Master of Mathematical Sciences specialising in Artificial Intelligence

Postgraduate

Degree hero banner

Mode

On campus

Campus

Adelaide City Campus

Duration

2 year(s) full-time

Program code

MAMTH

Study as

Full time or part time

Indicative annual fees

$41,500

Non-tuition fees

SATAC code

ACM172

Prerequisite

None

Assumed knowledge

First year university mathematics.

Entry requirements

Admission criteria

To be eligible, an applicant must have achieved at least one of the following minimum entry requirements and demonstrate they fulfil any prerequisite and essential criteria for admission. In cases where there are more eligible applicants than available places, admission will be competitive with ranks based on the entry criteria.

A completed bachelor (AQF level 7) or bachelor honours (AQF level 8) degree or equivalent from a recognised higher education institution; OR
A completed nested or related graduate certificate (AQF level 8) or higher or equivalent from a recognised higher education institution.

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Note:

Please note that entry requirements for this degree are provisional and subject to change.

Degree Structure: Master of Mathematical Sciences specialising in Artificial Intelligence

Program code: MAMTH

Complete 96 units comprising:

6 units for all Core courses, and
42 units for one Specialisation from Specialisation, and
24 units for all Work integrated learning, and
30 to 60 units for Electives

Study plan

A study plan sets out the courses you will need to complete and the recommended timing for each one. This will help to guide your enrolment in each study period, alongside any additional information provided below. If you have received a personalised plan or alternative advice from your Program Director, please refer to that guidance in the first instance, or seek help from your Program Director or Student Assist if you are unsure.

Choose your course type

Year 1

Semester 1

Units 6

MATHX203 | Multivariable Calculus (6 units)

Course type

¹ Core courses

Units 6

MATHX201 | Algebra (6 units)

Course type

¹ Specialisation - ARTIMAMTH - Artificial Intelligence - Specialisation courses

Units 6

MATHX205 | Optimisation (6 units)

Course type

¹ Specialisation - ARTIMAMTH - Artificial Intelligence - Specialisation courses

Units 6

STATX200 | Probability (6 units)

Course type

¹ Specialisation - ARTIMAMTH - Artificial Intelligence - Specialisation courses

Semester 2

COMP5064|Programming for Artificial Intelligence and Machine Learning 2 (6 units)

Units 6

MATHX302 | Advanced Optimisation (6 units)

Course type

¹ Specialisation - ARTIMAMTH - Artificial Intelligence - Specialisation courses

Units 6

MATHX405 | Mathematics of Artificial Intelligence (6 units)

Course type

¹ Specialisation - ARTIMAMTH - Artificial Intelligence - Specialisation courses

Units 6

STATX303 | Stochastic Processes (6 units)

Course type

¹ Specialisation - ARTIMAMTH - Artificial Intelligence - Specialisation courses

Year 2

Semester 1

Units 6

ARTI1000|Mathematical Generative Artificial Intelligence (6 units)

or

MATH6009|Deep Geometry (6 units)¹ Course type: Program electives

or

MATH6012|Deep Signal Processing (6 units)¹ Course type: Program electives

or

MATH6019|Reinforcement Learning (6 units)¹ Course type: Program electives

Course type

¹ Program electives

Units 6

ARTI1000|Mathematical Generative Artificial Intelligence (6 units)

or

MATH6009|Deep Geometry (6 units)¹ Course type: Program electives

or

MATH6012|Deep Signal Processing (6 units)¹ Course type: Program electives

or

MATH6019|Reinforcement Learning (6 units)¹ Course type: Program electives

Course type

¹ Program electives

Units 12

MATHX406 | Mathematics Research Project 1 (12 units)

Course type

¹ Work integrated learning

Semester 2

Units 6

ARTI1000|Mathematical Generative Artificial Intelligence (6 units)

or

MATH6009|Deep Geometry (6 units)¹ Course type: Program electives

or

MATH6012|Deep Signal Processing (6 units)¹ Course type: Program electives

or

MATH6019|Reinforcement Learning (6 units)¹ Course type: Program electives

Course type

¹ Program electives

Units 6

ARTI1000|Mathematical Generative Artificial Intelligence (6 units)

or

MATH6009|Deep Geometry (6 units)¹ Course type: Program electives

or

MATH6012|Deep Signal Processing (6 units)¹ Course type: Program electives

or

MATH6019|Reinforcement Learning (6 units)¹ Course type: Program electives

Course type

¹ Program electives

Units 12

MATHX407 | Mathematics Research Project 2 (12 units)

Course type

¹ Work integrated learning

Enrolment information

Find details about the rules and notes that apply to your program, along with other essential information required for successful enrolment. Supplementary supporting resources may also be provided where applicable.

Some programs include additional enrolment advice. If available for your program, it will be displayed here.

Courses

Listed here are all the courses that contribute to your program, including elective options that can be chosen. These courses come together to form your study plan. Courses fall into different categories, each of which have specific unit values that need to be met under the program rules.

What courses you'll study

Complete 96 units comprising:

6 units for all Core courses, and
42 units for one Specialisation from Specialisation, and
24 units for all Work integrated learning, and
30 to 60 units for Electives

Complete 6 units for ALL of the following:

Course name		Course code	Units
	Course name Multivariable Calculus	Course code MATHX203	Units 6

Complete 42 units for ALL of the following:

Course name		Course code	Units
	Course name Advanced Optimisation	Course code MATHX302	Units 6
	Course name Mathematics of Artificial Intelligence	Course code MATHX405	Units 6
	Course name Optimisation	Course code MATHX205	Units 6
	Course name Probability	Course code STATX200	Units 6
	Course name Stochastic Processes	Course code STATX303	Units 6
	Course name Programming for Artificial Intelligence and Machine Learning 2	Course code COMP5064	Units 6
	Course name Algebra	Course code MATHX201	Units 6

Work Integrated Learning description

WIL courses give you real‑world experience as part of your degree.

Complete 24 units for ALL of the following:

Course name		Course code	Units
	Course name Mathematics Research Project 1	Course code MATHX406	Units 12
	Course name Mathematics Research Project 2	Course code MATHX407	Units 12

Electives description

A flexible course choice within your degree.

Complete 30 to 60 units comprising:

30 to 60 units from Program electives

Course name		Course code	Units
	Course name Cryptography	Course code MATH3022	Units 6
	Course name Mathematical Modelling	Course code MATH5018	Units 6
	Course name Deep Geometry	Course code MATH6009	Units 6
	Course name Deep Signal Processing	Course code MATH6012	Units 6
	Course name Algebraic Topology	Course code MATH6015	Units 6
	Course name Reinforcement Learning	Course code MATH6019	Units 6
	Course name Complex Analysis	Course code MATHX100	Units 6
	Course name Internship in Mathematics	Course code MATHX101	Units 6
	Course name Mathematical Modelling	Course code MATHX103	Units 6
	Course name Differential Equations	Course code MATHX202	Units 6
	Course name Numerical Methods	Course code MATHX204	Units 6
	Course name Optimisation	Course code MATHX205	Units 6
	Course name Real Analysis	Course code MATHX206	Units 6
	Course name Advanced Differential Equations	Course code MATHX300	Units 6
	Course name Advanced Mathematical Modelling	Course code MATHX301	Units 6
	Course name Advanced Optimisation	Course code MATHX302	Units 6
	Course name Complex Networks	Course code MATHX303	Units 6
	Course name Fluid Dynamics	Course code MATHX304	Units 6
	Course name Functional Analysis	Course code MATHX305	Units 6
	Course name Geometry of Surfaces	Course code MATHX306	Units 6
	Course name Groups, Rings and Fields	Course code MATHX307	Units 6
	Course name Measure and Integration	Course code MATHX310	Units 6
	Course name Metric and Topological Spaces	Course code MATHX311	Units 6
	Course name Number Theory	Course code MATHX312	Units 6
	Course name Advanced Time Series	Course code MATHX400	Units 6
	Course name Asymptotic Methods	Course code MATHX401	Units 6
	Course name Category Theory	Course code MATHX402	Units 6
	Course name Integral Transforms	Course code MATHX403	Units 6
	Course name Lie Algebras and Lie Groups	Course code MATHX404	Units 6
	Course name Mathematics of Artificial Intelligence	Course code MATHX405	Units 6
	Course name Riemannian Geometry	Course code MATHX408	Units 6
	Course name Smooth Manifolds	Course code MATHX409	Units 6
	Course name Topics in Applied Mathematics A	Course code MATHX410	Units 6
	Course name Topics in Applied Mathematics B	Course code MATHX411	Units 6
	Course name Topics in Pure Mathematics A	Course code MATHX412	Units 6
	Course name Topics in Pure Mathematics B	Course code MATHX413	Units 6
	Course name Natural Language Processing	Course code MATHX415	Units 6
	Course name Probability	Course code STATX200	Units 6
	Course name Stochastic Processes	Course code STATX303	Units 6
	Course name Causal Inference	Course code STATX403	Units 6
	Course name Advanced Computer Vision	Course code COMP6032	Units 6
	Course name Programming for Artificial Intelligence and Machine Learning 2	Course code COMP5064	Units 6
	Course name Information Theory	Course code COMP4007	Units 6
	Course name Mathematical Generative Artificial Intelligence	Course code ARTI1000	Units 6
	Course name Algebra	Course code MATHX201	Units 6
	Course name Introduction to Topological Data Analysis	Course code MATHX308	Units 6
	Course name Mathematical Biology	Course code MATHX309	Units 6
	Course name Simulation for Decision Science	Course code MATHX207	Units 6
	Course name Algebraic Topology	Course code MATH4010	Units 6
	Course name Advanced Stochastic Processes	Course code MATHX200	Units 6
	Course name Statistical Theory	Course code STAT2003	Units 6

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