Courses - Faculty of Science


Computer Science

Stage I

COMPSCI 101
15 Points

Principles of Programming

An introduction to computers and computer programming in a high-level language. The role of computers and computer professionals in society is also introduced. The course is intended for students who may wish to advance in Computer Science or in Information Systems and Operations Management.

Restriction: Cannot be taken with or after COMPSCI 105, 107, 130, 210-220, 230-289, 313-399

COMPSCI 110
15 Points

Introduction to Computer Systems

An introduction to the various layers that make up a modern computer system: encoding of data and instructions, hardware, low-level programming, operating systems, applications and communications.

COMPSCI 111
15 Points

COMPSCI 111G
15 Points

An Introduction to Practical Computing

A practical introduction to computing. Topics include: web design, an overview of computer hardware and operating systems, effective use of common applications, using the internet as a communication medium, applying programming concepts, and social implications of technology.

Restriction: Cannot be taken with or after COMPSCI 110

COMPSCI 120
15 Points

Mathematics for Computer Science

Basic mathematical tools and methods needed for computer science are introduced. Elementary mathematical skills for defining, analysing and reasoning with abstract objects used in programming are developed. Topics include integers and rational numbers, strings and sets, methods of proof (including induction), algorithms and functions, and elementary introductions to graphs, trees, counting and probability.

Prerequisite: MATHS 102 or at least 13 credits in Mathematics at NCEA Level 3 or D in CIE A2 Mathematics or C in CIE AS Mathematics or 3 out of 7 in IB Mathematics

Restriction: Cannot be taken with, or after, COMPSCI 225, MATHS 254, 255

COMPSCI 130
15 Points

Introduction to Software Fundamentals

Fundamental programming techniques and processes, such as conditionals, iteration, recursion, functions, testing and debugging. Efficient ways to organise and manipulate data, including sorting and searching algorithms. Writing software that uses and implements common abstract data types such as lists, stacks, queues, dictionaries and trees.

Prerequisite: COMPSCI 101, or Achievement Standard NCEA Level 3: Digital Technologies and Programming: 91637 Develop a complex computer program for a specified task

Restriction: COMPSCI 105, 107

Stage II

COMPSCI 210
15 Points

Computer Organisation

The low level representation of data and algorithms in the computer. An introduction to computer organisation. The instruction execution model. Assembly and disassembly of instructions. Assembly language programming. How a high-level language is implemented at the machine level. The memory subsystem. Hardware support necessary to implement a secure multi-user operating system.

Prerequisite: COMPSCI 110, and 15 points from COMPSCI 105, 107, 130

COMPSCI 215
15 Points

Data Communications and Security

An introduction to data communications: the OSI reference model, particularly how the lower layers combine to implement the application layer. An introduction to secure communication and computer systems.

Prerequisite: COMPSCI 110 and PHYSICS 140 and 15 points from COMPSCI 105, 107, 130

COMPSCI 220
15 Points

Algorithms and Data Structures

An introduction to the analysis of algorithms and data structures. Common abstract data types and their implementations. Asymptotic complexity analysis. Sorting and searching algorithms. Depth-first and breadth-first search and applications. Graph optimisation problems.

Prerequisite: COMPSCI 120 and 15 points from COMPSCI 105, 107, 130

COMPSCI 225
15 Points

Discrete Structures in Mathematics and Computer Science

An introduction to the foundations of computer science, mathematics and logic. Topics include logic, principles of counting, mathematical induction, recursion, sets and functions, graphs, codes, and finite automata.

Prerequisite: 15 points from COMPSCI 120, MATHS 120, 150, 153

Restriction: MATHS 255

COMPSCI 230
15 Points

Object Oriented Software Development

The design and implementation of object-oriented programmes. Analysis and design. Modelling with UML. Design for reuse, for testing, and for ease of change. Programming with classes, objects and polymorphism.

Prerequisite: 15 points from COMPSCI 105, 107, 130

COMPSCI 235
15 Points

Software Development Methodologies

An introduction to software development, including processes, best practices, tools and quality assurance techniques such as testing.

Prerequisite: 15 points from COMPSCI 105, 107, 130

Restriction: COMPSCI 280

COMPSCI 289
15 Points

Research Seminar in Computer Science

An introduction to research topics in computer science. Students will be expected to prepare and deliver a review of research in a topic of their choice. Research articles will be provided during the course, and will consist of key scientific publications.

Prerequisite: Minimum GPA of 5.0 and COMPSCI 110, 120, 130

COMPSCI 290
15 Points

Special Topic

Stage III

COMPSCI 313
15 Points

Computer Architecture

Modern processor architectures. Principles of modern processor design; pipelining; memory hierarchies; I/O and network interfacing; compiler and OS support; embedded processors; performance; multiprocessing.

Prerequisite: COMPSCI 210, 215, PHYSICS 140

Restriction: SOFTENG 363, COMPSYS 304

COMPSCI 315
15 Points

Data Communications Technologies

The structure of data communications and networks, including the internet, covering all levels of the communications architecture. The layered protocol model, data transmission and coding, link-level and local area network protocols, wide-area internet working, routing, transport and security protocols. Basic application protocols as the foundation for distributed computing.

Prerequisite: COMPSCI 210, 215

Restriction: COMPSCI 314

COMPSCI 316
15 Points

Cyber Security

Introduces various concepts related to software, system and network security. Covers a range of topics including attacks on privacy and attack surface, static and dynamic analysis of malware, hardware security (trusted computing base, secure boot, and attestation), network security and some hot topics in cryptography including elliptic curve, blockchain and bitcoin.

Prerequisite: COMPSCI 210, 215

COMPSCI 320
15 Points

Applied Algorithmics

Fundamental design techniques used for efficient algorithmic problem-solving and software development. Methods that yield algorithms that are both provably correct and efficient. Efficiency of algorithms to provide a basis for deciding which algorithm is best for the job. Limits on the power of computers and the theory of NP-completeness. An introduction to methods whose correctness or performance is not guaranteed.

Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255

COMPSCI 331
15 Points

Large-Scale Software Development

Students will understand how to develop large-scale software systems, and learn about the issues associated with large-scale software systems and techniques for addressing them.

Prerequisite: COMPSCI 230, 235

COMPSCI 335
15 Points

Functional Programming and Distributed Services

Covers functional programming concepts, with applications to data integration from heterogeneous and asynchronous collections. Building web and cloud clients and services, with emphasis on high-level declarative and functional techniques. Dynamic web applications. Security and performance as overarching factors of web application development.

Prerequisite: COMPSCI 230 and 15 points at Stage II in Computer Science

COMPSCI 340
15 Points

Operating Systems

Operating system principles. Multi-user systems. Virtualisation. Scheduling. Concurrent processes, threads, synchronisation and deadlock. Memory allocation and virtual memory. Managing files, disks and other peripherals. Security, protection and archiving. Distributed systems and algorithms, location, migration and replication transparency. Real-time requirements. History of operating systems.

Prerequisite: COMPSCI 210, 230

Restriction: SOFTENG 370

COMPSCI 345
15 Points

Human-computer Interaction

Human behaviour and humans' expectations of computers. Computer interfaces and the interaction between humans and computers. The significance of the user interface, interface design and user centred design process in software development. Interface usability evaluation methodologies and practice. Includes a group development and evaluation project using current implementation techniques and tools.

Prerequisite: COMPSCI 230 or SOFTENG 206

Restriction: SOFTENG 350

COMPSCI 350
15 Points

Mathematical Foundations of Computer Science

The aim of this course is to present mathematical models for programming languages and computation, and derive some theorems regarding what can and cannot be computed. Abstract programming languages (finite automata, context-free grammars, Turing and register machines) are studied. Basic concepts for programming languages, limits on computational power and algorithmic complexity are presented. Church-Turing thesis and quantum computing are briefly and critically discussed.

Prerequisite: COMPSCI 220 or PHIL 222, and 15 points from COMPSCI 225, MATHS 254, 255

COMPSCI 351
15 Points

Fundamentals of Database Systems

Database principles. Relational model, Relational Algebra, Relational Calculus, SQL, SQL and Programming Languages, Entity Relationship Model, Normalisation, Query Processing and Query Optimisation, ACID Transactions, Transaction Isolation Levels, Database Recovery, Database Security, Databases and XML.

Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255

Restriction: COMPSCI 751, SOFTENG 351

COMPSCI 361
15 Points

Machine Learning

Machine learning is a branch of artificial intelligence concerned with making accurate, interpretable, computationally efficient, and robust inferences from data to solve a given problem. Understand the foundations of machine learning, and introduce practical skills to solve different problems.

Prerequisite: COMPSCI 220, and 15 points from DATASCI 100, STATS 101, 108, and 15 points from COMPSCI 225, MATHS 254, 255

Restriction: COMPSCI 762

COMPSCI 367
15 Points

Artificial Intelligence

Covers algorithms and representational schemes used in artificial intelligence. AI search techniques (e.g., heuristic search, constraint satisfaction, etc.) for solving both optimal and satisficing tasks. Tasks such as game playing (adversarial search), planning, and natural language processing. Discusses and examines the history and future of AI and the ethics surrounding the use of AI in society.

Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255

Restriction: COMPSCI 761

COMPSCI 369
15 Points

Computational Biology

Computational biology is the development and application of computer algorithms and software to address scientific questions in the biological and life sciences, often using big data. This course includes probabilistic computer modelling, computer-based statistical inference and computer simulation for, and motivated from, the life sciences. It focuses on modelling and analysing real-world biological data with an emphasis on analysing DNA sequence data.

Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255

COMPSCI 373
15 Points

Computer Graphics and Image Processing

Basic geometric processes including transformations; viewing and projection; back projection and ray tracing. Graphics modelling concepts: primitives, surfaces, and scene graphs, lighting and shading, texture mapping, and curve and surface design. Graphics and image processing fundamentals: image definition and representation, perception and colour models, grey level and colour enhancement, neighbourhood operations and filtering. Use of the OpenGL graphics pipeline.

Prerequisite: COMPSCI 210, 230

Restriction: COMPSCI 771

COMPSCI 380
15 Points

COMPSCI 380A
7.5 Points

COMPSCI 380B
7.5 Points

Project in Computer Science

Each student taking one of these courses will be expected to do an individual practical project under the supervision of a member of staff. Only students with excellent academic records will be allowed to take these courses, and only after a supervisor and topic have been agreed upon by the Head of Department.

Prerequisite: Approval of Academic Head or nominee

Restriction: COMPSCI 690

To complete this course students must enrol in COMPSCI 380 A and B, or COMPSCI 380

COMPSCI 389
15 Points

Research Methods in Computer Science

An overview of research methods and techniques used across the discipline of Computer Science, including formal proof techniques and empirical methods that involve quantitative and/or qualitative data. Students will be expected to apply the research methods in a collaborative research project.

Prerequisite: Minimum GPA of 5.0 and 45 points at Stage II in Computer Science

COMPSCI 390
15 Points

Special Topic

COMPSCI 391
15 Points

Special Topic

COMPSCI 392
15 Points

Special Topic

COMPSCI 393
15 Points

Special Topic

COMPSCI 399
15 Points

Capstone: Computer Science

Students work in small groups to complete a substantial problem applying the knowledge learnt from the different courses in the Computer Science major. Teams are expected to reason on a problem, devise a solution, produce an artefact and present their work. The capstone provides an opportunity for students to further develop their technical and communication skills.

Prerequisite: 30 points at Stage III in Computer Science and COMPSCI 210, 220, 230

Diploma Courses

COMPSCI 601
15 Points

Special Topic

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 602
15 Points

Special Topic

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 690A
15 Points

COMPSCI 690B
15 Points

Graduate Diploma Research Project

Restriction: COMPSCI 380

To complete this course students must enrol in COMPSCI 690 A and B

COMPSCI 691A
15 Points

COMPSCI 691B
15 Points

Postgraduate Diploma Research Project

Restriction: COMPSCI 780

To complete this course students must enrol in COMPSCI 691 A and B

Postgraduate 700 Level Courses

COMPSCI 701
15 Points

Special Topic: Creating Maintainable Software

Developing maintainable software has been an ongoing challenge in the software industry. This course presents the principles and practices that have been proposed for developing maintainable software systems. It will evaluate and critique these principles and practices through examining their application in practice and through understanding the research on their effectiveness.

Prerequisite: Approval of Academic Head or nominee

COMPSCI 702
15 Points

Security for Smart-devices

Covers security features supported by the different platforms for smart devices. Provides an overview of the most popular OS platforms in the market and focuses on security for Android and iOS. Recommended preparation: COMPSCI 340

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 703
15 Points

Special Topic: Generalising Artificial Intelligence

Artificial Intelligence with deep learning has seen recent substantial advances in image understanding and synthesis, NL translation, language modelling, speech recognition and synthesis, simple question answering, game playing, and other intelligence-based skills. This course examines progress towards general, learning-based, solutions to other deep, enduring Artificial Intelligence problems, including planning and reasoning, explanation, natural language understanding and generation, and knowledge acquisition, transfer and use. Recommended preparation: COMPSCI 361, 367

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 704
15 Points

Special Topic

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 705
15 Points

Advanced Topics in Human Computer Interaction

Human aspects of computer systems, relevant to commercial solution development and computer science research. Sample topics: advanced evaluation methods; support of pen and touch-based interaction; trends with domain specific user interface design, such as interfaces for enterprise systems. Recommended preparation: COMPSCI 345 or SOFTENG 350.

Prerequisite: Approval of the Academic Head or nominee

Restriction: SOFTENG 702

COMPSCI 706
15 Points

Special Topic

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 707
15 Points

Special Topic

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 709
15 Points

Directed Study

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 710
15 Points

Directed Study

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 711
15 Points

Parallel and Distributed Computing

Computer architectures and languages for exploring parallelism, conceptual models of parallelism, principles for programming in a parallel environment, different models to achieve interprocess communication, concurrency control, distributed algorithms and fault tolerance. Recommended preparation: COMPSCI 335.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 715
15 Points

Advanced Computer Graphics

An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. The precise content may vary from year to year. Consult the department for details. Recommended preparation: COMPSCI 373 or equivalent, and 15 points at Stage II in Mathematics.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 717
30 Points

Fundamentals of Algorithmics

Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: 15 points from COMPSCI 120 or equivalent and 15 points from COMPSCI 130 or equivalent

Prerequisite: Approval of Academic Head or nominee

Restriction: COMPSCI 220, 320, SOFTENG 250

COMPSCI 718
30 Points

Programming for Industry

An examination of object-oriented programming and design. Key principles of object-oriented programming: typing, encapsulation, inheritance, polymorphism and composition. Fundamental object-oriented modelling and design techniques. Students will develop application software of reasonable complexity that draws on object-oriented language features, and contemporary APIs, frameworks and tools.

COMPSCI 719
30 Points

Programming with Web Technologies

An examination of developing web-based applications. Client-side technologies: HTML, CSS and Javascript. Server-side technologies to support dynamic Web pages and data access. Fundamental relational database concepts and design techniques. Principles of Web-application design. HCI considerations and mobile clients. Students will build a Web-based application that dynamically generates content involving relational database access.

COMPSCI 720
15 Points

Advanced Design and Analysis of Algorithms

Selected advanced topics in design and analysis of algorithms, such as: combinatorial enumeration algorithms; advanced graph algorithms; analytic and probabilistic methods in the analysis of algorithms; randomised algorithms; methods for attacking NP-hard problems. Recommended preparation: COMPSCI 320 and a B- or higher in COMPSCI 220

Prerequisite: Departmental approval

COMPSCI 725
15 Points

System Security

Data security: confidentiality, integrity, availability. System security: prohibitions, permissions, obligations, exemptions. The gold standard of dynamic security: authentication, audit, authorisation. Governance: specification, implementation, assurance. Three-layer defence: prevention, detection, response. Control modalities: architectural, economic, legal, normative. System-centric analyses: attacks, threats, vulnerabilities, information flows. Owner-centric analyses: functionality, security, trust, distrust. Data-centric analyses. Security techniques: encryption, obfuscation, tamper resistance. System designs. Recommended preparation: 30 points from COMPSCI 313, 314, 320, 335, 340, 351, 702, 734, 742.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 726
15 Points

Network Defence and Countermeasures - Level 9

Focuses on the use and deployment of protective systems used in securing internal and external networks. Examines in detail the widely used protocols including SSL, IPSec, DNSSEC as well as covers infrastructure platform protocols including wireless security (IEEE 802.11). Explores current research and developments in the area of network defence and countermeasures. Recommended preparation: COMPSCI 314, 315

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 727
15 Points

Cryptographic Management

Focuses on cryptographic systems used in securing communications and data storage. Provides an overview of encryption algorithms including symmetric key cryptography, public key infrastructure, digital signatures and certificate technologies. The course covers management issues related to cryptography and explores current research and developments in this area. Recommended preparation: COMPSCI 210 or MATHS 120

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 732
15 Points

Software Tools and Techniques

An advanced course examining research issues related to tools and techniques for software design and development. Topics include: techniques for data mapping and data integration, software architectures for developing software tools, issues in advanced database systems. Recommended preparation: COMPSCI 331

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 734
15 Points

Web, Mobile and Enterprise Computing

Examines advanced and emerging software architectures at the confluence of XML, web services, distributed systems, and databases. Includes advanced topics in areas such as: mobile computing, remoting, web services for enterprise integration, workflow orchestrations for the enterprise, peer-to-peer computing, grid computing. Recommended preparation: COMPSCI 335.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 742
15 Points

Advanced Internet: Global Data Communications

The protocols and performance of local area networks. The special requirements of very high speed networks (100 Mb/s and higher). Asynchronous transfer mode (ATM) and its relation to other protocols. The TCP/IP suite. Recommended preparation: COMPSCI 314, 315.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 747
15 Points

Computing Education - Level 9

An overview of topics related to the use of technology in education and how people learn computer science concepts. Topics include research methodologies used in computer science education, how novices learn to program, and how technology can engage students in active learning, facilitate collaboration and enhance traditional educational practice. Recommended preparation: 30 points at Stage III in Computer Science

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 750
15 Points

Computational Complexity

Definitions of computational models and complexity classes: time complexity (e.g., P and NP), space complexity (e.g., L and PSPACE), circuit and parallel complexity (NC), polynomial-time hierarchy (PH), interactive complexity (IP), probabilistic complexity (BPP), and fixed-parameter complexity. Recommended preparation: COMPSCI 320 or 350.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 751
15 Points

Advanced Topics in Database Systems

Database principles. Relational model, relational algebra, relational calculus, SQL, SQL and programming languages, entity-relationship model, normalisation, query processing and query optimisation, ACID transactions, transaction isolation levels, database recovery, database security, databases and XML. Research frontiers in database systems. Recommended preparation: COMPSCI 220, 225.

Prerequisite: Approval of the Academic Head or nominee

Restriction: COMPSCI 351, SOFTENG 351

COMPSCI 752
15 Points

Big Data Management

Big data modelling and management in distributed and heterogeneous environments. Sample topics include: representation languages for data exchange and integration (XML and RDF), languages for describing the semantics of big data (DTDs, XML Schema, RDF Schema, OWL, description logics), query languages for big data (XPath, XQuery, SPARQL), data integration (Mediation via global-as-view and local-as-view), large-scale search (keyword queries, inverted index, PageRank) and distributed computing (Hadoop, MapReduce, Pig), big data and blockchain technology (SPARK, cryptocurrency). Recommended preparation: COMPSCI 351 or equivalent.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 753
15 Points

Algorithms for Massive Data

Modern enterprises and applications such as electronic commerce, social networks, location services, and scientific databases are generating data on a massive scale. Analysis of such data must be carried out by scalable algorithms. This course exposes data science practitioners and researchers to various advanced algorithms for processing and mining massive data, and explores best-practices and state-of-the-art developments in big data. Recommended preparation: COMPSCI 320

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 760
15 Points

Datamining and Machine Learning

An overview of the learning problem and the view of learning by search. Techniques for learning such as: decision tree learning, rule learning, exhaustive learning, Bayesian learning, genetic algorithms, reinforcement learning, neural networks, explanation-based learning and inductive logic programming. Experimental methods necessary for understanding machine learning research. Recommended preparation: COMPSCI 361 or 762

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 761
15 Points

Advanced Topics in Artificial Intelligence

The cornerstones of AI: representation, utilisation, and acquisition of knowledge. Taking a real world problem and representing it in a computer so that the computer can do inference. Utilising this knowledge and acquiring new knowledge is done by search which is the main technique behind planning and machine learning. Research frontiers in artificial intelligence. Recommended preparation: COMPSCI 220, 225.

Prerequisite: Approval of the Academic Head or nominee

Restriction: COMPSCI 367

COMPSCI 762
15 Points

Advanced Machine Learning

Machine learning is a branch of artificial intelligence concerned with making accurate, interpretable, computationally efficient, and robust inferences from data to solve a given problem. Students should understand the foundations of machine learning, and introduce practical skills to solve different problems. Students will explore research frontiers in machine learning. Recommended preparation: COMPSCI 220, 225 and STATS 101

Prerequisite: Approval of Academic Head or nominee

Restriction: COMPSCI 361

COMPSCI 765
15 Points

Interactive Cognitive Systems - Level 9

Many aspects of intelligence involve interacting with other agents. This suggests that a computational account of the mind should include formalisms for representing models of others' mental states, mechanisms for reasoning about them, and techniques for altering them. This course will examine the role of knowledge and search in these contexts, covering topics such as collaborative problem solving, dialogue processing, social cognition, emotion, moral cognition, and personality, as well as their application to synthetic characters and human-robot interaction.

Recommended preparation: COMPSCI 367

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 767
15 Points

Intelligent Software Agents

An introduction to the design, implementation and use of intelligent software agents (e.g., knowbots, softbots etc). Reviews standard artificial intelligence problem-solving paradigms (e.g., planning and expert systems) and knowledge representation formalisms (e.g., logic and semantic nets). Surveys agent architectures and multi-agent frameworks. Recommended preparation: COMPSCI 367.

Prerequisite: Approval of the Academic Head or nominee

COMPSCI 771
15 Points

Advanced Topics in Computer Graphics and Image Processing

Basic geometric processes including transformations; viewing and projection; back projection and ray tracing. Graphics modelling concepts: primitives, surfaces, and scene graphs, lighting and shading, texture mapping, and curve and surface design. Graphics and image processing fundamentals: image definition and representation, perception and colour models, grey level and colour enhancement, neighbourhood operations and filtering. Use of the OpenGL graphics pipeline. Research frontiers in computer graphics and image processing. Recommended preparation: COMPSCI 210, 230.

Prerequisite: Approval of the Academic Head or nominee

Restriction: COMPSCI 373

COMPSCI 773
15 Points

Intelligent Vision Systems

Computational methods and techniques for computer vision are applied to real-world problems such as 2/3D face biometrics, autonomous navigation, and vision-guided robotics based on 3D scene description. A particular feature of the course work is the emphasis on complete system design. Recommended preparation: COMPSCI 373 and 15 points at Stage II in Mathematics.

Prerequisite: Approval of Academic Head or nominee

COMPSCI 775
15 Points

Advanced Multimedia Imaging

Camera calibration, image sequence analysis, computer vision, 3D visualisation, ground truth for image sequence analysis, performance evaluation (noise, accuracy). Applications in vision-based driver assistance, panoramic or 3D visualisation using recorded images, or image and video retrieval. Recommended preparation: COMPSCI 373 and MATHS 208 or 250.

Prerequisite: Approval of Academic Head or nominee

COMPSCI 777
15 Points

Computer Games Technology

An advanced course looking at some of the computer graphics and artificial intelligence technology involved in computer games. Typical topics are: an introduction to the gaming industry; commercial modelling and animation software; maximising graphics performance, including such techniques as visibility preprocessing, multiple levels of detail, space subdivision, fast collision detection, direct programming of the graphics card; AI for computer games, including decision trees, rule-based systems, path planning, flocking behaviours, intelligent agents; research issues, such as physically-based modelling, terrain generation, computer learning. Recommended preparation: COMPSCI 367, 373.

Prerequisite: Approval of Academic Head or nominee

COMPSCI 778
60 Points

Internship - Level 9

Enables the development of practical knowledge and hands-on experience through a supervised internship in the IT industry. Students complete a research-informed project, and present both written and oral reports of their findings.

COMPSCI 780
15 Points

COMPSCI 780A
7.5 Points

COMPSCI 780B
7.5 Points

Postgraduate Project in Computer Science 1

Prerequisite: Approval of Academic Head or nominee

Restriction: COMPSCI 691

To complete this course students must enrol in COMPSCI 780 A and B, or COMPSCI 780

COMPSCI 789A
15 Points

COMPSCI 789B
15 Points

COMPSCI 789U
2.5 Points

Honours Research Project - Level 9

Prerequisite: Approval of Academic Head or nominee

To complete this course students must enrol in COMPSCI 789 A and B

COMPSCI 791
30 Points

COMPSCI 791A
15 Points

COMPSCI 791B
15 Points

Research Project - Level 9

To complete this course students must enrol in COMPSCI 791 A and B, or COMPSCI 791

COMPSCI 796A
60 Points

COMPSCI 796B
60 Points

MSc Thesis in Computer Science - Level 9

To complete this course students must enrol in COMPSCI 796 A and B

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