This course aims to introduce the AI principles and the associated techniques. Students will learn the AI ideas and algorithms, and acquire practical insights into the current development of this field.

Students will gain the understanding of artificial intelligence (AI) as the essential technology in pursuing the digital transformation journey, through the discussion of AI basics, applications and tools with use cases in various functions of an enterprise including sales and marketing, customer service, operations, risk management and other support functions. While applications in different sectors will be explored, those for the banking industry will be highlighted. Students will also look at the issues and challenges of adopting AI technologies in addition to its benefits, and learn the implementation aspect of digital transformation. This course is designed to prepare students to take part in digital transformation projects involving AI technologies in different roles such as a business user, solution analyst, project manager and AI solution provider.

This course introduces the fundamental programming constructs of the Python scripting language and its applications in data analytics and artificial intelligence. Students will develop the essential programming and problem-solving skills through a series of hands-on exercises on these two domains.

This course gives students some advanced topics in the areas of computer vision and pattern recognition.

This course is to provide an in-depth knowledge of natural language processing and a wide-range of downstream applications. Topics include: fundamental concepts, conceptual modeling of a natural language, part-of-speech tagging, syntactic parsing, critical thinking of downstream applications, and deep learning techniques for focused problems. The students will have a thorough understanding of natural language processing technique, and be able to creatively design models and critically analysis their effectiveness after taking this course.

The course offers a study of the mathematical modeling and simulation techniques for distributed systems and networking. It also provides case studies on one or more of the advanced topics in distributed systems, cloud computing, edge computing, computer networks, wireless networks, and mobile networks.

This course gives students a comprehensive knowledge on computer vision. Recent research advancements in selected computer vision topics will be covered. The student will also be required to design and develop a computer vision application prototype.

This course provides opportunities for students to apply programming skills and software tools for solving data analytics and artificial intelligence (AI) problems. The students will be given a series of discovery laboratory exercises and problem-solving exercises. Each exercise is accompanied by a short briefing lecture. A discovery laboratory exercise allows students to get familiar with the basics and the syntax of a particular tool, plug-in, or library. A problem-solving exercise asks students to apply single or multiple tools/plug-ins/libraries to solve some real-world problems. Students will be learning skills for data management and preprocessing, quantitative analysis, data mining, modeling and training, and data visualization. Some mini-projects will be given to students as capstone assessments so that they will be approaching problems with skills they have learned and practiced in the course.

This is an advanced course that will not only focus on the recent literature on the applications of machine learning to problems from a range of different areas, including image/signal processing, robotics, information retrieval and data mining, but also let students learn the state-of-the-art learning theories and techniques based on statistics, neural networks and information theory.

This course provides an in-depth knowledge of technology applications and management skills in the financial industry. After completing the course, students will understand the disruptive business models, rules and regulations, and the latest technologies adopted in the industry. Students will be able to evaluate the real-world cases using the design thinking approach. 

Students are exposed to the current IT research, professional development, and practice via seminars, IT forums, and presentations given by academic scholars, IT professionals, and research students. After completing this course, students will:
(1) learn the frontier knowledge of IT research and professional development;
(2) broaden their mind and inspire innovative ideas in their research areas;
(3) understand the current IT practice; and
(4) share their experience with academic scholars and IT professionals.

The course deals with the planning for using digital channels and social media to support organization’s marketing purposes. 

This course aims to introduce fundamental issues of big data management and the common data management techniques and tools including streaming and I/O efficient algorithms, distributed computing, and NoSQL storage and processing. In addition, advanced topics and an in-depth case study of Apache Spark for various applications on streaming, SQL, and graphs will also be covered. Furthermore, the potential applications of big data management to several areas such as business, finance, and so forth, are shown via examples and practices.

This course introduces principal concepts of data analysis and data management and their applications in real-life business problems. Topics mainly include 1) fundamentals of quantitative methods; 2) representation of data in a relational database and formulation of data query; 3) knowledge of data analytics and data mining; 4) data visualisation concepts.  

Digital Experience Innovation aims to enrich human experience with the wide variety of cutting-edge technologies (e.g. AI, Immersive Technologies AR/VR, IoT, etc.) and media that are available. The course will introduce the processes, methodologies, tools and techniques needed for developing cutting‑edge digital innovation projects, especially involving AI components, anticipating future needs and trends. Students will learn examples and apply skills in a broad range of contemporary industries from art, banking, entertainment, education, sports, marketing, rehabilitation, healthcare, etc. 

The course offers a study of the advanced techniques and tools of big data analytics and management. It also provides case studies on one or more of the advanced topics in computer vision, natural language processing, big graph analytics and management, and health informatics.

This is an advanced course that will not only let students learn the state of the art knowledge data engineering concepts, process es and system s but also cover the recent literature on the applications of knowledge and data engineering techniques to problems from a range of different areas, including social networks, mobile and spatial data, and transactional data.

To introduce the concepts and issues behind optimization problems, and the principles behind different optimization algorithms. Topics include both unconstrained and constrained optimization algorithms.

To introduce the theories and concepts of numerical methods and how they can be implemented for solving computer science research problems.

This course aims to prepare students for advanced research by examining how to plan, conduct, and report on research in the Computer Science field. Students will learn the methods involved in each step of a research project, including formulating research problems, problem solving techniques, theoretical/empirical validation, and publishing. Students will also examine examples drawn from different research areas as case studies on various aspects of the principal methods for lifelong learning.

This course provides an in-depth understanding of data security and privacy protection techniques from both theoretical and practical aspects. Students will learn basic data encryption, integrity protection, and privacy protection techniques. Students will also learn advanced data security and privacy techniques such as access control and cloud data security. In addition, data security and privacy policies and regulations will be introduced. This course offers opportunities to explore cryptographic tools for data security and privacy protection and apply them to different use cases.

This course aims to introduce various quantitative methods that are necessary for data analytics and artificial intelligence. It takes a computational approach in teaching the quantitative methods such as linear algebra, univariable and multivariable differentiation and calculus, probability and statistics, and optimization. Students will learn and master the concepts of quantitative methods through analyzing representative data analytics and artificial intelligence models/algorithms; and meanwhile they will acquire problem-solving skills for data analytics and artificial intelligence.

Students will learn state-of-the-art topics in intelligent information systems. Emphasis will be placed on the current issues, methodologies and/or practice. After completing this course, students will understand the selected topics in intelligent information systems.

This course provides an in-depth understanding and hands-on experience of the blockchain technology. Students will learn the concepts and techniques behind different types of blockchains, including mining mechanics, consensus protocols, smart contracts, and so on. Students will also learn blockchain application development skills via guided labs and projects.

To provide a study of intelligent decision making processes and relevant tools that support such processes. Students will learn the challenges and techniques of decision support in an environment with imperfect and changing information. Both the qualitative and the quantitative aspects of intelligent decision support will be covered. They will also learn the related architectural design, structure, functions and components of decision support systems.

Students will learn state-of-the-art topics in artificial intelligence. Emphases will be placed on the latest development of related methodologies and/or practice. After completing this course, students will understand some current topics and methodologies in the area of artificial intelligence.

This course will introduce the latest biometric technology and its applications. Student will learn basic and fundamental theories and algorithms for different modality of biometrics as well as how to develop a biometric system. While different modalities will be discussed, this course will focus on three most popular biometrics, namely fingerprint, face and iris.

The topics of this course mainly include 1) basic concepts such as user preference and prediction; 2) a variety of typical recommendation approaches including collaborative filtering, content-based filtering, matrix factorization, and neural-network-based approaches; 3) system evaluation design and metrics; 4) the role of human factors in system implementation and user-centered evaluation; 5) popular applications in e-commerce sites and social media.

This course aims to introduce the principles and techniques of machine learning. Students will learn the machine learning techniques and acquire practical insights into the current development of this field.

Students will learn state-of-the-art topics in data analytics. Emphasis will be placed on the current issues, methodologies and/or practice. After completing this course, students will understand the selected topics in data analytics.

To equip students with essential knowledge to design and implement web and mobile applications for data acquisition, storage and visualization. 

Students work on group or individual system development projects. Each project is supervised by an academic staff, and it may be co-supervised by practicing professionals. The project demands careful planning and creative application of underlying theories and enabling technologies. Students can select project in consultation with their project supervisors. A written report and an oral presentation are required upon successful completion of the project. Each project will be assessed by the supervisor(s) and one additional academic staff on four aspects: (i) project management and progress, (ii) methodologies and results, (iii) report writing, and (iv) oral presentation. Through these projects, students will develop: (i) mastery of integrating concepts with practice in information systems, (ii) creative and systematic problem solving skills for analyzing, designing, and implementing information systems, and (iii) report writing and presentation skills for effective communication in IT enterprises.

This course is to introduce financial markets mechanics and Direct Market Access. Financial asset classes and algorithmic trading will be studied. Risk management and trading psychology will be discussed. In addition, technical analysis such as price trends, position sizing, and latency will be covered. Basic operational concerns on trading will be examined. Hands-on computer experience in trade execution will be given.

This course provides an in-depth knowledge of technology applications in the financial industry. After completing the course, students will understand the financial concepts and operations, and the impacts of information technology to the financial sector. Students will also practice the use of selected financial applications and learn how to develop an application to support financial operations.

This course provides students with an integrative perspective of information systems and development by introducing different kinds of information systems and describing the underlying methodologies for such development. Topics include, but not limited to: model of information system, integrated view of different methodologies, methodology framework, soft systems methodology, and object-oriented methodologies. Through this course, students will be able to develop new models and solutions for an information system.

This course aims to introduce students to the fundamental concepts and techniques in computer and network security, and giving students an overview of information security and auditing, and to expose students to the latest trend of computer attack and defense.  Other advanced topics on information security such as mobile computing security, security and privacy of cloud computing, as well as secure information system development will also be discussed.

This course aims to cover key concepts and design principles related to enterprise application architecture and enterprise application integration. It includes topics like layering structure, business logic organization, patterns for object/relational access layers, model-view-control patterns for Web, message-based enterprise application integration, and recent advances in enterprise application architecture. 

This course provides an in-depth knowledge of development of enterprise information systems (EISs). Topics include alternative development strategies, agile development, software maintenance and functionalities of EISs.

This course provides an in-depth knowledge of enterprise networking and cloud computing. Topics include Ethernet LANs, wireless LANs, MANs, WANs, TCP/IP internetworking, network security, network management, cloud computing architecture, cloud computing services, design and implementation of cloud computing.

This course provides an in-depth knowledge of technology applications in financial industry. After completing the course, students will understand the financial operations and the impacts of information technology to the financial sector. Students will also practice the use of selected financial software and learn how to develop an application to support financial processes.

This course is to introduce algorithms in financial markets. Interest rates, term structure, bonds, and bond markets will be studied. Factors affecting bond price volatility will be discussed. In addition, financial market mechanics such as stocks, options, and futures will be covered. Basic algorithms of hedging and trading strategies using options and futures will be examined. Hands-on computer techniques for these calculations will be given.

This course aims to introduce basic concepts in operational finance, such as financial statements concepts, financial ratio analysis, and etc., and to describe the techniques and tools that support financial decision making. Students will learn how to apply the decision analysis and making techniques and tools to various phases of financial processes.

In this course, students will learn fundamental image processing techniques, characteristics of different types of medical images, and how to apply different classical image processing techniques to different types of medical images. Students will also learn the basic concept, structure as well as the components in Picture Archiving and Communication Systems (PACS).

In this course, students will learn the advanced techniques and methodology of health information management, and the models and algorithms used in computer-based public health and clinical decision making. They will also learn the related architectural design, structure, functions and components of decision support systems.

This course provides a comprehensive study of the key architectural principles, open standards and development technologies behind healthcare information systems. At the same time, it introduces the present state of the art as well as the future trends in the development of electronic health record systems, and discusses several core technical issues in acquiring, integrating, analyzing and utilizing healthcare data.

This course covers the healthcare systems applicable to Web, social media, and ubiquitous environment. It will explain to students how the healthcare system can monitor patients and elderly as they maintain their normal everyday activities, through body sensors and home environment sensors. It will further introduce how the data are collected to make trend analysis, determine state of well-being and warn health workers of potential problems.

This course provides an introduction to and overview of user interface design and usability testing. It integrates theories and methodologies from computer science, cognitive psychology, design, and many other areas. Issues include: command languages, menus, forms, and direct manipulation, graphical user interfaces, computer supported cooperative work, information search and visualization, World Wide Web design, input/output devices, and display design. 

Students work on group or individual system development projects. Each project is supervised by an academic staff, and it may be co-supervised by practicing professionals. The project demands careful planning and creative application of underlying theories and enabling technologies. Students can select project in consultation with their project supervisors. A written report and an oral presentation are required upon successful completion of the project. Each project will be assessed by the supervisor(s) and one additional academic staff on four aspects: (i) project management and progress, (ii) methodologies and results, (iii) report writing, and (iv) oral presentation. Through these projects, students will develop: (i) mastery of integrating concepts with practice in information systems, (ii) creative and systematic problem solving skills for analyzing, designing, and implementing information systems, and (iii) report writing and presentation skills for effective communication in IT enterprises. 

This course introduces health information privacy from legal, ethical, technical and economic aspects. Students will learn conceptions and legal foundations of health information privacy, security primitives, different privacy models, different anonymization algorithms, privacy technologies for biometrics, and privacy solutions for extended health data sharing scenarios. Students will also learn the economics of health information privacy. This course provides opportunities to explore cutting-edge privacy solutions in the context of health information and apply privacy technologies to real-life applications.

This course aims at providing students with the opportunities to improve their understanding of the web and mobile information system developments. Through this course, students will learn: (1) how to install, manage and maintain the information systems, and (2) the web programming and the database techniques, as well as hands-on experience, for developing web information systems, (3) how to extend the information systems to mobile platforms.

Students will learn state-of-the-art topics in advanced information systems. Emphasis will be placed on the current issues, methodologies and/or practice. After completing this course, students will understand the selected topics in advanced information systems.

This course aims to introduce the overview and the developing concerns of enterprise architecture. Functionalities of enterprise information systems and enterprise-scale agile software development concepts are included. Enterprise systems integration approach and performance evaluation of enterprise information systems are also covered.

This course introduces basic concepts of data communications and networks. The principles of the Internet and world wide web are discussed. The techniques for cloud computing and development of edge computing are studied. Students will also acquire hands-on experience in mobile application programming. Students who complete this course will be suitably prepared for the other courses offered in the MSc in IT Management curriculum.

This course provides the foundation concepts in managing IT resources and enabling digital transformation to meet business needs.

Students are exposed to the current IT practices through seminars given by IT professionals and academic staff, interacting in small groups with IT practitioners, and/or company visits. After completing this course, students will understand the current IT practice.

The course introduces the management of information technology as it is being practiced in organizations today to produce value for businesses and consumers.

This course deals with project management and addresses issues in information technology project development. On completion of the course, students should: (i) have acquired basic skills for project managers, (ii) be able to develop and prepare project plans for effective resource utilization, and (iii) be able to manage IT development projects.

This course is to give students a thorough grounding in the theory, techniques and practical issues involved in computer-based information systems auditing. The students will have an in-depth understanding of auditing concepts and methods after taking this course.    

This course examines legal and ethical issues in the use of information technology. On completion of the course, students should: (i) understand privacy, intellectual property rights, contracts & licenses as well as common criminal issues, (ii) understand the legal obligations of a computer professional, (iii) understand computer ethics and the importance of professional codes of conduct, and (iv) be able to derive and justify a personal position on moral and ethical matters related to computers in society.

This course covers the use of technology in many aspects of a business, with particular emphasis on concepts and practices for modeling, specifying and integrating within-enterprise and B2B business processes.  How the business process related to customer relationship management, enterprise resource planning, supply chain management, etc. could be transformed in the Internet era will be covered. Some case studies related to e-transformation in Business will also be discussed. Students after taking this course should be able to 1) understand how e-technologies can facilitate process/application integration with and across enterprise, and 2) evaluate the cost and benefit that e-transformation can bring to different business processes of an enterprise.

To extend the student's knowledge of information management systems and development methodology through the study of advanced theories and methodologies, and to examine the critical issues of current information systems (IS) research, so as to provide a student an integrative perspective of information management systems and development.

This course introduces the fundamental concepts as well as practical applications of Web Intelligence (WI) which combines contemporary Artificial Intelligence and advanced Information Technology in the context of Web-empowered systems, environments, and activities. Also, advanced topics related to Web Intelligence (WI) and their impact to different sectors of the society will be covered. After taking this course, students should be able to 1) identify the possible impact of Web Intelligence in the society, and 2) apply WI related techniques to advance existing Web-based systems and on-line business platforms.

This course is to provide an in-depth knowledge of relational database management systems (RDBMS). Topics include: conceptual modeling of a database, relational data model, relational algebra, database language SQL, relational database design, data storage, index structures, external sorting, query evaluation, transaction processing, concurrency control, and crash recovery. The students will have a thorough understanding of RDBMS after taking this course.

This course aims to introduce fundamental issues of knowledge discovery and the common data mining techniques including statistical methods, machine learning methods, and efficient algorithms. The main data mining techniques including classification, clustering, association rule mining, and also outlier detection. In addition, advanced topics such as graph mining and social network analysis will also be covered. Furthermore, their potential applications to a variety of areas such as business, finance, medicine, and so forth, are shown via some case studies.

Students will learn the principles of the Internet and the World Wide Web and study some advanced/current topics. After completing this course, students will understand the principles of the Internet and the World Wide Web and be able to develop and manage Internet systems.

This course will develop students' understanding of recent developments in e-technologies, including XML, Web services, service-oriented architecture, Web-enabled business processes, as well as related architectures, tools, and applications. It will also enable students to acquire the capability to design and develop software systems based on e-technologies and to apply them to some domain applications.

Students work on the projects proposed by themselves. Each project is supervised by an academic staff, and it may be co-supervised by practicing professionals. After completing the projects, students will submit written reports and present their results (e.g., new methodologies, IT systems, or critical surveys). Each project will be assessed by the supervisor(s) and one additional academic staff on four aspects: (i) project management and progress, (ii) methodologies and results, (iii) report writing, and (iv) oral presentation. Through these projects, students will develop: (i) mastery of integrating concepts with practice in IT Management, (ii) creative and systematic problem solving skills for designing, analyzing, managing or developing IT systems, (iii) self-learning capability for sustainable self-development in the rapidly changing IT field, and (iv) report writing and presentation skills for effective communication in IT enterprises.

This course introduces the basic principles and technologies of information and knowledge management. Information storage and retrieval systems, knowledge management solutions, and knowledge management systems will be covered. Students will be able to understand the impacts of information and knowledge management in business and organization. They will be able to utilize information and knowledge management to maximize productivity.

Students will learn state-of-the-art topics in business analytics. Emphasis will be placed on the current issues, methodologies and/or practice. After completing this course, students will understand some current topics in and methodologies of business analytics.

Students will learn state-of-the-art topics in IT management. Emphasis will be placed on the current issues, methodologies and/or practice. After completing this course, students will understand some current topics and methodologies of IT management

Students will learn state-of-the-art topics in knowledge and information management. Emphasis will be placed on the current issues, methodologies and/or practice. After completing this course, students will understand some current topics in and methodologies of knowledge and information management.

Students will learn state-of-the-art topics in Internet and Web technologies. Emphasis will be placed on the current issues, methodologies and/or practice.  After completing this course, students will understand some current topics in and methodologies of Internet and Web systems.

This course aims to introduce different analytic models used in the management of information technology. These include practical applications of quantitative analysis techniques in business decision making, process modeling, planning and evaluation. The course focuses on the ability to recognize the appropriate models applicable to diverse information technology management situations, and to identify solutions to them. Emphasis will be placed on problem formulation and solution application rather than mathematical derivations.

Students will learn the methodologies and concepts of business intelligence, including the characteristics, architectures, and the development of data warehouses, data lake, real-time processing and data analytics. After completing the course, the students will understand the features and applications of business intelligence techniques. Emphasis will be placed on the understanding of enabling technologies and their applications to improve operations and decision making in business contexts.

To provide an interdisciplinary study of visual analytics and decision support. Students will learn the fundamental concepts, methodologies, techniques, and tools in interactive visualization for the purposes of facilitating data understanding, analytical reasoning, and decision making.  After successful completion of this course, students will be capable of recognizing the needs and impacts of visual problem-solving with data in the context of decision making and proficient in applying relevant methodologies, techniques, and tools

Students will learn the principles and practices of information security management at different levels: bit level, message level, protocol level, system and network level, and managerial level. They will also learn the current topics, including blockchain.

The development of information technology and innovations plays an increasingly important role in enhancing the competitiveness of countries, organizations, and individuals. This course prepares students for the technology and information economy by providing the knowledge and skills necessary for innovation management and entrepreneurship. With particular emphasis on information technology-related activities, this course aims to (i) introduce students to the fundamental concepts, practices, opportunities, and challenges related to innovation management and entrepreneurship, (ii) provide students with frameworks and tools for the successful management of innovation from idea generation to market exploitation, and (iii) stimulate students’ interest in entrepreneurship and thus cultivating an entrepreneurial spirit.

E-business offers real and abundant opportunities for small, medium and large companies throughout the world. However, success in e-business rarely happens without strategy. This course exposes students to contemporary management thinking, methods, and strategies necessary to effectively build and manage e-business systems. This course aims to: (1) introduce students to the fundamental concepts and approaches of strategic management, (2) provide students with a comprehensive framework for understanding the business models and strategies for e-business, and (3) prepare students to be active participants in formulating and implementing e-business strategies for organizations.

This course aims to introduce the basic knowledge of big data analytics as well as the common data analytics techniques and tools. Furthermore, their potential applications to a variety of domains such as business, finance/banking industry, and health care are shown via case studies.

This course introduces the techniques underlying the design and engineering of distributed systems and cloud computing systems. Topics include cloud and distributed system models, computer clusters, virtualization, cloud storage and data centers, cloud-enabling technologies, cloud mechanisms, and cloud architectures. Students will also acquire hands-on experience in cloud programming and software.

Students will learn and master information searching skills, writing skills and presentation skills for undertaking IT projects.

Each student is required to work on an academic research project independently under the supervision of an academic staff. After completing the research projects, students will submit written research papers and present their research results. Each project will be assessed by the supervisor and one observer on four aspects: (i) project management and progress, (ii) methodologies and results, (iii) paper writing, and (iv) oral presentation. Through these research projects, students will learn and practice how to identify research problems, conduct literature reviews, criticize and analyze existing solutions, propose and evaluate new solutions, write and present research papers.

Each student is required to work on an academic research project independently under the supervision of an academic staff. After completing the research projects, students will submit written research papers and present their research results. Each project will be assessed by the supervisor and one observer on four aspects: (i) project management and progress, (ii) methodologies and results, (iii) paper writing, and (iv) oral presentation. Through these research projects, students will practice how to carry out independent research, propose and evaluate new solutions, write and present research papers.

This course aims to cover key concepts, technologies and skills in web and mobile programming, including HTML, CSS, JavaScript, server-side scripting language, database connectivity and web protocols. After the completion of this course, students will be able to develop web and mobile applications with dynamic and interactive contents.

This course introduces principal concepts of data management and analysis. Topics mainly include: 1) representation of data in relational database and formulation of data query; 2) knowledge of data analytics and data mining; 3) data visualization concepts; 4) principles of data security and privacy management.