Why Bachelor of Mathematics?
Each day, the world generates vast amounts of data. Containing valuable insights, this data can help or hinder businesses. What most people don’t know is that mathematics is relied upon to deliver this current technological revolution.
Our Bachelor of Mathematics majoring in Data Science will prepare you for an exciting career in this growing field. You’ll learn data science practices including how to navigate complex networks and perform relevant analyses using advanced tools and algorithms.
Deeply practical, you’ll also connect with industry, discovering how to translate real-world problems into computer-driven solutions. You’ll graduate ready to thrive in your data science career, applying your expertise to change the way we live and work.
Overview
Our Bachelor of Mathematics majoring in Data Science provides a solid grounding in the mathematical principles, theories and advanced modelling techniques relevant to global industry practices.
In your Data Science major, you’ll build a deep knowledge of abstract theories used in mathematics and statistical modelling. Learning how to apply fundamental concepts in calculus, algebra, statistics and data taming.
Deeply practical, you might have opportunities to collaborate with industry and will complete a real-world project in your third year. You might also choose to undertake an additional honours year, developing advanced research skills that will set you apart to employers.
You’ll graduate with the expertise to understand data and translate business problems into a solution-focused, structured and organised blueprint. Preparing you well for an exciting career in a range of industries - including finance, healthcare, technology, education, government and more.
Key features
Study the fundamentals of mathematics and mathematical modelling before specialising in data science. - Common first year courses in mathematics provide flexibility for specialisation changes.
- Build a rigorous foundation to springboard into a range of industries.
- Learn how to use statistical tools and algorithms to solve complex problems.
- Create, interpret and communicate data and results.
- Further your studies in research by completing an honours fourth year.
What you'll learn
In our degree you will be exposed to contemporary, future-focused courses preparing you for an exciting future with unforeseen possibilities.
In first year, you’ll be introduced to fundamental mathematical theories, principles and concepts transferable across a range of careers. Courses in differential and integral calculus and statistical methods will help you see how discrete mathematics is applied to real-world problems.
Your second year will see you explore advanced topics in linear algebra, mathematical modelling and differential equations, applying knowledge in mathematical theories and statistical practice.
With the basics under your belt, you’ll dive deeper into your data science major. Learning how to model complex networks, use computational statistics and apply decision science principles. You’ll also discover how to perform relevant analyses using new and advanced tools and algorithms by applying these to complex and everyday problems.
In your third year, you’ll build important industry relationships with Adelaide University partners. You might do this through our specialised Maths Clinic, an internship or a supervised project. You’ll have the opportunity to build your communication, critical thinking and problem-solving skills – highly sought after by employers.
Assessments for this degree include assignments, online quizzes, examinations, research projects and lab/practical team-based projects.
Majors
Did you know that you can also choose a Bachelor of Mathematics with a major in one of the following:
What courses you'll study
Complete 144 units comprising:
- 60 units for Core courses, and
- 18 units from Work integrated learning, and
- Either:
- 48 units for Majors, or
- 48 units for Discipline courses, and
- 18 units for Electives
Complete 60 units comprising:
- 0 to 18 units from Common core, and
- 42 units from Program core
| Course name | Course code | Units | |
|---|---|---|---|
|
Course name
UG Common Core 1
|
Course code
AUXX1000
|
Units
6
|
|
|
Course name
UG Common Core 2
|
Course code
AUXX2000
|
Units
6
|
|
|
Course name
UG Common Core 3
|
Course code
AUXX3000
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Problem Solving and Programming
|
Course code
COMP1002
|
Units
6
|
|
|
Course name
Calculus 1
|
Course code
MATH1004
|
Units
6
|
|
|
Course name
Calculus 2
|
Course code
MATH1005
|
Units
6
|
|
|
Course name
Communication and Research Skills in Mathematics
|
Course code
MATH1020
|
Units
6
|
|
|
Course name
Linear Algebra
|
Course code
MATHX104
|
Units
6
|
|
|
Course name
Multivariable Calculus
|
Course code
MATHX203
|
Units
6
|
|
|
Course name
Probability and Statistics
|
Course code
STATX100
|
Units
6
|
Notes
Program core - Calculus 1 will not be compulsory for students entering the program who have successfully completed SACE Stage 2 Specialist Mathematics (or equivalent). For these students, Calculus 1 can be replaced with any first year mathematics elective.
Complete 48 units comprising:
- 18 units for all Data Science major courses, and
- 6 units from Level 1 Data Science major courses, and
- 6 units from Level 2 Data Science major courses, and
- 18 units from Level 3 Data Science major courses
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Optimisation
|
Course code
MATHX205
|
Units
6
|
|
|
Course name
Data Science Practice
|
Course code
STATX301
|
Units
6
|
|
|
Course name
Probability
|
Course code
STATX200
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Discrete Mathematics
|
Course code
MATH1006
|
Units
6
|
|
|
Course name
Geometry
|
Course code
MATH1007
|
Units
6
|
|
|
Course name
First Steps in Mathematics Research
|
Course code
MATH1011
|
Units
6
|
|
|
Course name
Mathematics in Action
|
Course code
MATH1012
|
Units
6
|
|
|
Course name
Introduction to Mathematical Data Science
|
Course code
MATH1035
|
Units
6
|
|
|
Course name
Critical Evaluation in Data Science
|
Course code
MATHX106
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Statistical Theory
|
Course code
STAT2003
|
Units
6
|
|
|
Course name
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
|
Course name
Introduction to Networks
|
Course code
MATHX102
|
Units
6
|
|
|
Course name
Mathematical Modelling
|
Course code
MATHX103
|
Units
6
|
|
|
Course name
Algebra
|
Course code
MATHX201
|
Units
6
|
|
|
Course name
Differential Equations
|
Course code
MATHX202
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Statistical Methodology
|
Course code
STAT3000
|
Units
6
|
|
|
Course name
Computational Statistics
|
Course code
STAT3006
|
Units
6
|
|
|
Course name
Simulation for Decision Science
|
Course code
MATHX207
|
Units
6
|
|
|
Course name
Advanced Optimisation
|
Course code
MATHX302
|
Units
6
|
|
|
Course name
Complex Networks
|
Course code
MATHX303
|
Units
6
|
|
|
Course name
Time Series Analysis
|
Course code
MATHX313
|
Units
6
|
|
|
Course name
Text and Social Media Analytics M
|
Course code
COMPX300
|
Units
6
|
Complete exactly 18 units from the following:
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Professional Practice
|
Course code
MATH1021
|
Units
6
|
|
|
Course name
Internship in Mathematics
|
Course code
MATHX101
|
Units
6
|
|
|
Course name
Statistical Practice
|
Course code
STATX290
|
Units
6
|
|
|
Course name
Mathematics Clinic 1
|
Course code
MATH3013
|
Units
6
|
|
|
Course name
Mathematics Clinic 2
|
Course code
MATH3900
|
Units
6
|
|
|
Course name
Project in Mathematics
|
Course code
MATH3901
|
Units
6
|
Complete 18 units comprising:
- 6 units from University-wide electives Level 1, and
- One of the following:
- 6 units from Discipline electives Level 2, or
- 6 units from Applied Mathematics electives Level 2, or
- 6 units from Data Science electives Level 2, or
- 6 units from Pure Mathematics electives Level 2, or
- 6 units from Statistics electives Level 2, and
- One of the following:
- 6 units from Discipline electives Level 3, or
- 6 units from Applied Mathematics electives Level 3, or
- 6 units from Data Science electives Level 3, or
- 6 units from Pure Mathematics electives Level 3, or
- 6 units from Statistics electives Level 3
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Elective 1
|
Course code
AUXX1011
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Elective 1
|
Course code
AUXX1011
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Further Steps in Mathematics Research
|
Course code
MATH2010
|
Units
6
|
|
|
Course name
Complex Analysis
|
Course code
MATHX100
|
Units
6
|
|
|
Course name
Introduction to Networks
|
Course code
MATHX102
|
Units
6
|
|
|
Course name
Mathematical Modelling
|
Course code
MATHX103
|
Units
6
|
|
|
Course name
Algebra
|
Course code
MATHX201
|
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
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
|
Course name
Probability
|
Course code
STATX200
|
Units
6
|
|
|
Course name
Statistical Theory
|
Course code
STAT2003
|
Units
6
|
|
|
Course name
Design of Experiments
|
Course code
STATX500
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Further Steps in Mathematics Research
|
Course code
MATH2010
|
Units
6
|
|
|
Course name
Statistical Theory
|
Course code
STAT2003
|
Units
6
|
|
|
Course name
Complex Analysis
|
Course code
MATHX100
|
Units
6
|
|
|
Course name
Introduction to Networks
|
Course code
MATHX102
|
Units
6
|
|
|
Course name
Mathematical Modelling
|
Course code
MATHX103
|
Units
6
|
|
|
Course name
Algebra
|
Course code
MATHX201
|
Units
6
|
|
|
Course name
Differential Equations
|
Course code
MATHX202
|
Units
6
|
|
|
Course name
Numerical Methods
|
Course code
MATHX204
|
Units
6
|
|
|
Course name
Real Analysis
|
Course code
MATHX206
|
Units
6
|
|
|
Course name
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
|
Course name
Design of Experiments
|
Course code
STATX500
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Further Steps in Mathematics Research
|
Course code
MATH2010
|
Units
6
|
|
|
Course name
Statistical Theory
|
Course code
STAT2003
|
Units
6
|
|
|
Course name
Complex Analysis
|
Course code
MATHX100
|
Units
6
|
|
|
Course name
Introduction to Networks
|
Course code
MATHX102
|
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
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
|
Course name
Probability
|
Course code
STATX200
|
Units
6
|
|
|
Course name
Design of Experiments
|
Course code
STATX500
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Complex Analysis
|
Course code
MATHX100
|
Units
6
|
|
|
Course name
Introduction to Networks
|
Course code
MATHX102
|
Units
6
|
|
|
Course name
Mathematical Modelling
|
Course code
MATHX103
|
Units
6
|
|
|
Course name
Algebra
|
Course code
MATHX201
|
Units
6
|
|
|
Course name
Differential Equations
|
Course code
MATHX202
|
Units
6
|
|
|
Course name
Numerical Methods
|
Course code
MATHX204
|
Units
6
|
|
|
Course name
Real Analysis
|
Course code
MATHX206
|
Units
6
|
|
|
Course name
Optimisation
|
Course code
MATHX205
|
Units
6
|
|
|
Course name
Data Visualisation
|
Course code
MATHX314
|
Units
6
|
|
|
Course name
Design of Experiments
|
Course code
STATX500
|
Units
6
|
|
|
Course name
Further Steps in Mathematics Research
|
Course code
MATH2010
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Elective 1
|
Course code
AUXX1011
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Cryptography
|
Course code
MATH3022
|
Units
6
|
|
|
Course name
Advanced Statistical Theory
|
Course code
STAT3005
|
Units
6
|
|
|
Course name
Computational Statistics
|
Course code
STAT3006
|
Units
6
|
|
|
Course name
Text and Social Media Analytics
|
Course code
COMPX300
|
Units
6
|
|
|
Course name
Simulation for Decision Science
|
Course code
MATHX207
|
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
Introduction to Topological Data Analysis
|
Course code
MATHX308
|
Units
6
|
|
|
Course name
Mathematical Biology
|
Course code
MATHX309
|
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
Time Series Analysis
|
Course code
MATHX313
|
Units
6
|
|
|
Course name
Bayesian Statistical Practice
|
Course code
STATX300
|
Units
6
|
|
|
Course name
Data Science Practice
|
Course code
STATX301
|
Units
6
|
|
|
Course name
Statistical Methodology
|
Course code
STATX302
|
Units
6
|
|
|
Course name
Stochastic Processes
|
Course code
STATX303
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Text and Social Media Analytics
|
Course code
COMPX300
|
Units
6
|
|
|
Course name
Simulation for Decision Science
|
Course code
MATH2000
|
Units
6
|
|
|
Course name
Advanced Mathematical Modelling
|
Course code
MATH3001
|
Units
6
|
|
|
Course name
Mathematical Biology
|
Course code
MATH3002
|
Units
6
|
|
|
Course name
Advanced Optimisation
|
Course code
MATH3003
|
Units
6
|
|
|
Course name
Groups, Rings and Fields
|
Course code
MATH3004
|
Units
6
|
|
|
Course name
Metric and Topological Spaces
|
Course code
MATH3005
|
Units
6
|
|
|
Course name
Measure and Integration
|
Course code
MATH3006
|
Units
6
|
|
|
Course name
Geometry of Surfaces
|
Course code
MATH3007
|
Units
6
|
|
|
Course name
Number Theory
|
Course code
MATH3008
|
Units
6
|
|
|
Course name
Introduction to Topological Data Analysis
|
Course code
MATH3009
|
Units
6
|
|
|
Course name
Fluid Dynamics
|
Course code
MATH3011
|
Units
6
|
|
|
Course name
Functional Analysis
|
Course code
MATH3012
|
Units
6
|
|
|
Course name
Time Series Analysis
|
Course code
MATH3021
|
Units
6
|
|
|
Course name
Cryptography
|
Course code
MATH3022
|
Units
6
|
|
|
Course name
Complex Networks
|
Course code
MATH3023
|
Units
6
|
|
|
Course name
Statistical Methodology
|
Course code
STAT3000
|
Units
6
|
|
|
Course name
Stochastic Processes
|
Course code
STAT3002
|
Units
6
|
|
|
Course name
Data Science Practice
|
Course code
STAT3004
|
Units
6
|
|
|
Course name
Advanced Statistical Theory
|
Course code
STAT3005
|
Units
6
|
|
|
Course name
Computational Statistics
|
Course code
STAT3006
|
Units
6
|
|
|
Course name
Bayesian Statistical Practice
|
Course code
STAT3012
|
Units
6
|
|
|
Course name
Advanced Differential Equations
|
Course code
MATHX300
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Simulation for Decision Science
|
Course code
MATHX207
|
Units
6
|
|
|
Course name
Statistical Methodology
|
Course code
STATX302
|
Units
6
|
|
|
Course name
Stochastic Processes
|
Course code
STATX303
|
Units
6
|
|
|
Course name
Fluid Dynamics
|
Course code
MATHX304
|
Units
6
|
|
|
Course name
Mathematical Biology
|
Course code
MATHX309
|
Units
6
|
|
|
Course name
Advanced Optimisation
|
Course code
MATHX302
|
Units
6
|
|
|
Course name
Data Science Practice
|
Course code
STATX301
|
Units
6
|
|
|
Course name
Text and Social Media Analytics
|
Course code
COMPX300
|
Units
6
|
|
|
Course name
Groups, Rings and Fields
|
Course code
MATH3004
|
Units
6
|
|
|
Course name
Metric and Topological Spaces
|
Course code
MATH3005
|
Units
6
|
|
|
Course name
Measure and Integration
|
Course code
MATH3006
|
Units
6
|
|
|
Course name
Geometry of Surfaces
|
Course code
MATH3007
|
Units
6
|
|
|
Course name
Number Theory
|
Course code
MATH3008
|
Units
6
|
|
|
Course name
Functional Analysis
|
Course code
MATH3012
|
Units
6
|
|
|
Course name
Cryptography
|
Course code
MATH3022
|
Units
6
|
|
|
Course name
Advanced Statistical Theory
|
Course code
STAT3005
|
Units
6
|
|
|
Course name
Computational Statistics
|
Course code
STAT3006
|
Units
6
|
|
|
Course name
Advanced Differential Equations
|
Course code
MATHX300
|
Units
6
|
|
|
Course name
Advanced Mathematical Modelling
|
Course code
MATHX301
|
Units
6
|
|
|
Course name
Complex Networks
|
Course code
MATHX303
|
Units
6
|
|
|
Course name
Bayesian Statistical Practice
|
Course code
STATX300
|
Units
6
|
|
|
Course name
Introduction to Topological Data Analysis
|
Course code
MATHX308
|
Units
6
|
|
|
Course name
Time Series Analysis
|
Course code
MATHX313
|
Units
6
|
| Course name | Course code | Units | |
|---|---|---|---|
|
|
Course name
Simulation for Decision Science
|
Course code
MATH2000
|
Units
6
|
|
|
Course name
Mathematical Biology
|
Course code
MATH3002
|
Units
6
|
|
|
Course name
Advanced Optimisation
|
Course code
MATH3003
|
Units
6
|
|
|
Course name
Groups, Rings and Fields
|
Course code
MATH3004
|
Units
6
|
|
|
Course name
Metric and Topological Spaces
|
Course code
MATH3005
|
Units
6
|
|
|
Course name
Measure and Integration
|
Course code
MATH3006
|
Units
6
|
|
|
Course name
Geometry of Surfaces
|
Course code
MATH3007
|
Units
6
|
|
|
Course name
Number Theory
|
Course code
MATH3008
|
Units
6
|
|
|
Course name
Introduction to Topological Data Analysis
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Course code
MATH3009
|
Units
6
|
|
|
Course name
Advanced Differential Equations
|
Course code
MATH3010
|
Units
6
|
|
|
Course name
Fluid Dynamics
|
Course code
MATH3011
|
Units
6
|
|
|
Course name
Functional Analysis
|
Course code
MATH3012
|
Units
6
|
|
|
Course name
Time Series Analysis
|
Course code
MATH3021
|
Units
6
|
|
|
Course name
Cryptography
|
Course code
MATH3022
|
Units
6
|
|
|
Course name
Complex Networks
|
Course code
MATH3023
|
Units
6
|
|
|
Course name
Stochastic Processes
|
Course code
STAT3002
|
Units
6
|
|
|
Course name
Advanced Statistical Theory
|
Course code
STAT3005
|
Units
6
|
|
|
Course name
Computational Statistics
|
Course code
STAT3006
|
Units
6
|
|
|
Course name
Bayesian Statistical Practice
|
Course code
STAT3012
|
Units
6
|
|
|
Course name
Text and Social Media Analytics
|
Course code
COMPX300
|
Units
6
|
|
|
Course name
Advanced Mathematical Modelling
|
Course code
MATHX301
|
Units
6
|
|
|
Course name
Data Science Practice
|
Course code
STATX301
|
Units
6
|
Notes
Discipline electives Level 2 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Applied Mathematics electives Level 2 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Data Science electives Level 2 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Pure Mathematics electives Level 2 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Statistics electives Level 2 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Discipline electives Level 3 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Applied Mathematics electives Level 3 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Data Science electives Level 3 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Pure Mathematics electives Level 3 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Statistics electives Level 3 - Students may elect to replace the Discipline Electives with open electives under guidance from the Program Director
Career outcomes
The growing amount of diverse data in the world has left many organisations grappling with how to best integrate analytics into their daily operations and decision-making processes. Your unique expertise in taming and making sense of data, combined with deep knowledge of mathematical principles, places you front and centre for these career opportunities.
You could use your specialised mathematics expertise to analyse health data and develop treatment strategies on behalf of pharmaceutical companies. You might assess environmental impacts and develop sustainable solutions for renewable energy companies. Or perhaps you’ll help businesses solve complex problems, improve operations, and make strategic decisions as a management consultant.
Careers may also include:
- Data scientist
- Big data researcher
- Big data visualiser
- Data miner.
Industry trends
Data science is one of the fastest growing occupations in Australia. There is currently ‘unmet’ demand for graduates with skills in this area – graduate ready to explore unlimited career possibilities (Australian Mathematical Sciences Institute, 2023).
The demand for fast, data-driven decision-making is becoming the norm for industries across the board. Employer interest in the application of artificial intelligence and big data technologies to achieve greater precision in their use and interpretation of data is creating a wealth of career opportunities for mathematicians to apply their expertise in these data-focused roles.
More broadly, a wide range of trends are driving the demand for mathematicians – across every industry. Advancements in areas like quantum computing, cybersecurity, predictive analytics, financial technologies, artificial intelligence, and biostatistics all depend upon the expertise of mathematicians to drive progress forward.
Ready to apply?
Please note that a non-refundable application fee of AUD$150 applies for every application submitted to Adelaide University.
Your study experience and support
Adelaide University sets you up for success in your studies – and your social life. You’ll have access to work placement and internship opportunities, overseas study tours and exchanges, networking events with guest speakers and more. Our campuses are equipped with purpose-built facilities including lecture theatres, libraries, workshops, laboratories, and spaces that simulate real work environments. These are all supported by the latest technologies and a 24/7 online learning platform with personalised study information and resources.
You’ll have everything you need to live well and thrive during your studies, with health services on campus, gymnasiums, technology zones and modern student lounges. Get involved in campus sport or join our student clubs that will connect you to your passions – and the people who share them.
Adelaide also has a variety of accommodation options to suit your individual requirements and budget, with options ranging from dedicated student accommodation to private rentals. One of the world’s most liveable cities, Adelaide has lots of leafy parks, gardens and social hubs – and some of the highest living standards globally. No matter where you are in Adelaide, you’re only a short distance from beaches, vineyards, museums, art galleries, restaurants, bars and parklands. Visit the accommodation web page to find out more.
Student services
We’re here to support you on your student journey. Adelaide University offers a range of support services and facilities, including:
- Career advice and mentoring services
- Personal counselling
- LGBTQIA+ support
- Academic support
- Fees and finance help
- Security services
- Accommodation services
- Common rooms
- Prayer rooms.
You’ll also have unlimited access to our dedicated student support hub. Visit in-person or online, or contact our friendly team by phone. We can assist you with anything study-related including enrolment, identification cards, timetables, fees and more.
Your campus
You'll be studying at one of our renowned campuses, accessing cutting-edge facilities and contemporary study spaces.
Study hours
Your courses will require a combination of different learning formats, including lectures, tutorials, workshops, seminars and practicals. Aside from your classes, you’ll also need to allocate additional time for independent study. This may include assignments, readings, projects and contributing to online discussion forums. As a rough guide, full-time studies may require 12-26 hours of class time and 14-18 hours of independent study per week.
Assessment
During your studies at Adelaide University, you’ll complete a mixture of practical, professional and research-based learning. Your assessment types will vary depending on the degree you’re studying, but may include:
- Case studies
- Essays and assignments
- Examinations
- Group projects
- Internships and placements
- Practicals
- Presentations
- Reports and project documentations
- Research projects
- Workplace and classroom contributions.
