Computer Science

COMPUTER SCIENCE (HONOURS)

The Bachelor of Advanced Studies (Honours) (Computer Scence) requires 48 credit points from this table including:
(i) 6 credit points of 4000-level Honours coursework core units, and
(ii) 18 credit points of 4000-level Honours coursework selective units, and
(iii) 24 credit points of 4000-level Honours research project units

Honours Coursework Core

INFO4990 IT Research Methods

Credit points: 6 Teacher/Coordinator: A/Prof Kalina Yacef; A/Prof Irena Koprinska Session: Semester 1,Semester 2 Classes: Tutorials, Workshops, E-learning Prerequisites: Students must satisfy Honours admission requirements. Prohibitions: INFO4444 or INFO5993 Assessment: Through semester assessment (100%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) day
Note: Department permission required for enrolment
This unit will provide an overview of the different research methods that are used in IT. Students will learn to find and evaluate research on their topic and to present their own research plan or results for evaluation by others. The unit will develop a better understanding of what research in IT is and how it differs from other projects in IT. Students will learn research ethics. This unit of study is required for students in IT who are enrolled in a research project as part of their Honours degree. It is also recommended for students enrolled or planning to do a research degree in IT and Engineering.

Honours Coursework Selective

COMP5045 Computational Geometry

Credit points: 6 Teacher/Coordinator: Dr Joachim Gudmundsson Session: Semester 1 Classes: Project Work Assumed knowledge: It is assumed that students will have experience with data structure and algorithms as covered in COMP9103 OR COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions). Assessment: Through semester assessment (72%) and Final Exam (28%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) day
In many areas of computer science- robotics, computer graphics, virtual reality, and geographic information systems are some examples- it is necessary to store, analyse, and create or manipulate spatial data. This course deals with the algorithmic aspects of these tasks: we study techniques and concepts needed for the design and analysis of geometric algorithms and data structures. Each technique and concept will be illustrated on the basis of a problem arising in one of the application areas mentioned above.
COMP5046 Natural Language Processing

Credit points: 6 Teacher/Coordinator: Soyeon Han Session: Semester 1 Classes: Lectures, Laboratory Assumed knowledge: Knowledge of an OO programming language Assessment: Through semester assessment (50%) and Final Exam (50%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) day
This unit introduces computational linguistics and the statistical techniques and algorithms used to automatically process natural languages (such as English or Chinese). It will review the core statistics and information theory, and the basic linguistics, required to understand statistical natural language processing (NLP). Statistical NLP is used in a wide range of applications, including information retrieval and extraction; question answering; machine translation; and classifying and clustering of documents. This unit will explore the key challenges of natural language to computational modelling, and the state of the art approaches to the key NLP sub-tasks, including tokenisation, morphological analysis, word sense representation, part-of-speech tagging, named entity recognition and other information extraction, text categorisation, phrase structure parsing and dependency parsing. You will implement many of these sub-tasks in labs and assignments. The unit will also investigate the annotation process that is central to creating training data for statistical NLP systems. You will annotate data as part of completing a real-world NLP task.
COMP5047 Pervasive Computing

Credit points: 6 Teacher/Coordinator: Anusha Withanghe Don Session: Semester 2 Classes: Studio class Assumed knowledge: ELEC1601 AND (COMP2129 OR COMP2017). Background in programming and operating systems that is sufficient for the student to independently learn new programming tools from standard online technical materials. Assessment: Through semester assessment (60%) and Final Exam (40%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) day
Note: Department permission required for enrolment
This is an advanced course on Pervasive Computing, with a focus on the "Internet of Things" (IoT). It introduces the key aspects of the IoT and explores these in terms of the new research towards creating user interfaces that disappear into the environment and are available pervasively, for example in homes, workplaces, cars and carried.
COMP5048 Visual Analytics

Credit points: 6 Teacher/Coordinator: Prof Seok Hong Session: Semester 1,Semester 2 Classes: Lectures, Tutorials Assumed knowledge: It is assumed that students will have experience with data structure and algorithms as covered in COMP9103 OR COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions). Assessment: Through semester assessment (60%) and Final Exam (40%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
Note: Department permission required for enrolmentin the following sessions:Semester 1
Visual Analytics aims to facilitate the data analytics process through Information Visualisation. Information Visualisation aims to make good pictures of abstract information, such as stock prices, family trees, and software design diagrams. Well designed pictures can convey this information rapidly and effectively. The challenge for Visual Analytics is to design and implement effective Visualisation methods that produce pictorial representation of complex data so that data analysts from various fields (bioinformatics, social network, software visualisation and network) can visually inspect complex data and carry out critical decision making. This unit will provide basic HCI concepts, visualisation techniques and fundamental algorithms to achieve good visualisation of abstract information. Further, it will also provide opportunities for academic research and developing new methods for Visual Analytic methods.
COMP5313 Large Scale Networks

Credit points: 6 Teacher/Coordinator: Lijun Chang Session: Semester 1 Classes: Lectures, Tutorials Assumed knowledge: It is assumed that students will have basic knowledge of computer networks as covered in INFO1112 or COMP9201 or COMP9601 (or equivalent UoS from different institutions). Assessment: Through semester assessment (60%) and Final Exam (40%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
The growing connected-ness of modern society translates into simplifying global communication and accelerating spread of news, information and epidemics. The focus of this unit is on the key concepts to address the challenges induced by the recent scale shift of complex networks. In particular, the course will present how scalable solutions exploiting graph theory, sociology and probability tackle the problems of communicating (routing, diffusing, aggregating) in dynamic and social networks.
COMP5329 Deep Learning

Credit points: 6 Teacher/Coordinator: Chang Xu Session: Semester 1 Classes: Tutorials, Lectures Assumed knowledge: COMP5318 Assessment: through semester assessment (50%), final exam (50%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
This course provides an introduction to deep machine learning, which is rapidly emerging as one of the most successful and widely applicable set of techniques across a range of applications. Students taking this course will be exposed to cutting-edge research in machine learning, starting from theories, models, and algorithms, to implementation and recent progress of deep learning. Specific topics include: classical architectures of deep neural network, optimization techniques for training deep neural networks, theoretical understanding of deep learning, and diverse applications of deep learning in computer vision.
COMP5347 Web Application Development

Credit points: 6 Teacher/Coordinator: Dr Basem Suleiman; Dr Basem Suleiman Session: Semester 1 Classes: Lectures, Laboratory, Project Work Prerequisites: INFO1103 or INFO1113 or COMP9103 or COMP9220 or COMP5028 Assumed knowledge: It is assumed that students will have experience with software development as covered in SOFT2412 or COMP9103 (or equivalent UoS from different institutions). Assessment: Through semester assessment (40%) and Final Exam (60%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) day
Nowadays most client facing enterprise applications are running on web or at least with a web interface. The design and implementation of a web application require totally different set of skills to those are required for traditional desktop applications. All web applications are of client/ server architecture. Requests sent to a web application are expected to go through the public Internet, which slows the responsiveness and increases the possible security threat. A typical web application is also expected to handle large number of requests coming from every corner of the Internet and sent by all sorts of client systems. This further complicates the design of such system.
This course aims at providing both conceptual understanding and hand-on experiences for the technologies used in building web applications. We will examine how data/messages are communicated between client and server; how to improve the responsiveness using rich client technology; as well as how to build a secure web application.
At the end of this course, students are expected to have a clear understanding of the structure and technologies of web applications. Students are also expected to have practical knowledge of some major web application environments and to be able to develop and deploy simple web applications. Cloud based platform are increasingly popular as the development and deployment platform. This course will incorporate the cloud aspect of web application development as well.
COMP5348 Enterprise Scale Software Architecture

Credit points: 6 Teacher/Coordinator: Dr Basem Suleiman Session: Semester 1 Classes: Lectures, Laboratory Assumed knowledge: It is assumed that students will have experience with software development as covered in SOFT2412 or COMP9103 and also COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions). Assessment: Through semester assessment (40%) and Final Exam (60%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
This unit covers topics on software architecture for large-scale enterprises. Computer systems for large-scale enterprises handle critical business processes, interact with computer systems of other organisations, and have to be highly reliable, available and scalable. This class of systems are built up from several application components, incorporating existing "legacy" code and data stores as well as linking these through middleware technologies, such as distributed transaction processing, remote objects, message-queuing, publish-subscribe, and clustering. The choice of middleware can decide whether the system achieves essential non- functional requirements such as performance and availability. The objective of this unit of study is to educate students for their later professional career and it covers Software Architecture topics of the ACM/IEEE Software Engineering curriculum. Objective: The objective of this unit of study is to educate students for their later professional career and it covers topics of the ACM/IEEE Software Engineering curriculum.
COMP5415 Multimedia Design and Authoring

Credit points: 6 Teacher/Coordinator: Dr Xiu Wang Session: Semester 2 Classes: Lectures, Tutorials Assumed knowledge: It is assumed that students will have experience with software development as covered in SOFT2412 or COMP9103 (or equivalent UoS from different institutions). Assessment: Through semester assessment (40%) and Final Exam (60%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
This unit provides principles and practicalities of creating interactive and effective multimedia products. It gives an overview of the complete spectrum of different media platforms and current authoring techniques used in multimedia production. Coverage includes the following key topics: enabling multimedia technologies; multimedia design issues; interactive 2D and 3D computer animation; multimedia object modelling and rendering; multimedia scripting programming; post-production and delivery of multimedia applications.
COMP5424 Information Technology in Biomedicine

Credit points: 6 Teacher/Coordinator: A/Prof Tom Cai Session: Semester 1 Classes: Lectures, Tutorials Assumed knowledge: It is assumed that students will have experience with software development as covered in SOFT2412 or COMP9103 (or equivalent UoS from different institutions). Assessment: Through semester assessment (40%) and Final Exam (60%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
Information technology (IT) has significantly contributed to the research and practice of medicine, biology and health care. The IT field is growing enormously in scope with biomedicine taking a lead role in utilising the evolving applications to its best advantage. The goal of this unit of study is to provide students with the necessary knowledge to understand the information technology in biomedicine. The major emphasis will be on the principles associated with biomedical digital imaging systems and related biomedicine data processing, analysis, visualisation, registration, modelling, retrieval and management. A broad range of practical integrated clinical applications will be also elaborated.
COMP5426 Parallel and Distributed Computing

Credit points: 6 Teacher/Coordinator: A/Prof Bing Zhou Session: Semester 1 Classes: Lectures, Tutorials Assumed knowledge: It is assumed that students will have experience with algorithms design and software development as covered in (COMP2017 or COMP9017) and COMP3027 (or equivalent UoS from different institutions). Assessment: Through semester assessment (45%) and Final Exam (55%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
This unit is intended to introduce and motivate the study of high performance computer systems. The student will be presented with the foundational concepts pertaining to the different types and classes of high performance computers. The student will be exposed to the description of the technological context of current high performance computer systems. Students will gain skills in evaluating, experimenting with, and optimising the performance of high performance computers. The unit also provides students with the ability to undertake more advanced topics and courses on high performance computing.
COMP5427 Usability Engineering

Credit points: 6 Teacher/Coordinator: Prof Judith Kay Session: Semester 2 Classes: Lectures, Laboratory Assumed knowledge: It is assumed that students will have skills with modelling as covered in ISYS2110 or ISYS2120 or COMP9110 or COMP9201 (or equivalent UoS from different institutions). Assessment: Through semester assessment (60%) and Final Exam (40%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) day
Usability engineering is the systematic process of designing and evaluating user interfaces so that they are usable. This means that people can readily learn to use them efficiently, can later remember how to use them and find it pleasant to use them. The wide use of computers in many aspects of people's lives means that usability engineering is of the utmost importance.
There is a substantial body of knowledge about how to elicit usability requirements, identify the tasks that a system needs to support, design interfaces and then evaluate them. This makes for systematic ways to go about the creation and evaluation of interfaces to be usable for the target users, where this may include people with special needs. The field is extremely dynamic with the fast emergence of new ways to interact, ranging from conventional WIMP interfaces, to touch and gesture interaction, and involving mobile, portable, embedded and desktop computers.
This unit will enable students to learn the fundamental concepts, methods and techniques of usability engineering. Students will practice these in small classroom activities. They will then draw them together to complete a major usability evaluation assignment in which they will design the usability testing process, recruit participants, conduct the evaluation study, analyse these and report the results
ISYS5050 Knowledge Management Systems

Credit points: 6 Teacher/Coordinator: Prof Joseph Davis Session: Semester 1 Classes: Lectures, Tutorials Prerequisites: COMP5206 OR ISYS2160 Assumed knowledge: It is assumed that students will have good understanding of relational data model and database technologies as covered in ISYS2120 or COMP9220 or COMP5206 (or equivalent UoS from different institutions). Assessment: Through semester assessment (100%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Normal (lecture/lab/tutorial) evening
The need to track and facilitate the sharing of the core knowledge resources in contemporary organisations is widely recognised. This course will provide a comprehensive introduction to the area of Knowledge Management (KM) from both technological and organisational perspectives. We will review and discuss a range of published papers, case studies, and other publications that deal with a range of important KM-related topics. One of the key knowledge management technologies, Business Intelligence Systems, will be covered in detail. It will also include hands-on work using the BI (Online Analytical Processing- OLAP) tool, COGNOS.
Some of the main themes to be covered will include: KM- Conceptual Foundations; Taxonomies of organizational knowledge and KM mechanisms; Case/Field Studies of KM Initiatives; Data Warehousing and OLAP/Business Analytics; Data, text, and web mining; Social media,crowdsourcing, and KM; Big data and actionable knowledge.
[[i||Additional 4000-level units to be developed for offering in 2021]]

Honours Core Research Project

COMP4103 Computer Science Honours Project A

Credit points: 6 Teacher/Coordinator: Dr Josiah Poon Session: Semester 1,Semester 2 Classes: Research Prerequisites: (COMP3027 or COMP3927) and COMP3888 and (COMP3308 or COMP3608 or COMP3419 or COMP3221 or COMP3520). Enrolment in the Bachelor of Advanced Studies Computer Science major Assessment: Through semester assessment (100%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Supervision
Note: Department permission required for enrolment
Students enrolled in the Honours programs study various advanced aspects of Computer Science. The program may include lectures, tutorials, seminars and practicals. They will undertake a research project. Assessment will include the project and may include examinations and classwork.
COMP4104 Computer Science Honours Project B

Credit points: 6 Teacher/Coordinator: Dr Josiah Poon Session: Semester 1,Semester 2 Classes: Research Prerequisites: (COMP3027 or COMP3927) and COMP3888 and (COMP3308 or COMP3608 or COMP3419 or COMP3221 or COMP3520). Enrolment in the Bachelor of Advanced Studies Computer Science major Assessment: Through semester assessment (100%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Supervision
Note: Department permission required for enrolment
Students enrolled in the Honours programs study various advanced aspects of Computer Science. The program may include lectures, tutorials, seminars and practicals. They will undertake a research project. Assessment will include the project and may include examinations and classwork.
COMP4105 Computer Science Honours Project C

Credit points: 6 Teacher/Coordinator: Dr Josiah Poon Session: Semester 1,Semester 2 Classes: Research Prerequisites: (COMP3027 or COMP3927) and COMP3888 and (COMP3308 or COMP3608 or COMP3419 or COMP3221 or COMP3520). Enrolment in the Bachelor of Advanced Studies Computer Science major Assessment: Through semester assessment (100%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Supervision
Note: Department permission required for enrolment
Students enrolled in the Honours programs study various advanced aspects of Computer Science. The program may include lectures, tutorials, seminars and practicals. They will undertake a research project. Assessment will include the project and may include examinations and classwork.
COMP4106 Computer Science Honours Project D

Credit points: 6 Teacher/Coordinator: Dr Josiah Poon Session: Semester 1,Semester 2 Classes: Research Prerequisites: (COMP3027 or COMP3927) and COMP3888 and (COMP3308 or COMP3608 or COMP3419 or COMP3221 or COMP3520). Enrolment in the Bachelor of Advanced Studies Computer Science major Assessment: Through semester assessment (100%) Campus: Camperdown/Darlington, Sydney Mode of delivery: Supervision
Note: Department permission required for enrolment
Students enrolled in the Honours programs study various advanced aspects of Computer Science. The program may include lectures, tutorials, seminars and practicals. They will undertake a research project. Assessment will include the project and may include examinations and classwork.