Bachelor of Artificial Intelligence

General information

Overview

The Bachelor of Artificial Intelligence is designed to provide graduates with a broad and coherent body of knowledge in artificial intelligence and computing, together with the analytical, technical and professional skills required for practice in the ICT profession. The course aims to equip graduates with the knowledge, skills and professional attitudes consistent with the requirements of the Australian Computer Society.

Study structure

Successful completion of the Bachelor of Artificial Intelligence requires students to complete units of study to the value of 300 credit points. All units of study are valued at 12.5 credit points unless otherwise stated.

Full-time study: 100 credit points/eight standard units of study per year
Part-time study: 50 credit points/four standard units of study per year
One credit point is equivalent to one hour of study per week per semester (including contact hours and private study)
See the course planner for an example degree structure.

Full-time study: 100 credit points/eight standard units of study per year
One credit point is equivalent to one hour of study per week per semester (including contact hours and private study)
See the course planner for an example degree structure.

Core and major units

200 credit points

Units of study	Unit code
Core units
Computer Systems Core unit , 12.5 credit points	COS10004
Introduction to Programming Core unit , 12.5 credit points	COS10009
Web Technology Project Core unit , 12.5 credit points	COS10026
Technology in an Indigenous Context Project Core unit , 12.5 credit points	COS10025
Object Oriented Programming Core unit , 12.5 credit points	COS20007
Networks and Switching Core unit , 12.5 credit points	TNE10006
Computing Technology Project A Core unit , 12.5 credit points	COS40005
Computing Technology Project B Core unit , 12.5 credit points	COS40006
Major units
Technology in an Indigenous Context Project Major unit , 12.5 credit points	COS10025
Introduction to Artificial Intelligence Major unit , 12.5 credit points	COS30019
IoT Programming Major unit , 12.5 credit points	SWE30011
Computing Technology Innovation Project Major unit , 12.5 credit points	COS30049
Intelligent Systems Major unit , 12.5 credit points	COS30018
Natural Language Processing and GenAI Major unit , 12.5 credit points	COS30081
Artificial Intelligence Engineering Major unit , 12.5 credit points	COS40007
Applied Machine Learning Major unit , 12.5 credit points	COS30082

Choose from a combination of the following course components to complete 100 credit points of other study. Students may also select elective units (12.5 credit points each).

Co-majors

100 credit points

A co-major is a major in a field of study outside this course. You can choose one in addition to a first major. Co-majors will not be named on your testamur certificate however, they will be shown on your transcript of results.

Advertising
Animation
Biotechnology
Business Analysis
Cinema and Screen Studies
Climate and Social Justice
Computer Science
Creative Writing and Literature
Criminology
Data Analytics
Digital Advertising Technology
Environmental Science
Environmental Sustainability
Ethics and Technology
Games and Interactivity
Global Studies
History
Indigenous Studies
Information Systems
Journalism
Management
Marketing
Media Industries
Neuroscience
Perspectives on Globalisation
Philosophy
Politics and International Relations
Politics, Power and Technology
Professional and Creative Writing
Professional Writing and Editing
Psychology
Public Relations
Screen Production
Screen Studies and Popular Culture
Social Media
Space Technology

View co-major units

Minors

50 credit points

Minors are a structured set of 4 units or 50 credit points and may be chosen from any field of study.

Accounting
Advertising
Business Law
Data Analytics
Digital Advertising Technology
Digital Marketing
Entrepreneurship
Finance
Human Resource Management
International Relations and Security
Logistics and Supply Chain Management
Management
Managing Information Systems
Marketing
Public Relations
Social Impact
Social Media

View minor units

Work placement

You'll get paid to work in an area related to your field of study for either 6 or 12 months, where you'll combine hands-on learning with academic submissions, workplace reflection and feedback from your host organisation. Most students undertake their placements in the third year of their degree, so you’ll want to map out your electives as soon as you can and register for a placement at least 6 months before your preferred start date.

Optional professional work placement

50 or 100 credit points

Units of study	Unit code
Professional placement - Major (12 months)
Integrated Professional Placement A - Information and Communication Technology Academic unit, 25.0 credit points	ICT20013
Work Experience in Industry A Practical unit, 25.0 credit points	WEI20001
Integrated Professional Placement B - Information and Communication Technology Academic unit, 25.0 credit points	ICT20014
Work Experience in Industry B Practical unit, 25.0 credit points	WEI20002
or
Professional placement - Minor (6 months)
Integrated Professional Placement A - Information and Communication Technology Academic unit, 25.0 credit points	ICT20013
Work Experience in Industry A Practical unit, 25.0 credit points	WEI20001

Recommended elective units

These recommended elective units can deepen your understanding of your chosen major or an area of interest. A full list of available elective units can be found upon enrolment.

Artificial Intelligence major

COS30002 Artificial Intelligence for Games
COS30015 IT Security
COS30031 Games Programming
COS30045 Data Visualisation
COS40003 Concurrent Programming
MTH00007 Preliminary Mathematics
MTH10012 Calculus and Applications
MTH10013 Linear Algebra and Applications
MTH10020 Mathematics for Computing
MTH20015 Modelling Nature’s Non-Linearity
MTH20016 Quantitative Prediction
MTH30001 Stochastic Modelling
MTH30003 Numerical and Computational Mathematics
MTH30006 Optimisation
SWE30009 Software Testing and Reliability
SWE30011 IoT Programming
SWE40006 Software Deployment and Evolution
TNE30023 Advanced Switching

Cybersecurity major

CHE10007 Introduction to Forensic Science
COS30008 Data Structures and Patterns
COS30017 Software Development for Mobile Devices
COS30031 Games Programming
COS30043 Interface Design and Development
COS30045 Data Visualisation
COS40003 Concurrent Programming
CRI10002 Fundamentals of Criminology
FOR10001 Introduction to Forensic Psychology
ICT20025 ICT Design Project
MTH00007 Preliminary Mathematics
MTH10012 Calculus and Applications
MTH10013 Linear Algebra and Applications
MTH10020 Mathematics for Computing
MTH20015 Modelling Nature’s Non-Linearity
MTH20016 Quantitative Prediction
MTH30001 Stochastic Modelling
MTH30003 Numerical and Computational Mathematics
MTH30006 Optimisation
SWE30009 Software Testing and Reliability
SWE30011 IoT Programming
TNE30018 Enterprise Network Server Administration
TNE30023 Advanced Switching

Data Science major

COS30008 Data Structures and Patterns
COS30015 IT Security
COS30017 Software Development for Mobile Devices
COS30019 Introduction to Artificial Intelligence
COS30043 Interface Design and Development
ICT20025 ICT Design Project
INF10025 Data Management and Analytics
INF20016 Big Data Management
INF20031 Cyber Security for Business
INF30004 Business Intelligence and Data Visualisation
MBP10001 Technology and Data Acquisition
MTH00007 Preliminary Mathematics
MTH10012 Calculus and Applications
MTH10013 Linear Algebra and Applications
MTH10020 Mathematics for Computing
MTH20015 Modelling Nature’s Non-Linearity
MTH20016 Quantitative Prediction
MTH30001 Stochastic Modelling
MTH30003 Numerical and Computational Mathematics
MTH30006 Optimisation
STA20008 Statistics for Forensics
SWE30011 IoT Programming
TNE10005 Network Administration
TNE30023 Advanced Switching

Games Development major

ART10004 Introduction to Game Studies
COS30008 Data Structures and Patterns
COS30019 Introduction to Artificial Intelligence
COS30043 Interface Design and Development
MTH00007 Preliminary Mathematics
MTH10012 Calculus and Applications
MTH10013 Linear Algebra and Applications
MTH10020 Mathematics for Computing
SWE30011 IoT Programming
SWE40006 Software Deployment and Evolution

Internet of Things major

COS30008 Data Structures and Patterns
COS30018 Intelligent Systems
COS30019 Introduction to Artificial Intelligence
COS30031 Games Programming
COS30043 Interface Design and Development
COS30045 Data Visualisation
COS40003 Concurrent Programming
ICT20025 ICT Design Project
ICT30015 Technology Internship
MTH00007 Preliminary Mathematics
MTH10012 Calculus and Applications
MTH10013 Linear Algebra and Applications
MTH10020 Mathematics for Computing

Software Development major

COS30002 Artificial Intelligence for Games
COS30015 IT Security
COS30017 Software Development for Mobile Devices
COS30019 Introduction to Artificial Intelligence
COS30031 Games Programming
COS30045 Data Visualisation
MTH00007 Preliminary Mathematics
MTH00012 Foundation Mathematics
MTH10013 Linear Algebra and Applications
MTH10020 Mathematics for Computing
SWE30011 IoT Programming
SWE40006 Software Deployment and Evolution
TNE30012 Secure Remote Access Networks
TNE30023 Advanced Switching

Find more detail about elective units

Outcomes and course rules

Learning outcomes

On successful completion of this course students will be able to:

Analyse and integrate a broad and coherent body of knowledge in artificial intelligence and computer science across diverse application domains, exercising critical thinking and professional judgement, and recognising and respecting Indigenous perspectives and knowledge systems in the design and use of digital technologies.
Select, evaluate, and implement appropriate AI methods, algorithms, datadriven techniques, and contemporary tools to scope, design, develop, test, deploy, and manage intelligent systems in industryrelevant contexts.
Communicate and justify technical decisions effectively to technical and nontechnical stakeholders, collaborate productively as a team member or leader, and plan and manage AIfocused projects using appropriate project management tools and practices.
Evaluate ethical, professional, regulatory, and societal considerations and exercise accountability in the development, deployment, and management of artificial intelligence systems, demonstrating professional integrity and responsible practice in global and cultural contexts.
Analyse complex, industryrelevant problems and design, justify, and implement effective AIbased solutions, applying appropriate decisionmaking and problemsolving methodologies with intellectual independence and professional responsibility.
Critically reflect on personal performance, learning strategies, and selfmanagement practices, and develop strategies for continuous professional development and lifelong learning in the rapidly evolving field of artificial intelligence.

Career opportunities

Graduates of the Bachelor of Artificial Intelligence will be prepared for professional roles in the ICT sector requiring the development and application of intelligent systems. They will possess strong capabilities in the design, development, deployment and management of artificial intelligence solutions for medium to large-scale projects. Graduates will have demonstrated experience working effectively in multidisciplinary team environments and will exhibit well developed oral and written communication skills, enabling them to communicate technical concepts clearly to both specialist and non-specialist audiences.

Course rules

To qualify for the award of Bachelor of Artificial Intelligence, students must complete 300 credit points comprising of:

eight [8] core units (100 credit points)
eight [8] units of study from the Artificial Intelligence Major (100 credit points)
eight [8] units of other studies (100 credit points) comprising a co-major, minor, advanced minor or electives

Students complete no more than 150 credit points (normally 12 units) at Introductory Level (i.e. Stage 1). A unit of study can only be counted once. Where units are shared between majors and/or minors, students must choose an approved alternative unit.

Domestic students also have an opportunity to undertake a WIL Professional Placement. Please note that due to government regulation international students holding a student visa are not able to undertake Professional Placements in this course.

Volume of learning

The Bachelor of Artificial Intelligence consists of 300 credit points. Units normally carry 12.5 credit points (cps). A standard annual full-time load comprises 100 credit points and a part-time load comprises 50 credit points.

The volume of learning of the Bachelor of Artificial Intelligence is typically 3 years.

Professional placements

Professional Placements are subject to a competitive selection process. International students may be required to change courses in order to complete a placement and should consider visa implications and extended study duration prior to applying.

Students who undertake a 12-month professional placement are subject to the following course rules and must complete 375 credit points comprising:

eight [8] Artificial Intelligence Core units (100 credit points)
eight [8] units of study from the Artificial Intelligence Major (100 credit points)
four [4] units of study from the Professional Placement Co-Major (100 credit points); and
six [6] units of other studies (75 credit points) comprising a minor, advanced minor or electives

Students who undertake a 6-month professional placement are subject to the following course rules and must complete 337.5 credit points comprising:

eight [8] Artificial Intelligence Core units (100 credit points)
eight [8] units of study from the Artificial Intelligence Major (100 credit points)
two [2] units of study from the Professional Placement Minor (50 credit points); and
seven [7] units of other studies (87.5 credit points) comprising a minor, advanced minor or electives.

Maximum Academic Credit

The maximum level of credit that can be granted for the Bachelor of Artificial Intelligence is 200 credit points (normally 16 units).

Admission criteria

Information about Swinburne's general admission criteria can be found at Admissions at Swinburne - Higher Education webpage.

Interested in the Bachelor of Artificial Intelligence?

From state-of-the-art facilities to opportunities to engage with industry – this course is designed with your future in mind. Let's get started.

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