AI-related papers (courses) at AUT

AUT offers a variety of papers related to AI. These can be taken as part of a degree, or as a Certificate of Proficiency.

Undergraduate papers

These papers can be studied as part of:

Artificial Intelligence

The aim of this paper is to understand the nature of intelligent systems and how such a system may be implemented.

Find out more about this paper

Data Mining and Knowledge Engineering

Introduces students to the exciting world of Data Mining. Organisations have, over time, accumulated vast amounts of valuable data that, when exploited appropriately, will give them a significant competitive advantage over their rivals who merely "crunch" data. Data Mining is an area that has come of age - well proven techniques and tools are widely available. Covers popular mining techniques as well as providing specific hands-on experience using a publicly available tool.

Find out more about this paper

Embedded Digital Systems

To create a complete embedded system from the initial design, functional and technical descriptions to the final electronic circuit, structure diagram and C code.

Find out more about this paper

Nature Inspired Computing

Provides an overview of the fundamentals of nature inspired computing (NIC), particularly in the fields of evolutionary algorithms, swarm intelligence, artificial life, DNA computing and quantum computing. Real world applications in optimisation, simulation and modeling will be introduced in workshops and recent advances presented and analysed.

Find out more about this paper

Text and Vision Intelligence

This paper covers fundamental and advanced aspects of language (especially text) and vision from an artificial intelligence perspective. The primary focus is on practical algorithms, tools and systems of text, vision intelligence, as well as their performance evaluation.

Find out more about this paper

Postgraduate papers in computer sciences

These papers can be studied as part of:

Artificial Intelligence

Critical appraisal of the key concepts underpinning artificial intelligence programs. Analysis and critique of different computational approaches in artificial intelligence (AI).

Find out more about this paper

Bioinformatics

Critically analyses computational, mathematical and information processing methods for biological data collection, storage, processing and knowledge discovery, with applications to support decision making in science, engineering, medicine, health, agriculture, horticulture, and bio-protection.

Find out more about this paper

Data Mining and Machine Learning

Studies and evaluates data mining techniques such as Decision Tree classifiers, Bayesian classifiers, Apriori techniques for discovering associations between features, clustering algorithms, and neural network technology. Critically analyses the link between traditional statistical analysis and data mining.

Find out more about this paper

Intelligent Surveillance

Emphasises practical skills and enhances students' conceptual and analytical skills in creative thinking and problem solving. Examples of successful surveillance systems and the relevant algorithms and tools will be also introduced. On completion of the paper, students will have sufficient expertise to allow them to consider undertaking a research thesis in the area.

Find out more about this paper

Nature Inspired Computing

Computing approaches inspired by nature, constructed using biological principles and modeled on natural processes allowing students to use, critically appraise and analyse the key concepts underpinning Nature Inspired Computing (NIC) techniques as applied to optimisation and search problems.

Find out more about this paper

Neuroinformatics

Introduces contemporary developments in Neuroinformatics (NI) and the techniques available to work with the vast amount of NI data. Students will apply computational modeling techniques to NI data and critique the process and results. The first interdisciplinary paper on the subject offered in Australasia, this paper will suit students and researchers from various subject areas. Students choose their assignment topics for individual or group work.

Find out more about this paper

Text Mining

Explores the issues associated with processing of knowledge represented by natural languages using a computer. Discourse will be analyzed for text structure, segmentation, cohesion/coherence and reference resolution. Text processing tasks such as document summarisation, inter-language translations, and information extraction will be examined. Also, the use of text mining for a variety of applications will be examined as case studies.

Find out more about this paper

Ubiquitous Computing

Critically analyses the convergence of technologies enabling the delivery of rich media and useful applications in a variety of formats and to a large range of devices, investigates platform and location independent access, and context-aware systems, appraises issues related to ubiquitous applications development, wireless networking infrastructure, emerging W3C standards, emerging technologies, mobile agents and auto identification and analysis.

Find out more about this paper

Postgraduate papers in engineering

These papers can be studied as part of:

Computer Vision

Provides the underlying notation, methods, and algorithms for processing and analysis of digital images and video, and how to apply these technologies in selected real-world scenarios. Subjects are presented in a concise mathematical and algorithmic form, and tutorials and assignments provide support for experimenting with the taught concepts. Considered scenarios are computational photography, stereo vision, motion analysis, image segmentation, 3D shape recon-struction, and object detection and tracking.

Find out more about this paper

Digital Signal Processing

This course introduces the fundamentals of DSP techniques and their application in engineering, focusing on discrete-time signals and linear systems in both Time and Frequency domains, Fourier analysis and Z-transform, digital filter design and implementation, echo generation and speech processing, convolution and correlation. Matlab will be used as a simulation tool for the DSP algorithms and TMS320C67xx will be used to implement the algorithms. The architecture and features of some DSP processors will be covered. Digital image processing and image compression techniques and algorithms will be discussed.

Find out more about this paper

Embedded Software Engineering

Advanced techniques for the design, development and implementation of embedded systems including: implementing an advanced operating system on an embedded computer, development of high-level hardware-orientated applications using an appropriate language, client-server embedded systems including embedded web server development, system modeling using UML, design patterns for embedded systems, and software engineering for embedded systems.

Find out more about this paper

Robotics and Automation

Introduces fundamentals of robotics with a focus on robotic manipulators found in industrial automation. It will cover basic concepts of robotics, space transformations, forward and inverse kinematics, velocity and force analysis with Jacobians, robot dynamics and control, trajectory planning, robot programming and integration of robots with other modules for industrial automation.

Find out more about this paper

PhD studies

With a qualifying postgraduate degree such as a bachelor's (honours) or master's, you can enrol in AUT's PhD programme. For this you typically choose a topic or project that interests you, contact potential supervisors, and then join a research institute. It usually takes three to four years of full-time study during which you produce a substantial amount of research that solves or explores a problem in a new way.

Doctor of Philosophy (PhD) information

Contact us

Maryam Doborjeh
Email: mgholami@aut.ac.nz

Co-founders

The co-founders of the AUT AI Initiative are:

Website search