Artificial Intelligence Subject regulations
Artificial intelligence (AI) is the combination of data, algorithms and computing power that can perform tasks that would require intelligence if they were done by a human. It is impacting our lives, businesses and environment. As a subject AI will give students advanced skills and techniques to address the problems at hand.
Other qualifications
Prescriptions for:
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GradCert(AI) and GradDip(AI) A Graduate Certificate and [Graduate Diploma](https://calendar.waikato.ac.nz/regulations/diplomas/graddip are available to graduates who have not included Artificial Intelligence at an advanced level in their first degree.
For further details, contact the Division of Health, Engineering, Computing and Science Office.
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PGCert(AI), PGDip(AI), BSc(Hons), MSc [1], MAI and MSc(Research) To complete a PGCert(AI), students must complete 60 points at 500 level consisting of 60 points from papers listed for Artificial Intelligence.
To complete a PGDip(AI), students must complete 120 points at 500 level including at least 90 points from papers listed for Artificial Intelligence.
Enrolment in papers towards the BSc(Hons) is only by invitation of the Head of School. To complete a BSc(Hons) in Artificial Intelligence, students must complete 120 points at 500 level, including at least 90 points from the 500-level papers listed for Artificial Intelligence, of which at least 30 points must be in research (normally AIMLX591).
To complete an MSc in Artificial Intelligence, students admitted under section 2(a) of the MSc regulations must complete 180 points at 500 level including AIMLX592, and at least another 60 points from the 500-level papers listed for Artificial Intelligence.
The qualification regulations define the requirements for the Master of Artificial Intelligence.
To complete an MSc (Research) in Artificial Intelligence, students admitted under section 2(a) of the MSc (Research) regulations must complete 180 points at 500 level consisting of AIMLX594, and 60 points from the 500-level papers listed for Artificial Intelligence.
[1] The MSc in Artificial Intelligence will not be offered in 2025.
Artificial Intelligence papers
| Code and paper title | Points | |
|---|---|---|
COMPX216
Artificial Intelligence
This paper provides an introduction to artificial intelligence, including techniques for knowledge representation and reasoning, searching and... |
15 | 25A (Hamilton) & 25A (Tauranga) & 25X (Hainan University, Haikou China) |
|
DATAX221
Statistical Data Analysis
This paper introduces students to the R programming language. Analysis of variance, multiple regression, non parametric methods and time series are... |
15 | 25A (Hamilton) |
| Code and paper title | Points | |
|---|---|---|
|
COMPX301
Design and Analysis of Algorithms
This course is for students interested in the art and science of computer programming. It is concerned with advanced data structures and their... |
15 | 25A (Hamilton) |
|
COMPX307
Principles of Programming Languages
The design, implementation and use of programming languages, in particular the use of functional languages to implement imperative languages will be... |
15 | 25B (Hamilton) |
|
COMPX310
Machine Learning
This paper introduces Machine Learning (ML) which is the science of making predictions. ML algorithms strive to be fast and highly accurate, while... |
15 | 25B (Hamilton) |
|
COMPX326
Computer Vision
This paper provides an introduction to modern computer vision techniques based on deep learning methods. |
15 | 25A (Hamilton) |
|
COMPX328
Natural Language Processing
This paper provides an introduction to modern natural language processing techniques based on deep learning methods. |
15 | 25A (Hamilton) |
|
COMPX361
Logic and Computation
The syllabus includes: further development of predicate logic with application to program verification; mathematical induction including structural... |
15 | 25B (Hamilton) & 25B (Tauranga) & 25X (Hainan University, Haikou China) |
|
COMPX367
Computational Mathematics
Introduces numerical methods for solving various mathematical problems. |
15 | 25B (Hamilton) |
|
CSMAX300
Visual Data Communication
This paper focuses on the skills and knowledge for communicating with data. A variety of methods of communicating and presenting data will be covered. |
15 | 25A (Hamilton) |
|
DATAX321
Advanced Data Analysis
This paper uses R for data analysis and modelling. The topics covered are general linear models, generalised linear models, and statistical learning... |
15 | 25B (Hamilton) |
|
DATAX322
Probability and Stochastic Processes
This paper introduces students to probability theory and stochastic processes. It covers formally the theoretical foundations of probability, random... |
15 | 25A (Hamilton) |
| Code and paper title | Points | |
|---|---|---|
|
AIMLX591
Artificial Intelligence Dissertation
A report on findings of a theoretical or empirical investigation. |
30 | 25X (Hamilton) |
|
AIMLX592
Artificial Intelligence Dissertation
A report on the findings of a theoretical or empirical investigation. |
60 | 25X (Hamilton) |
|
AIMLX594
Artificial Intelligence Thesis
An externally examined piece of written work that reports on the findings of supervised research. |
120 | 25X (Hamilton) |
|
BIOMD501
Technology in Biomedicine: From Drug Discovery and Development to Precision Medicine
In this paper, students will gain an understanding of how technology, including artificial intelligence, is used in disease diagnosis, drug... |
15 | 25B (Hamilton) |
|
COMPX520
Dissertation
A directed study investigation and report on an approved project or study topic under the supervision of a lecturer. Students should obtain the... |
45 | 25D (Hamilton) & 25I (Hamilton) & 25X (Hamilton) |
|
COMPX521
Machine Learning Algorithms
This paper exposes students to selected machine learning algorithms and includes assignments that require the implementation of these algorithms. |
15 | 25B (Hamilton) |
|
COMPX523
Machine Learning for Data Streams
Data streams are everywhere, from F1 racing over electricity networks to news feeds. Data stream mining relies on and develops new incremental... |
15 | 25A (Hamilton) |
|
COMPX525
Deep Learning
This paper provides an introduction into Deep Learning, focussing on both algorithms and applications. It covers both the basics of Neural networks... |
15 | 25A (Hamilton) |
|
COMPX546
Graph Theory
An introduction to graph theory and combinatorics, including network optimisation algorithms. |
15 | 25A (Hamilton) |
|
COMPX567
Advanced Computational Mathematics
This paper considers computational methods for solving various mathematical problems. |
15 | 25B (Hamilton) |
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COMPX216 Artificial Intelligence
This paper provides an introduction to artificial intelligence, including techniques for knowledge representation and reasoning, searching and...
Points 15This paper introduces students to the R programming language. Analysis of variance, multiple regression, non parametric methods and time series are...
Points 15 -
COMPX301 Design and Analysis of Algorithms
This course is for students interested in the art and science of computer programming. It is concerned with advanced data structures and their...
Points 15The design, implementation and use of programming languages, in particular the use of functional languages to implement imperative languages will be...
Points 15This paper introduces Machine Learning (ML) which is the science of making predictions. ML algorithms strive to be fast and highly accurate, while...
Points 15This paper provides an introduction to modern computer vision techniques based on deep learning methods.
Points 15This paper provides an introduction to modern natural language processing techniques based on deep learning methods.
Points 15The syllabus includes: further development of predicate logic with application to program verification; mathematical induction including structural...
Points 15Introduces numerical methods for solving various mathematical problems.
Points 15This paper focuses on the skills and knowledge for communicating with data. A variety of methods of communicating and presenting data will be covered.
Points 15This paper uses R for data analysis and modelling. The topics covered are general linear models, generalised linear models, and statistical learning...
Points 15This paper introduces students to probability theory and stochastic processes. It covers formally the theoretical foundations of probability, random...
Points 15 -
AIMLX591 Artificial Intelligence Dissertation
A report on findings of a theoretical or empirical investigation.
Points 30A report on the findings of a theoretical or empirical investigation.
Points 60An externally examined piece of written work that reports on the findings of supervised research.
Points 120In this paper, students will gain an understanding of how technology, including artificial intelligence, is used in disease diagnosis, drug...
Points 15A directed study investigation and report on an approved project or study topic under the supervision of a lecturer. Students should obtain the...
Points 45This paper exposes students to selected machine learning algorithms and includes assignments that require the implementation of these algorithms.
Points 15Data streams are everywhere, from F1 racing over electricity networks to news feeds. Data stream mining relies on and develops new incremental...
Points 15This paper provides an introduction into Deep Learning, focussing on both algorithms and applications. It covers both the basics of Neural networks...
Points 15An introduction to graph theory and combinatorics, including network optimisation algorithms.
Points 15This paper considers computational methods for solving various mathematical problems.
Points 15
2025 Catalogue of Papers information current as of 5 Nov 2024 01:00am