamental business and economic principles of dynamic digital capabilities as well as mobile platform innovation. Business in today’s global and exponential world must adjust to the dramatic changes caused by emerging technologies such as AI, Blockchain, Cloud and Data as well as smart cities, ecosystems, on-demand platforms and crowdsourcing 2.0. We provide a systematic framework, cases and hands-on experience in analyzing industries, cities and regions being transformed by digitalization, disruption, demonetization and dematerialization. Managers, developers, engineers and graduate students are guided in the development of ABCD business models and dynamic digital capability-building. Cases include multinational corporations, entrepreneurial startups, emerging unicorns and nonprofits worldwide.


Entrepreneurship development and ventures in Asia

This course provides an intense and mentored hands-on experiential learning opportunity where highly motivated entrepreneurial teams of students become co-founders of a high tech startup, competing in a competitive online Venture Startup Simulation Game. We cover and apply strategic thinking, industry analysis, competitive advantage, value chain analysis, Blue Ocean value innovation strategies and Digital plus AI-Data business models. This is a quick, fun, fast-learning and low-risk way to experience the nuts and bolts, the ups and downs and competitive dynamics of the launch and first year of a $3.5M VC funded venture startup. The second half of the course focuses on Applied AI ventures in Asia and how to develop a successful AI-data strategy and Demo Day “pitch”.


Building smart cities: an information system approach

Hong Kong, like a number of cities in China and overseas, is following global trend to develop and transform herself into a smart city.  The concept of a smart city is based on the application of ICT in various domains of the city to connect and integrate the systems and services of the city for better synergy and efficient use of resources.  The vast amount of real-time data generated by smart sensors can be integrated with the modern information and communication technologies, useful information and insights can then be derived by analytic techniques to optimize and automate city management.  Productivity can be boosted and sustainability can be ensured based on the effective collection, delivery and manipulation of the information in smart cities by innovative applications.  The ultimate goal of smart city development is to improve people’s quality of life and support the development of innovation and business enterprises.

This course presents an overview and the core concepts and techniques of building smart cities by utilizing the technologies like Geographic Information Systems (GIS), Location Intelligence, Open Data, Common Spatial Data Infrastructure (CSDI), Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI) etc., that are indispensable to the development and effective management of the key components of smart cities.  Key components of smart cities in the Smart City Wheel and various development stages will be discussed in details and current and potential technologies facilitating smart city development will be introduced.  Students will not only learn the concepts but also real applications being developed or used in smart cities.  A series of guest lectures will be arranged for our students to understand more about the actual implementations of smart city projects in various industries in Hong Kong.


Mobile and IoT computing services and applications

With nearly 5 billion mobile phone users worldwide, including well over 2 billion smartphone users, new mobile and IoT technologies are driving the development of a slew of new products and services.  This course introduces students to the technologies, applications, services and business models associated with the mobile Internet and the Internet of Things (“IoT”).  This includes looking at underlying technologies as well as important usability, security, privacy and business considerations, and learning to appreciate and analyze the challenges and tradeoffs they entail.  The course also provides an overview of future trends and ongoing research in this new and fast growing area. 


Machine learning for business and e-commerce #

This course provides the necessary fundamental concepts, theory and tools in Machine Learning (ML) to enable students to understand how Artificial Intelligence (AI) and ML can be applied in typical business applications in general, and for E-Commerce in particular.  As AI is a broad field of study, the course will focus on ML including an introduction to the fundamentals of ML, supervised and unsupervised learning, ML workflow, dataset preparation, handling and analysis, selection and training of ML models: regression, classification and clustering models; Support Victor Machines (SVM), decision trees, ensemble learning and random forests; introduction to Artificial Neural Networks (ANN), Large Language Model (LLM) and other neural network models.  The course will use ML projects and applications to demonstrate how ML can be used to solve real business problems.

# Pending for University approval


Digital transformation: strategy and people #

Change is constant and inseparable from life.

Survival in today’s volatile, uncertain, complex, chaotic and accelerating (VUCCA) world calls for continual adaptations to change.  In response, companies increasingly rely on digital transformation to redesign their business processes, revisit their value propositions and recalibrate their business models.  But transformation initiatives are difficult to implement and prone to failure as they entail a host of technological, organizational and human issues.

Digital transformation success revolves around the degree to which a company can tightly align its strategy, systems, processes and people with its business model.  More importantly, success hinges on how a company’s workforce adapts to change, thinks outside the box to see fleeting opportunities, and leverages emerging technologies to design, innovate and market high-margin products and services.

Building on two interlaced strands of inquiry this course relies on the principles of cognitive science, organizational behavior and strategy to examine the role of change as a strategic imperative.  It explores the nature of change, complexity, chaos and failure to highlight the importance of adaptation and transformation.

First, we examine the central role of human cognition in digital transformation.  We show that in spite of the importance of technology, the success of digital transformation is largely dependent on human factors.  By studying the inner workings of the brain, we demonstrate that resistance to change and inability to adapt are manifestation of cognitive biases that adversely engulf our thinking and behavior.  We highlight the pernicious effects of digital devices on our ability to focus without being distracted.  We also underline the role of mindfulness in transforming mind, unleashing cognitive potentials, fostering creativity and thus enhancing quality of our lives.

In tandem with the first objective we show that competitive advantage is by definition temporary because people and companies are subject to continual disruption.  We provide a roadmap for transforming companies into agile enterprises where customers, suppliers, partners and employees are linked together to create superior economic value.  In the process we explore how best to avoid the pitfalls of digital transformation.

# Pending for University approval


Securities transaction banking

The course introduces the business and technology scenarios in the field of Transaction Banking for financial markets.  It balances the economic and financial considerations for products and markets with the organizational and technological requirements to successfully implement a banking function in this scenario.  It is a crossover between studies of economics, finance and information technology, and features the concepts from basics of the underlying financial products to the latest technology of tokenization of assets on a Blockchain.


Blockchain and cryptocurrency

This course is for students who are not computer science majors.  In this course, students will learn the rationales behind the design of blockchain and cryptocurrency, the key technical / cryptographic elements that build up the blockchain technology, classifications of different types of blockchains, the comparisons of different blockchain platforms, what applications fit the best for the blockchain technology, and example applications in a wide range of disciplines.  This course will also introduce some popular cryptocurrencies, e.g. Bitcoin, discuss in details about bitcoin transactions, briefly introduce what a cryptocurrency exchange is, and the evil sides of cryptocurrencies (e.g. being the ransoms of ransomware and money laundry).


Financial fraud analytics

This course aims at introducing various analytics techniques to fight against financial fraud.  These analytics techniques include, descriptive analytics, predictive analytics, and social network learning.  Various data set will also be introduced, including labeled or unlabeled data sets, and social network data set.  Students learn the fraud patterns through applying the analytics techniques in financial frauds, such as, insurance fraud, credit card fraud, etc.

Key topics include: Handling of raw data sets for fraud detection; Applications of descriptive analytics, predictive analytics and social network analytics to construct fraud detection models; Financial Fraud Analytics challenges and issues when applied in business context.

Required to have basic knowledge about statistics concepts.


RegTech in finance

The course studies the use of regulatory technology, or RegTech, in the context of regulatory monitoring, reporting and compliance.  It demonstrates that the true potential of RegTech lies in its ability to effect a profound transition from a Know Your Customer (KYC) to a Know Your Data (KYD) approach, which relies on efficient processes for the collection, formatting and analysis of reported data.  The course covers the RegTech landscape and global challenges, the use of innovative technologies and disruption, RegTech investment, application for authorized institutions and industry adoption, illustrated with initiatives and examples in the Hong Kong context.  It also discusses social impact and regulation, and the future development of RegTech.


Smart banking and innovative finance #

This course provides an in-depth exploration of blockchain technology and distributed ledger technology (DLT) and their applications in the context of Smart Banking and Innovative Finance.  Students will gain a comprehensive understanding of the underlying principles, functionalities, and potential benefits and challenges of the emerging Financial Technology (FinTech) 3.0.

The course will cover the emerging trend in Smart Banking and Innovative Finance with various disruptive business-IT (DLT and BlockChain) models in the evolving FinTech ecosystem such as decentralized finance (DeFi), central bank digital currencies (CBDC) and Hong Kong SAR Government’s w-CBDC and rCBDC projects, eHKD/eCNY use cases, Open Banking and API (Application Programming Interface) ecosystem, Virtual Banks and Stored Valued Facility (SVF), Banking as a Service (BaaS), Banking as a Platform (BaaP), Faster Payment System (FPS) and cross-border payment/forex applications, smart contracts, tokenization and tokenomics, WealthTech, InsurTech, Self-Sovereign Identity (SSI), Zero Knowledge Proof (ZKP), and the related regulatory considerations.

Through lectures, case studies, in-class discussions, group presentations and reflective exercises, students will develop practical skills in designing, implementing, and managing blockchain and DLT solutions for Smart Banking and Innovative Finance.

# Pending for University approval


Internet infrastructure technologies

This course takes a systematic approach to study the various components which form the infrastructure of the Internet.  It provides a comprehensive coverage of existing and emerging Internet technologies and applications.  Topics include: access and backbone network technologies; IP addressing and routing architectures; standard transport and application protocols; operating principles and internals of network entities.  We will focus not only on how the Internet works but also its design rationale and engineering tradeoffs.


E-crimes: digital crime scenes and legal sanctions

This course helps participants to grapple with crimes in the electronic age from both technical and legal points of view.  It addresses three important aspects of the subject, namely, technologies adopted in e-crimes, legal sanctions and management of e-crimes scenes.  Topics covered include: trends in e-crimes; different types of e-crimes, tools and technologies for committing e-crimes; laws relating to e-crimes and criminal sanctions; digital forensics, post-incident and live-forensic crime scene management, chain of evidence, collecting and collating digital evidence.

Mutually exclusive with: COMP3311/CSIS0311 Legal aspects of computing


Topics in Internet computing

This course covers advanced topics in areas in Internet computing that are relevant at the time.  Leaders in the field, expert practitioners and distinguished scholars in the field around the world will be invited to participate in this course.


Website engineering

This course will introduce the standards, the software technologies and some good practices for implementing websites and web applications.  It aims at covering an "end-to-end" picture of content delivery and presentation on the web, that is, from the "server-sides" where data is stored, adapted or integrated, to the "client-sides" with various demands and capabilities.  It will suit students who wish to have a technical understanding on the subject or a career in website engineering, as it will introduce the techniques for building maintainable, extensible, interactive and mission-critical websites and web applications, using state-of-the-art standards and open-source tools.

The topics covered will be organized into four parts: (1) Website development basics (enabling standards and technologies, responsive web design, basic web security); (2) Design and implementation of web applications (rich Internet applications, client-side frameworks, MVC design patterns and libraries, content management systems); (3) Interoperability of web applications and services (web API protocols, mashups, cloud services for web development); and (4) Optimizations (traffic analysis, search engine and performance optimization techniques).


Data science for business #

The emerging discipline of data science combines statistical methods with computer science to solve problems in applied areas.  In this case we focus on how data science can be used to solve business problems especially those enabled by electronic commerce.  By its very nature e-commerce is able to generate large amounts of data and data mining methods are quite helpful for managers in turning this data into knowledge which in turn can be used to make better decisions.  These data sets and their accompanying quantitative methods have the potential to dramatically change decision making in many areas of business.  For example, ideas like interactive marketing, customer relationship management, and database marketing are pushing companies to utilize the information they collect about their customers in order to make better marketing decisions.

This course focuses on how data science methods can be applied to solve managerial problems in business.  Our emphasis is developing a core set of principles that embody data science: empirical reasoning, exploratory and visual analysis, and predictive modeling.  We use these core principles to understand many methods used in data mining and machine learning.  Our strategy in this course is to survey several popular techniques and understand how they map into these core principles.  These techniques are illustrated with case studies that involve decisions about targeting, product recommendation, customer retention and financial lending.  The class takes a learning-by-doing approach to analyze data and make decisions from these analyses.  However, the emphasis is not on the software for implementing these techniques but on understanding the inputs and outputs of these techniques and how they are used to solve business problems, and effectively communicate them to managers.

# Pending for University approval


Fundamentals of e-commerce security

This course provides an in-depth understanding of basic security problems and relevant e-commerce solutions, while helping students implement today's most advanced security technologies, such as designing secure Web, e-commerce, and mobile commerce applications, securing corporate internal network, and providing secure employee/user authentication.


Semantic data architecture

This course covers enterprise approaches for designing semantically-driven data architectures to enable information systems focussed on data sharing and interoperability.  These approaches also include data management functions, including data modeling, metadata, reference data, and data governance, in the context of enterprise architectures.  The course will develop advanced skills in understanding and applying data architecture methodologies and frameworks, including structured information modelling and data element representations that underpin global data standards.

The course has a strong focus on advanced semantic web technologies that make the web more data-driven and autonomous, allowing for more accurate searching, better data management, and easier access to information.  Semantic web technologies include formal ontologies, which help to categorise and classify data, and linked data, which connects disparate data sources together.  A semantic ontology is an organised system of knowledge - based on mathematical foundations - that describes the meaning and relationships of concepts within a domain.  It consists of classes, properties, and relationships between them. This structure is used to create a shared understanding between different agents across and within enterprises and drives rich inferences and advanced reasoning outcomes.

This course requires students to have a good knowledge web technologies, modern data modeling, and a good understanding of logic expressions and is suitable for students who want to pursue a career in contemporary data architectures for complex enterprises.


Digital forensics

This course serves as an introduction to students about current concepts and methodologies in conducting digital forensics investigation.  It gives an overview of post-mortem digital forensics analysis, network forensics analysis, mobile forensics analysis as well as live forensics analysis and provides students with hands-on experience of identifying, acquiring, preserving, analysing and presenting digital evidence.


Knowledge graphs #

Knowledge graphs - a powerful method for organising and managing complex information - offers a wide range of advanced benefits and capabilities for organisations to manage their data platforms.

Knowledge graphs empower businesses to unlock the full potential of their data including improved data integration, enhanced analytics, contextual understanding, efficient data governance, agile knowledge management, collaboration, artificial intelligence, and visualisation.  By leveraging the power and technological advantages of knowledge graphs, enterprises can drive innovation, gain a competitive edge, and revolutionise the way businesses operate in the digital age.

This course provides comprehensive coverage and understanding of the principles, techniques, and tools used to build and leverage knowledge graph platforms.  The course covers topics including knowledge graph modelling, representation and reasoning, vocabulary management, querying, large language models, and visualisation.  Emphasis is placed on practical real-world applications and hands-on exercises to reinforce theoretical concepts.

# Pending for University approval