Department of Computer Science


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Postgraduate Courses

COMPSCI 601/602   Special Topic Diploma Courses   SS, S1, S2  
COMPSCI 691 A and B Postgraduate Diploma Dissertation S1, S2  
COMPSCI 702 Security for Smart‐devices  S1 
COMPSCI 705 Advanced Topics in Human Computer Interaction S2  
COMPSCI 711   Parallel and Distributed Computing  S2
COMPSCI 715   Advanced Computer Graphics  S2
COMPSCI 720 Advanced Design and Analysis of Algorithms S1
COMPSCI 725 System Security  S2
COMPSCI 726 Network Defence and Countermeasures  S2
COMPSCI 727 Cryptographic Management S1
COMPSCI 732 Software Tools and Techniques S1
COMPSCI 734 Web, Mobile and Enterprise Computing  S1
COMPSCI 742 Advanced Internet: Global Data Communications  S2
COMPSCI 747 Computing Education  S1
COMPSCI 750 Computational Complexity  S2
COMPSCI 751 Advanced Topics in Database Systems S1
COMPSCI 752 Web Data Management  S1
COMPSCI 753 Uncertainty in Data  S2
COMPSCI 760 Datamining and Machine Learning  S2
COMPSCI 761 Advanced Topics in Artificial Intelligence  S2
COMPSCI 765 Interactive Cognitive Systems  S1
COMPSCI 767 Intelligent Software Agents  S1
COMPSCI 771 Advanced Topics in Computer Graphics and Image Processing  S1
COMPSCI 773 Intelligent Vision Systems  S1
COMPSCI 780 Postgraduate Project in Computer Science  SS, S1, S2
COMPSCI 789 A and B BSc (Hons) Dissertation  S1, S2
COMPSCI 796 A and B MSc Thesis in Computer Science  S1, S2
COMPSCI 799 A and B Part‐time MSc Thesis in Computer Science  S1, S2
BIONF702 Comparative Bioinformatics S1
BIONF703 Genome Bioinformatics and Systems Biology S2


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COMPSCI 601/602
Special Topic Diploma Courses
Prerequisite: Departmental approval. Please contact the Diploma Coordinator before enrolment at diplomas@cs.auckland.ac.nz
These courses are offered to Postgraduate Diploma students to supplement their knowledge of Computer Science concepts introduced at Stage III. Students are required to attend lectures and complete the course work for a Stage III COMPSCI course. They are additionally required to produce a substantial report in a topic proposed by the course coordinator of the Stage III course. It is important to note that students must pass the report component, as well as the Stage III exam and coursework, to pass the course as a whole.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: link

 


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COMPSCI 691 A and B
Postgraduate Diploma Dissertation
Prerequisite: Departmental approval. Please contact the Diploma Coordinator before enrolment at diplomas@cs.auckland.ac.nz
Restriction: COMPSCI 780
This is a two‐semester course for Postgraduate Diploma students only. Students must enrol in COMPSCI 691A and 691B. This 30‐point dissertation is an introduction to individual research and study within a specialised field of Computer Science. You will work closely with an academic member of staff, but your study will be self‐directed.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: link

 


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COMPSCI 702
Security for Smart‐devices
Recommended preparation: COMPSCI 340
This course covers security features supported by the different platforms for smart devices (e.g., smartphones and tablets). It provides an overview of the most popular OS platforms in the market. The course focuses on state‐of‐the‐art in security for Android and iOS. The second part of the course consists of students giving seminars based on research articles. The course also has a practical component, where students get self‐organised in teams and operate as a startup to deliver a software artefact.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 705
Advanced Topics in Human Computer Interaction
Preparation: COMPSCI 345 or SOFTENG 350
Restriction: SOFTENG 702
Careful consideration of the human aspects of computer systems is a major part of both commercial solution development and computer science research. This course investigates current topics in HCI research. Examples are: support of pen‐based interaction on a range of devices such as digital whiteboards, tablet PCs and PDAs; technical infrastructure for pen‐based interaction; trends with domain specific user interface design such as interfaces for enterprise systems. Each student will do one project and one research seminar.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 711
Parallel and Distributed Computing
Recommended preparation: Students are expected to have completed at least three Stage III COMPSCI courses. Those who have not done COMPSCI 335 are expected to self‐study C# and the Web service materials covered in COMPSCI 335.
Advances in hardware architecture make parallel computing possible on PCs. This course focuses on programming models, algorithms and techniques for developing distributed applications and systems. The topics include, parallel programming models, minimal spanning tree, Byzantine agreement, the CAP theorem, logical time, multicast, mutex, garbage collection, snapshot, deadlock detection, web caching, resource looking up in p2p system, and cloud computing, etc.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 715
Advanced Computer Graphics
Recommended preparation: COMPSCI 373, or equivalent, and 15 points at Stage II Mathematics
An advanced course looking at the latest computer graphics technologies and their use in research and commercial applications. Typical topics are games (e.g. for health, rehabilitation, education), novel modelling and animation techniques, advanced user interfaces (sketch based interfaces, Augmented and Virtual Reality), advanced OpenGL (advanced shading, rendering, texturing, shadows) and GPU accelerated algorithms.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 720
Advanced Design and Analysis of Algorithms
Recommended preparation: COMPSCI 320
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; randomized algorithms; methods for attacking NP‐hard problems; algorithms for collective decision making.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 725
System Security
Recommended preparation: Two of the following courses: COMPSCI 313, 314, 320, 335, 340, 351,734, 742
Computer security is increasingly important, now that e‐commerce is commonplace and e‐ government is starting to come online. Computer systems are susceptible to a variety of attacks including denial of service, unauthorised modifications, and unauthorised use. In this paper, we will briefly survey the field of computer security, then we will study some technical articles from the recent literature on specific topics in computer security.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 726
Network Defence and Countermeasures
Recommended preparation: COMPSCI 314 or equivalent
This course focuses on the use and deployment of protective systems used in securing internal and external networks. Its purpose is to provide a detailed understanding of technologies such as firewalls, NAT, IDS, honeypot and a host of other security mechanisms for providing security at different TCP/IP layers. It examines in detail the widely used protocols including SSL, IPSec, DNSSEC as well as covers infrastructure platform protocols including wireless security (IEEE 802.11). This course also explores the current research and developments in the area of network defence and countermeasures.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 727
Cryptographic Management
Prerequisite: Approval of the Head of Department of Computer Science
Focuses on the use and deployment of cryptographic systems used in securing communications and data storage. Provides an overview of encryption algorithms and the technologies and systems that support them including symmetric key cryptography, public key infrastructure, digital signatures and certificate technologies. As a part of this overview, this course will concentrate on the management issues of algorithm selection; encryption key generation, distribution, and revocation; and strategies for overcoming encryption security vulnerabilities and their associated breaches. The course also discusses best-practices and compliance with national and international standards and explores the current research and developments in this area.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 732
Software Tools and Techniques
Recommended preparation: COMPSCI 335
An advanced course examining research issues related to tools and techniques for software design and development. Typical topics could include advanced software development methodologies, software architectures for developing software tools, collaborative work and software engineering, open source vs closed source development, issues in advanced database systems.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 734
Web, Mobile and Enterprise Computing
Recommended preparation: COMPSCI 335
This course looks at emerging mobile and distributed software architectures at the confluence of Web services, XML and databases. The course includes advanced topics in areas such as: mobile computing, Web architectures and performance, Web services routing and security, imperative/declarative/functional integration, XML/SQL/objects integration, services/messaging/objects interface integration, workflow orchestrations, and other techniques for enterprise distributed systems.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 742
Advanced Internet: Global Data Communications
Recommended preparation: COMPSCI 314
This is a research‐oriented course, covering selected topics relating to data communication, including but not limited to the internet, radio networks, high speed networks, and local loop technologies as well as their underlying physical layer and coding. Students are expected to learn how to present a good technical argument on these issues.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 747
Computing Education
Recommended preparation: 
This course focuses on how students learn computing concepts, and how computers are used in the wider education field. We survey the field of Computer Science Education, including issues involving curriculum design and delivery, differences between programming languages and environments, and how novices learn to program. We also discuss different instructional technologies such as educational games, mobile learning and software tools that support collaboration.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 750
Computational Complexity
Recommended preparation: COMPSCI 320 or COMPSCI 350
This is a survey course of the popular computational complexity classes and measures including and beyond P and NP. 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), alternating machines, and fixed parameter complexity.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 751
Advanced Topics in Database Systems
Preparation: COMPSCI 220 and 225
Restriction: COMPSCI 351, SOFTENG 351
This course builds on and explores the topics covered in COMPSCI 351. Students are required to attend lectures and complete the coursework for COMPSCI 351. They are additionally required to produce a substantial report in a topic proposed by the course coordinator.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 752
Web Data Management
Preparation: COMPSCI 351 or equivalent
Internet and the Web have revolutionized access to information. Today, one finds primarily on the Web, HTML (the standard for the Web) but also documents in pdf, doc, plain text as well as images, music and videos. The public Web is composed of billions of pages on millions of servers. It is a fantastic means of sharing information. It is very simple to use for humans. On the negative side, it is very inappropriate for access by software applications. This motivated the introduction of new data models, namely XML and RDF that are well suited both for humans and machines. The course aims to describe the structure of information found on the Web, and to explain how this information can be efficiently represented, described and accessed. Primary topics of the course include Web data modelling and large‐scale data management in distributed and heterogeneous environments. Topics include: Extensible Markup Language (XML), XPath, XQuery, XUpdate, XSLT, Tree automata, RDF, RDFS, Ontologies, OWL, SPARQL, Data Integration, Web Search, Data distribution, Distributed computing, Hadoop, MapReduce, Pig.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered

 


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COMPSCI 753
Uncertainty in Data
Preparation: COMPSCI 351 or equivalent
Modern applications generate large volumes of uncertain data. This course investigates approaches to modelling, managing and processing uncertain data. It covers how to design databases in the presence of uncertainty, and discusses the state‐of‐the‐art in querying techniques for databases where data values or records are uncertain. Principled methods are investigated that improve the quality of data in databases.
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 760
Datamining and Machine Learning
Recommended preparation: COMPSCI 367  
Machine learning techniques are widely used in many computing applications; for example, in  web search engines, spam filtering, speech and image recognition, computer games, machine  vision, credit card fraud detection, stock market analysis and product marketing applications.  Machine learning implies that there is some improvement that results from the learning program  having seen some data. The improvement can be in terms of some performance program (e.g.,  learning an expert system or improving the performance of a planning or scheduling program), in  terms of finding an unknown relation in the data (e.g., data mining, pattern analysis), or in terms  of customizing adaptive systems (e.g., adaptive user‐interfaces or adaptive agents).  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 761
Advanced Topics in Artificial Intelligence
Recommended preparation: COMPSCI 220 and 225 
Restriction: COMPSCI 365, 366, 367
This course builds on and explores the topics covered in COMPSCI 367. Students are required to  attend lectures and complete the coursework for COMPSCI 367. They are additionally required to  produce a substantial report in a topic proposed by the course coordinator.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link

 


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COMPSCI 765
Interactive Cognitive Systems
Recommended preparation: COMPSCI 367
Many aspects of intelligence involve interacting with other agents. The computationalist approach  to AI accordingly includes formalisms for representing models of others' mental states,  mechanisms for reasoning about these formalisms, and techniques for altering them. This course  examines the role of knowledge and search in these contexts, covering topics such as  collaborative problem solving; interactive dialogue; social, emotional and moral cognition; and  personality. We look at a range of applications including personal assistants, human‐robot  interaction, training and education systems, and teams of autonomous robots. The strengths and  weaknesses of this approach are brought to light via comparison to other modern approaches in  AI that emphasize the dynamical, embodied and situated nature of natural intelligence.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered


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COMPSCI 767
Intelligent Software Agents
Recommended preparation: COMPSCI 367
One of the core abilities of an intelligent software agent is to be able to solve problems and to  plan how to achieve goals. Search is a general purpose technique for finding solutions to  problems. However, these search spaces may be quite large and planning is one technique for  exploiting domain‐specific knowledge to reduce the size of the space to be searched. Problems  may include dealing with other agents who might be adversaries, or reasoning about scarce  resources.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered


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COMPSCI 767
Intelligent Software Agents
Recommended preparation: COMPSCI 367
One of the core abilities of an intelligent software agent is to be able to solve problems and to  plan how to achieve goals. Search is a general purpose technique for finding solutions to  problems. However, these search spaces may be quite large and planning is one technique for  exploiting domain‐specific knowledge to reduce the size of the space to be searched. Problems  may include dealing with other agents who might be adversaries, or reasoning about scarce  resources.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered


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COMPSCI 771
Advanced Topics in Computer Graphics and Image Processing
Recommended preparation: COMPSCI 210 and 230  
Restriction: COMPSCI 372, 373, 375
This course builds on and explores the topics covered in COMPSCI 373. Students are required to  attend lectures and complete the coursework for COMPSCI 373. They are additionally required to  produce a substantial report in a topic proposed by the course coordinator.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered


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COMPSCI 773
Intelligent Vision Systems
Recommended preparation: COMPSCI 373 and 15 points at Stage II Mathematics Students should have active knowledge of C/C++/C# programming.  
This course introduces computational methods and techniques for computer vision, extended  towards real‐world problems such as 2/3D face biometrics, 2/3D hand tracking, 2/3D hand signs  recognition, and vision‐guided robotics based on 3D scene description. The students will interact  with 3D vision equipments based in the city campus 3D vision lab. A particular feature of the  course work is the emphasis on complete system design.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered


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COMPSCI 780 
Postgraduate Project in Computer Science
Prerequisites: Departmental approval required. See the Project Coordinator before enrolment.
This 15‐point project is supervised, independent research or development work on a topic related  to Computer Science.  
Details about the course can be found through the links below:


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COMPSCI 789 A and B
BSc (Hons) Dissertation
Prerequisite: Departmental approval required. Contact the Honours Coordinator before enrolment.
All students completing a Bachelor of Science (Honours) in Computer Science are expected to  complete this 30‐point dissertation. Students are expected to find a staff member to supervise the  dissertation and will work closely with them on the agreed topic. The form of study undertaken  will vary widely, depending upon the chosen topic.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: link


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COMPSCI 791 A and B
MProfStuds Dissertation
Prerequisites: Departmental approval required. 
This is a compulsory 30‐point dissertation course that is offered to Master of Professional Studies  students only. You will be enrolled in COMPSCI 791A and COMPSCI 791B in consecutive  semesters. This research opportunity will introduce you to self‐directed study in a specialised field  of Computer Science. You will work closely with an academic member of staff, and develop your  skills and knowledge in the agreed topic area. The form of study undertaken will vary widely,  depending upon your chosen topic, which may require careful theoretical investigation or a large  implementation.  
Details about the course can be found through the links below:
  • Summer: not offered
  • Semester 1: link
  • Semester 2: link


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COMPSCI 796 A and B
MSc Thesis in Computer Science  
Required: Departmental approval essential. Contact the Masters Coordinator before enrolment.
This course is a full‐time 120‐point course lasting two semesters. To complete this course,  students must enrol in both COMPSCI 796A and B.  
Details about the course can be found through the links below:


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COMPSCI 799 A and B
Part‐time MSc Thesis in Computer Science  
Required: Departmental approval essential. Contact the Masters Coordinator before enrolment.  
This course is a part‐time 120‐point course lasting four semesters. To complete this course,  students must enrol in both COMPSCI 799 A and B twice.  
Details about the course can be found through the links below:


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BIOINF 702
Comparative Bioinformatics
Required:  Entry by permission, COMPSCI 369 or similar recommended. 
This is a challenging and broad-ranging course which sets out to give a foundation in many different areas of modern bioinformatics. It will build on your previous knowledge of computer science, biology and the basics of bioinformatics. Half the course is dedicated to modern approaches to phylogenetics. In this half you will cover the basics of homology and sequence alignment, models for trees and sequence mutation, and statistical methods and software for phylogenetic reconstruction. The second half of the course focuses on structural bioinformatics including alignment, prediction and comparison of protein structure. 

Details about the course can be found through the links below:

  • Summer: not offered
  • Semester 1: link
  • Semester 2: not offered


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BIOINF 703
Genome Bioinformatics and Systems Biology
Required:  Entry by permission, BIOINF 701 or similar recommended. 
Advances in genetic sequencing technologies are rapidly changing our ability to determine the genome sequence and to explore the gene expression profiles of organisms. Relevant computational methods, including graph theory, string comparison and pattern matching will be discussed, along with their application to genome assembly, metagenomics, gene-gene interaction and systems biology.

Details about the course can be found through the links below:

  • Summer: not offered
  • Semester 1: not offered
  • Semester 2: link


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