Students are required to complete at least 24 units (8 graduate courses) for graduation.
MScIE comprises both lectures and practical workshops in the field of information engineering, technology management and research project. Besides, students will have the flexibility to explore other offerings within the Faculty of Engineering and in the Faculty of Business Administration.
*The following courses are applicable for the academic year 2023-24. The availability of courses in each academic year is dependent on the availability of instructors.
Physical characteristics of radio channels, cellular coverage, noise and interferences; radio modem technologies; channel assignment by frequency, time, or code division; handoffs and mobility management; wide area wireless network case studies: GSM and 3G; local area wireless network case studies: IEEE 802.11 and IEEE 802.15; principles of satellite communications, introduction to GPS system.
(Not for students who have taken ESTR4304 or IERG4100)
Optical fiber and transmission characteristics, optical sources (lasers and light-emitting diodes) and transmitters, photodetectors and optical receivers, optical passive and active components: couplers, filters, switches, modulators, EDFA and Raman amplifiers, etc., optical system design, lightwave systems and networks: undersea systems, optical multia-access network design, SONET/SDH, fiber-in-the-loop, passive optical networks, optical network management.
(Not for students who have taken ELEG3303 or ESTR3206 or IERG4030)
Digital text, image, audio and video coding techniques; digital image and video processing; standard of video compression: MPEG and H.261; advanced topics in multimedia systems and applications.
(Not for students who have taken IERG4190)
This course will introduce to the students emerging topics in information engineering. The detailed course contents may be changed from year to year depending on the current development and the teacher specialty. Course assessment is at the discretion of course teacher.
This course aims to enhance students’ knowledge in cryptography as well as information security and privacy, in both theoretical and practical ways. The course introduces cryptography at an elementary level, enabling students to appreciate on its application to information security and privacy. Daily applications of cryptography will be discussed, including digital certificate and Public Key Infrastructure (PKI), Virtual Private Network (VPN), wireless communication security, as well as security and privacy issues in online social networks.
Entrepreneur characteristics; product innovation: factors driving innovation, creation and evaluation of new product ideas, risk assessment of commercialization, critical factors for success; business planning: market assessment and strategy, business model, product planning, financial planning, cash flow; financing options, negotiation and deals; formation of a new venture: team, company and product building; execution and dealing with reality; exit strategies; case studies related to innovation and entrepreneurship in information engineering.
(Not for students who have taken CMSC5730 or ENGG3802 or ENGG3803 or ENGG5700 or ESTR3502 or FTEC5570 or IERG5340 or SEEM3450)
The course covers the principles and applications of various emerging communication technologies to support the current high-capacity and flexible telecommunication networks. The topics include telecommunication network infrastructures, advanced optical fiber and wireless transmission techniques, network control and management, and smart applications. The current topics include optical transport networks, wireless LTE, software-defined networking, fiber-wireless systems, enabling technology for Internet of Things, etc. The topics will vary from year to year.
(Not for students who have taken IERG4340)
The World-Wide Web increasingly becomes the popular choice for delivering interactive applications, offering advantages such as instantaneous access, automated upgrade, online collaboration. This course introduces web technologies including client-side scripting, server programming, database, and user interface. It also briefly describes other related topics such as free/open hosting platforms and SaaS (Software as a Service), open API, virtualized servers on cloud. RIA (Rich Internet Application) across the online and mobile networks. Students also learn web programming concepts, and learn common web security threats and how to avoid them. Hands-on projects may be used to enhance the experience and the appreciation of the topics.
(Not for students who have taken IERG4210)
This course introduces technology strategy and management. The challenges of technology companies (such as hardware, software, internet, consumer electronics, communications and networking) regardless they are in startup or mature stage, are very different from other industries. They need to consider five aspects carefully to formulate an effective strategy. A framework of strategy in technology-intensive companies will be introduced. This framework consists of 5 components:
1. Network Effects
2. Multi-sided Platforms
3. Intellectual Property (IP) and Standards
4. Technology Commercialization
5. Digital Convergence
Social networking concerned with the conduction of various social behaviors over the internet, as well as the underlying technologies. It is an interdisciplinary subject involving multiple fields including computer networks and applications, psychology, as well as sociology. This course provides a holistic overview on both technology and humanity aspects of social networks, with emphases on the social sciences aspects and perspectives. It covers topics such as social network analysis (e.g. discourse analysis, semantics, social network pattern), network-mediated knowledge building and collaboration, epistemology in social networks, and applications of social networks in business and education.
The course aims to introduce various advanced wireline (copper wire and optical fiber) and wireless communication technologies to realize first-mile broadband access for video and data services. The wireline technologies include hybrid fiber coax (HFC), digital subscriber line (DSL), data over cable service interface specification (DOCSIS), passive optical network (PON) and fiber-to-the-home/premise (FTTH / FTTP), and broadband over powerline (BPL). The wireless technologies include multichannel multipoint distribution service (MMDS), local multipoint destribution service (LMDS), wireless local loop (WLL), WiFi and WiMAX, free-space-optics (FSO), and ultrawideband (UWB). Radio frequency identification (RFID) technique and applications. Fixed / mobile convergence access networks. Enabling technologies and network applications for home networks. Cases studies.
This course studies the essentials, advanced topics and emerging technologies on mobile network programming on two popular mobile platforms – Android and IOS. Topics include the mobile programming language fundamentals, application framework, application components, network programming, multithreading and so on. Further, different distributed server architectures and models that can offer scalability and extensibility will be highlighted.
This course gives an overview of social media, studies how different tools in information science can be used to analyse social media content, and how these results can be useful in different applications. This course will cover both knowledge in computational analysis of social media and the corresponding social networks, and basic technical skills in Python programming for the analysis.
The course introduces the basic underlying cryptographic concepts of blockchain as a powerful tool to support distributed ledgers in all digital transactions. The significances of trust, anonymity, and consensus mechanisms are discussed. The course further explores the applications of blockchain and smart contracts in various practical applications, including financial services, distributed systems, and specific domains such as smart city, healthcare, logistics and supply chains, etc.
Data science is a cross-disciplinary study involving informatics, machine learning, and statistics. This course discusses various components in the pipeline of a data science project, which include Python programming, data pre-processing, feature selection, common machine learning algorithms and data visualization. A problem driven approach is adopted to discuss applications of data science in various real-life examples.
The course introduces the principles, architectures, enabling technologies and smart applications of Internet of Things (IoT) systems. Various technology options for smart object identification, sensors, machine-to-machine communications and protocols, cloud computing and big data analytics, security, as well as their design considerations will be discussed. Emerging smart applications of IoT in various fields such as healthcare, transportation, logistics, manufacturing & production, home automation, smart city, will be studied.
This course explores technologies, techniques, and designs of data-center and cloud-based networking services. Real-world production networks from various cloud providers will be used as examples.
Topics include a brief recap of fundamental computer networking concepts (routing, TCP, etc.), data- center networks, multipath topologies and routing, load balancing, network virtualization, Software-Defined Networks (SDN), Network Function Virtualization, new transport protocols, hardware offloading and acceleration (FPGA), in-network computing with programmable switches (P4), congestion control, network management and verification, etc. The course also discusses the main elements of the data-center networking infrastructure, including the topologies and techniques that are used to scale such networks to hundreds of thousands of servers and the services and accelerators that are used to scale the performance of the distributed/ cloud-based applications/ services that are hosted by data-centers.
This course aims to provide students an understanding in the operating principles and hands-on experience with mainstream Big Data Computing systems. Open-source platforms for Big Data processing and analytics would be discussed.
Topics to be covered include:
• Programming models and design patterns for mainstream Big Data computational frameworks;
• System Architecture and Resource Management for Data-center-scale Computing;
• System Architecture and Programming Interface of Distributed Big Data stores;
• High-level Big Data Query languages and their processing systems;
Advisory: This course contains substantial hands-on components which require solid background in programming and hands-on operating systems experience.
(Not for students who have taken ESTR4316 or IERG4330)
Machine learning refers to making computer perform various tasks by learning from data. It is also now one of the essential components in many online services, for example, to generate personalized recommendations on e-commerce platforms, perform face detection and recognition or predict the arrival time of delivery, etc. Given the widespread usage of machine learning, it is important that complex machine learning models can be deployed in an efficient way to support real time services at scale and to allow seamless update of the models. This course will first introduce fundamental concepts in the architecture of scalable internet-based services, distributed/network programming and infrastructure support for content delivery. It then goes on to introduce how scalable online services can be created and maintained, with a focus on services that involve machine learning.
Topics will include asynchronous programming, distributed message queues and brokers, load balancers, micro-services, distributed caches and databases, and challenges and solutions in building and deploying various machine learning models/services in a production environment.
Advisory note: Students are expected to have background in computer networking and machine learning.
(Not for students who have taken IERG4080 or ESTR4312)
Students may also enroll in credit-bearing research project course and internship course during their study:
Student will work independently under the supervision of a faculty member on a research project in Information Engineering. The topic and scope of the study is to be agreed between the student and the supervisor. A project report is required at the end of the course.
Student will work independently under the supervision of a faculty member on a research project in Information Engineering. The topic and scope of the study is to be agreed between the student and the supervisor. A project report and an oral presentation are required at the end of the course.
(Prerequisite: IEMS5910)
This course is designed to allow students to acquire a basic understanding and the skills of the practical aspects of the information engineering profession. During the internship, the student must attach to a company in a study-related position for no less than 12 weeks. The student will have an academic supervisor (as primary supervisor) and an industry co-supervisor from the company, both have the expertise to provide advice to the student. To be qualified for award of the subject credit, the student must submit a report summarizing the internship experience at the end of the internship. Additional presentation may be required by the hosting company.
The internship should normally take place in the summer term after a student has finished the first two semesters of studies. Part-time students can decide to undertake the internship in the summer term of either the first or second year of studies.
Students can also select courses (including MPhil-PhD courses) offered by the Department of Information Engineering.
MSc in Biomedical Engineering
MSc in Computer Science
MSc in Electronic Engineering
MSc in Mechanical and Automation Engineering
MSc in E-Commerce and Logistics Technologies
MSc in Systems Engineering and Engineering Management
Students may select up to 6 units of courses with 5000-level offered by the above MSc programmes.
MSc in Business Analytics
Students may select up to 3 units of courses with DSME 5000-level offered by the above MSc programme.
Please visit the course catalog for the course outcome, enrollment requirement, no. of units etc. Availability of courses are subject to change. The programme reserves the right to make adjustments to the class schedules prior to the start of the respective semester.
MScIE offers Academic Achievement Scholarships to students who have demonstrated their academic excellence and outstanding performance during the study.
The Chinese University of Hong Kong places very high importance on honesty in academic work submitted by students, and adopts a policy of zero tolerance on cheating in examinations and plagiarism. Any related offence will lead to disciplinary action including termination of studies at the University.
Students should make himself/herself familiar with the policy and thereby help avoid any practice that would not be acceptable.
