Subjects

Table I
Code
Modules
Credits
Lecture hours
Pre-requisite
COMP6121 
Introduction to Internet of Things  

This module provides a comprehensive overview of the Internet of Things (IoT) from the global context. A number of technologies enabling IoT will be included, which are IP networking, wireless communication, Arduino programming, etc. They create the environment by allowing interaction between machines, smart devices, ubiquitous computers, physical objects and human users. This module is an introduction to the fundamentals of IoT, designed for either Information Communication Technology (ICT) or non-ICT students. In particular, the module will define the core system architectures, including but not limited to, the middleware to design single device and multi-device systems. It will also offer hands-on experience in labs to build smart device applications.
3
45 hrs
---
COMP6122 
Introduction to Big Data  

Introduction to Big Data covers the new large-scale programming models that allow easily creating algorithms that process massive amounts of information with a cluster of computer nodes. These platforms hide the complexity of coordinating complex parallel computations across the cooperating nodes, instead providing to developers a high-level programming model. The module is based on the MapReduce programming model. Lectures explain how multiple data analysis algorithms can be expressed under this model, and executed automatically over clusters of machines. The module also covers the internal mechanisms that a MapReduce framework uses to coordinate and execute the job among the infrastructure. Finally, additional related topics in the area of Big Data, such as alternative large-scale processing platforms, NoSQL data stores, and Cloud Computing execution infrastructure are presented.
3
45 hrs
---
COMP6123 
Research Methodology  

The module will teach the practical research and transferable skills applicable to applied research in computing and information technologies (IT). It provides broad coverage of issues and topics related to applied IT research, including research philosophies and methodologies, research design, research ethics, and techniques pertaining to data collection and analysis applicable in IT research. It also covers risk management and various project management skills.
3
45 hrs
---
COMP6124 
Communication Technology for Internet of Things  

This module provides a comprehensive study of the major communication technologies and emerging standards that enable applications on Internet of Things (IoT). It covers a wide range of technologies which IoT is expected to bridge in the formation of an autonomous communication network that supports smart applications and intelligent decision making. Topics include: cellular technologies (2G/3G/4G/5G) and M2M communications, covering their transmission characteristics, physical layer technologies, medium access protocols, and routing protocols; WiFi; Bluetooth; Radio Frequency Identification (RFID); Near Field Communication (NFC); Wireless Sensor Networks; Wireless Personal Area Networks including IEEE 802.15.4 and ZigBee, and the Low Power networks such as SigFox and LoRa.
3
45 hrs
---
COMP6125 
Multimedia Technology for Internet of Things  

This module aims to provide students with the advanced topics of multimedia compression and communication, and the in-depth concepts and applications of computer vision. Topics include the principles of scalable video and audio codecs, file formats and codec settings for optimizing the quality and media bandwidth, applying the codecs in developing a basic media player application that is suitable for mobile access, in-depth concepts and methods of computer vision, and the structure of the applications of computer vision.
3
45 hrs
---
COMP6126 
E-Commerce with Big Data  

Recent advances in information and communication technologies (ICTs) have led to the rapid explosion of consumer and user data. Business intelligence derived from big data can help firms to better understand market needs, develop new products and services, improve operational efficiency, and acquire competitive advantages. This module provides an overview of common big data applications and analysis techniques (e.g., market basket analysis, sentiment analysis, decision tree, clustering, etc.) in business and discusses some implementation issues related to big data projects. As part of a group project, students will need to demonstrate the ability to come up with a business plan based on a given case study and a relevant data set.
3
45 hrs
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Table II
Code
Modules
Credits
Lecture hours
Pre-requisite
COMP6101 
Machine Learning  

Artificial Intelligence (AI) is so pervasive today that possibly you are using it in one way or the other and you don’t even know about it. One of the popular applications of AI is Machine Learning (ML), which is the science of getting computers to learn without being explicitly programmed. In the past decade, machine learning has given us many amazing applications such as self-driving cars, speech recognition, image recognition, financial trading, machine translation, AlphaGo etc. This module covers some of the most important methods for machine learning including deep neural networks, reinforcement learning, etc. The aim of the module is to give students the theoretical underpinnings of machine learning techniques, and to allow them to apply such methods by practice in a range of areas such as image recognition, classification, automatic control, etc.
3
45 hrs
---
COMP6102 
Security and Authentication  

The module aims to give students an introduction to the principles, methods and applications of cryptography and authentication protocols used for network security. Security and authentication play an important part in the IoT. With sensitive information being delivered among an ever growing number of devices and parties, one wants to make sure that information will only be seen by someone with keys, and also the keys won’t be stolen or faked. Cryptography and authentication protocols are the techniques to address these issues.
3
45 hrs
---
COMP6103 
Cloud Computing  

Cloud Computing has transformed how services and applications are delivered. With the rise of virtualization technology and new programming paradigms, applications can quickly be delivered to a growing audience, without the need to physically own and configure the infrastructure. With its rapid elasticity and scalability, cloud computing has become an enabling technology for processing of big data and IoT sensor data. This module covers the main characteristics of Cloud Computing, including the enabling technologies, main software and service paradigms underpinning it, as well as related aspects, namely security, privacy, and ethical concerns.
3
45 hrs
---
COMP6104 
Digital Media and Social Networking  

The rapid spread of Online Social Networks (OSNs) and digital media has led to changes in the way users interact on the Internet, and most personal communication is now conducted through such tools. The adoption of services like Facebook, YouTube and Instagram also affect the traffic patterns on the Internet. Lately, there has been a great deal of research into the measurement and analysis of Internet user connectivity, traffic patterns and data sharing for OSNs. This module deals with the implications for the society from personal data collections. The main topics include analysis of personal data collections with data mining, current social media landscape and business models based on personal data.
3
45 hrs
---
COMP6105 
Selected Topics I  

The selected topics are designed to accommodate new, advanced and state-of-the-art technologies that are not included, but relevant, in this curriculum.
3
45 hrs
---
COMP6106 
Selected Topics II  

The selected topics are designed to accommodate new, advanced and state-of-the-art technologies that are not included, but relevant, in this curriculum.
3
45 hrs
---
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Table III
Code
Modules
Credits
Lecture hours
Pre-requisite
COMP6299 
Dissertation  

Students are required to apply the techniques and technologies which they have learned in a significant advanced research project. Under the supervision of an advisor, the students shall focus on a contemporary research topic and make use of the leading-edge techniques to investigate or produce new research findings. Upon completion, a dissertation is to be submitted and evaluated using the standard criteria for scholarly work. In addition to a written report, there will be an oral defense, where the students will be required to explain and defend the dissertation.
12
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Remark:

In order to fulfill the graduation requirement, students must complete 36 credits, including 18 credits from the compulsory modules listed in Table I, 6 credits from the optional modules in Table II, and 12 credits from the Dissertation in Table III.
 

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Master of Big Data and Internet of Things (MDATA)