Bachelor of Artificial Intelligence
2023 Deakin University Handbook
Year | 2023 course information |
---|---|
Award granted | Bachelor of Artificial Intelligence |
Course Map | The course map for new students commencing from Trimester 1 2023. The course map for new students commencing from Trimester 2 2023. Course maps for commencement in previous years are available on the Course Maps webpage or please contact a Student Adviser in Student Central. |
Campus | Offered at Burwood (Melbourne) |
Online | Yes |
Duration | 3 years full-time or part-time equivalent |
CRICOS course code | 0100304 Burwood (Melbourne) |
Deakin course code | S308 |
Approval status | This course is approved by the University under the Higher Education Standards Framework. |
Australian Qualifications Framework (AQF) recognition | The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 7. |
Course sub-headings
- Course overview
- Indicative student workload
- Professional recognition
- Career opportunities
- Participation requirements
- Mandatory student checks
- Pathways
- Fees and charges
- Course Learning Outcomes
- Course rules
- Minor sequences
- Course structure
- Work experience
- Details of minor sequences
- Other learning experiences
Course overview
Deakin’s Bachelor of Artificial Intelligence equips you with the knowledge and skills to design, develop and evolve software solutions that harness the latest advances in artificial intelligence (AI). Get hands-on experience developing AI-driven software solutions with the support of academics who are leaders in this emerging field. Our world-class research in AI feeds directly into our classrooms, ensuring what you learn is at the cutting edge of industry expectations and capabilities.
You will have access to fully equipped computer labs with the latest software and technologies to ensure you graduate with the specialist skills to design and build the intelligent systems of the future. You will also have opportunities to obtain certificates from the training program for Microsoft Azure AI.
With a minimum of 100 hours of industry experience, you’ll develop in-demand skills working side-by-side with experienced AI specialists.
Want the skills to build intelligent machines and software that power our future?
AI is driving digital disruption, with new technology redefining many industries. Businesses are looking to take advantage of recent advances in AI, creating a large demand for skilled professionals.
AI offers you an exciting future, as a growing number of industries spend time and money improving what they do through learned behaviour and operating efficiencies. This is just the beginning; many more challenging, real-world problems remain to be solved.
Intelligent systems such as self-driving cars and smart digital assistants create high demand for skilled AI professionals to develop and implement them. The number of jobs emerging in the AI space is increasing each year and will enable productivity increases for most industries across the globe.
As an Artificial Intelligence specialist, you’ll work alongside software engineers, data scientists, application developers and business analysts, applying your expert knowledge to ensure AI is appropriately integrated into software solutions.
As a graduate, you'll be well-equipped to work on the design, development and operation of AI-driven software solutions.
Indicative student workload
You can expect to participate in a range of teaching activities each week. This could include classes, seminars, practicals and online interaction. You can refer to the individual unit details in the course structure for more information. You will also need to study and complete assessment tasks in your own time.
Professional recognition
The Bachelor of Artificial Intelligence is provisionally accredited with the Australian Computer Society (ACS).
Career opportunities
AI offers an exciting future for students as more industries invest in improving what they do through learned behaviour and operating efficiencies. However, this is the tip of the iceberg and many more challenging real-world problems remain to be solved.
Graduates will have the specialist knowledge and be equipped to work on the design, development and operation of software solutions involving AI, across a broad range of industry sectors. You may find employment in roles such as a data scientist, data analyst, AI technology software engineer, AI ethicist or an AI architect to name a few.
Participation requirements
Placement can occur at any time, including during the standard holiday breaks listed here: https://www.deakin.edu.au/courses/key-dates.
Elective units may be selected that include compulsory placements, work-based training, community-based learning or collaborative research training arrangements.
Reasonable adjustments to participation and other course requirements will be made for students with a disability. More information available at Disability support services.
Mandatory student checks
Any unit which contains work integrated learning, a community placement or interaction with the community may require a police check, Working with Children Check or other check.
Pathways
Graduates of the Bachelor of Artificial Intelligence will be able to progress to further studies in the Master of Applied Artificial Intelligence, the Master of Data Science or pursue research higher degrees after enrolling in the Bachelor of Information Technology (Honours).
Equipment requirements
For information regarding hardware and software requirements, please refer to the School of Information Technology's website, www.deakin.edu.au/information-technology/students or telephone 03 9244 6699.
Fees and charges
Fees and charges vary depending on your course, the type of fee place you hold, your commencement year, the units you choose and your study load.
Tuition fees increase at the beginning of each calendar year and all fees quoted are in Australian dollars ($AUD). Tuition fees do not include textbooks, computer equipment or software, other equipment or costs such as mandatory checks, travel and stationery.
Use the Fee estimator to see course and unit fees applicable to your course and type of place. Further information regarding tuition fees, other fees and charges, invoice due dates, withdrawal dates, payment methods is available on our Current students fees website.
Course Learning Outcomes
Deakin Graduate Learning Outcomes | Course Learning Outcomes |
Discipline-specific knowledge and capabilities | Develop a broad, coherent knowledge of the discipline of artificial intelligence, including deep learning and reinforcement learning, with detailed knowledge of key AI algorithms. Design, develop and implement software solutions that incorporate artificial intelligence Apply knowledge of artificial intelligence to the research and evaluation of AI solutions and provision of specialist advice. |
Communication | Prepare different types of technical and user-oriented documentation using adequate structure, terminology and context. Convey information in a clear, concise and coherent manner using appropriate oral communication techniques and skills. Represent ideas using IT codes, conventions, modelling languages, and standards to reflect on artificial intelligence ideas and processes in an effective manner. Apply interpersonal skills to proactively assist, contribute to ideas, respect opinions and value contribution made by others when working collaboratively. |
Digital literacy | Identify, select and use digital technologies and tools to generate, manage and share digital resources associated with artificial intelligence concepts and solutions. Independently and systematically locate information, evaluate its reliability, and use the information for design and problem solving. Identify appropriate practices and processes to ensure the security, integrity, safety and availability of digital resources. |
Critical thinking | In assessing artificial intelligence scenarios, critically evaluate arguments, hypothesis, systems, and proposals to identify basic statements. In assessing artificial intelligence scenarios, locate ambiguity and vagueness in arguments, requirements, and proposals to determine if ideas are reasonable, and identify information that may be contradictory, omitted, or not collected. In assessing artificial intelligence scenarios, apply judgement in evaluating ideas, associated reasoning, and available evidence to arrive at conclusions that are valid. |
Problem solving | Apply technical skills, knowledge and techniques to identify and define problems utilising artificial intelligence in a variety of contexts. Apply technical skills and knowledge in modelling methods and processes to understand problems, handle abstraction and design artificial intelligence solutions. Apply technical skills and knowledge to develop creative approaches and/or solutions in planning, designing, managing, evaluating and executing artificial intelligence projects. |
Self-management | Evaluate own knowledge and skills using frameworks of reflection and use that self-awareness to target professional goals. Recognise the need, and engage in, independent learning for continual development as a computing professional. Work under general direction, engaging in the feedback process independently to ensure outcomes are achieved. |
Teamwork | Contribute knowledge and skills of artificial intelligence when working within a team, demonstrating responsibility and accountability. Engage consistently and professionally in groupware to contribute knowledge and skills of artificial intelligence to achieve shared team objectives and outcomes. Apply strategies to support positive group dynamics and to function effectively as a team member. |
Global citizenship | Apply professional ethics, responsibilities, and norms of professional computing practice. Demonstrate awareness of regulation and ethical implications of acquisition, use, disclosure and eventual disposal of information. Engage with societal, health, safety, legal, and cultural issues to identify consequential responsibilities relevant to artificial intelligence in practice. |
Approved by Faculty Board 2 June 2022
Course rules
To complete the Bachelor of Artificial Intelligence, students must attain 24 credit points, which must include the following:
- Seventeen (17) credit points of core units
- completion of STP050 Academic Integrity (0-credit point compulsory unit)
- completion of SIT010 Safety Induction Program (0-credit point compulsory unit)
- completion of STP010 Career Tools for Employability (0-credit point compulsory unit)
- Three (3) credit points of Artificial Intelligence capstone units
- Four (4) credit points of open elective units or a minor sequence (4 credit points)
Students are required to meet the University's academic progress and conduct requirements.
Minor sequences
Refer to the details of each minor sequence for availability.
- Cloud Technologies
- Cyber Security
- Cyber Security Analytics
- Embedded Systems
- Finance
- Full Stack Development
- Health Analytics
- Human Resource Management
- Marketing
- Retail Management
- Security Management
- Sport Analytics
- Sustainability and Environmental Science
- Virtual and Augmented Reality
Course structure
Core
Year 1 - Trimester 1
STP050 | Academic Integrity (0 credit points) |
SIT010 | Safety Induction Program (0 credit points) |
STP010 | Career Tools for Employability (0 credit points) |
SIT102 | Introduction to Programming |
SIT192 | Discrete Mathematics |
SIT111 | Computer Systems |
SIT114 Introduction to Artificial Intelligence [No longer available for enrolment from 2024, alternate unit SIT112]
Year 1 - Trimester 2
SIT232 | Object-Oriented Development |
SIT103 | Database Fundamentals |
SIT202 | Computer Networks and Communication |
SIT194 | Introduction to Mathematical Modelling |
Year 2 - Trimester 1
SIT221 | Data Structures and Algorithms |
SIT215 | Computational Intelligence |
SIT220 | Data Wrangling |
Plus one (1) minor or elective unit (one (1) credit point)
Year 2 - Trimester 2
SIT307 | Machine Learning |
SIT223 | Professional Practice in Information Technology # |
SIT292 | Linear Algebra for Data Analysis |
Plus one (1) minor or elective unit (one (1) credit point)
Year 3 - Trimester 1
SIT319 | Deep Learning |
SIT330 | Natural Language Processing |
Plus one (1) minor or elective unit (one (1) credit point)
Plus one (1) credit point from the following capstone options:
SIT374 | Team Project (A) - Project Management and Practices ^~ OR |
One (1) SIT elective unit
Year 3 - Trimester 2
SIT332 | Robotics, Computer Vision and Speech Processing |
Plus one (1) minor or elective unit (one (1) credit point)
Plus two (2) credit points from the following capstone options:
SIT378 | Team Project (B) - Execution and Delivery ^ and |
SIT306 | IT Placements and Industry Experience ^+ |
OR
SIT344 | Professional Practice (2 credit points) ^+ |
^ offered in trimester 1, trimester 2, trimester 3
+ Students must have completed STP010 Career Tools for Employability (0-credit point compulsory unit) and SIT223 Professional Practice in IT.
~ Note: Students are recommended to undertake SIT374 and SIT378 in consecutive trimesters. Students should seek advice from the unit chair if they are unable to complete SIT374 and SIT378 consecutively.
# Corequisite of STP010 Career Tools for Employability (0-credit point compulsory unit)
Electives
Select from a range of elective units offered across many courses. In some cases you may even be able to choose elective units from a completely different discipline area (subject to meeting unit requirements).
It is important to note that some elective units may include compulsory placement, study tours, work-based training or collaborative research training arrangements.
Work experience
This course includes a compulsory work placement where you will be required to undertake a minimum of 100 hours in industry, providing professional work experience with an approved host organisation. Alternatively, high achieving students may have the opportunity to undertake an extended full-time paid industry-based learning placement (conditions apply, please refer to deakin.edu.au/sebe/wil.)
Elective units may also provide additional opportunities for Work Integrated Learning experiences.
Details of minor sequences
Cloud Technologies
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000011
Overview
In today’s data-driven digital world, cloud technologies are an area of significant business interest and their adoption and integration into business practices is growing at a rapid pace. This minor focuses on providing you with the knowledge, skills and expertise required to construct solutions using virtualisation, enterprise networks, system security and cloud infrastructure.
Units
SIT233 | Cloud Computing |
SIT325 | Advanced Network Security |
SIT323 | Cloud Native Application Development |
SIT314 | Software Architecture and Scalability for Internet-Of-Things |
Cyber Security
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000015
Overview
This minor sequence provides an insight into cyber security and equips you with skills in secure coding, security management and ethical hacking. In today's digital world, cyber security threats are a major challenge across many sectors. As cyber-attacks become everyday occurrences, IT professionals with the ability to identify, analyse and manage cyber security challenges are in increasing demand globally.
Units
SIT182 | Real World Practices for Cyber Security |
SIT218 | Secure Coding |
SIT284 | Cyber Security Management |
SIT379 | Ethical Hacking |
Cyber Security Analytics
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000016
Overview
In today's digital world, cyber security threats are a major challenge across many sectors. As cyber-attacks become everyday occurrences, IT professionals with the ability to identify, analyse and manage cyber security challenges are in increasing demand globally. This minor sequence provides an insight into the analysis of data associated with cyber security attacks.
Units
SIT182 | Real World Practices for Cyber Security |
SIT282 | Computer Forensics and Investigations |
SIT384 | Cyber Security Analytics |
Plus one (1) unit from:
SIT326 | Advanced Network Analytics and Forensics |
SIT327 | Network Forensics |
Embedded Systems
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000005
Overview
This minor will focus on developing solutions that use hardware, software, sensors, actuators, prototyping platforms and systems software. Students will gain the skills and knowledge to solve real-world problems in smart-homes, the Internet of Things and Robotics.
Units
SIT122 | Robotics Studio |
SIT123 Data Capture Technologies [No longer available for enrolment from 2024, alternate unit SIT225]
SIT210 | Embedded Systems Development |
SIT329 | Advanced Embedded Systems |
Finance
Campuses
Burwood (Melbourne), Online
Unit set code
MN-M30005
Overview
This minor will provide students with an understanding of the basic principles of business finance and the operation of money and capital markets. This knowledge is extended into practical application in domestic and international equity and debt markets.
Units
MAF101 | Fundamentals of Finance |
Plus three (3) units from:
MAF203 | Business Finance |
MAF202 | Money and Capital Markets |
MAF306 | International Finance and Investment |
MAF307 | Equities and Investment Analysis |
Full Stack Development
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000012
Overview
Web development is one of the fastest-growing careers in today’s economy, with growing demand for full stack web developers who are proficient in both front-end and back-end web development. Throughout this minor sequence, you will explore responsive web apps, full stack development across frontend applications and backend services, and mobile programming for Android and iOS.
Units
SIT120 | Introduction to Responsive Web Apps |
SIT331 | Full Stack Development: Secure Backend Services |
SIT313 | Full Stack Development: Secure Frontend Applications |
SIT305 | Mobile Application Development |
Health Analytics
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000017
Overview
This minor provides specialisation in health data analysis, which will enable students to have specific domain knowledge to work with the experts of the field and introduce using data science tools in the area. Students who are interested in the field of health and want to work as a data scientist in this area are encouraged to do this minor. HSH302 (Policy, Politics and Health) is recommended as an elective for those wanting to extend their studies in this area.
Units
HBS107 | Understanding Health |
HBS108 | Health Information and Data |
HSH205 | Epidemiology and Biostatistics 1 |
HSH216 | Epidemiology and Biostatistics 2 |
Human Resource Management
Campuses
Burwood (Melbourne), Online
Unit set code
MN-M30012
Overview
This minor will equip students with the skills, knowledge and abilities in order perform basic workplace tasks in human resource management. Human resource management is a critical area that is relevant to all organisations, it encompasses employees working effectively within and for organisations.
Units
MMM132 | Management |
Plus three (3) units from:
MMH230 | Fundamentals of Human Resource Management |
MMH231 | Human Resource Practice |
MMH232 | Human Resource Development |
MMH349 | Employment Relations |
Marketing
Campuses
Burwood (Melbourne), Online
Unit set code
MN-M30008
Overview
This minor focusses on developing discipline knowledge and industry-relevant practices in marketing. There is a strong focus on industry-relevant insights, the latest marketing practices, future market trends and strategy development in an ever-changing business landscape. The knowledge and skills developed within the marketing minor are complementary to anyone looking to better understand drivers to successful business outcomes, irrespective of which sector a business may sit within.
Units
MMK101 | Marketing Fundamentals |
Plus three (3) units from:
MMK251 | Services Marketing |
MMK266 | Consumer Behaviour |
MMK295 | Integrated Marketing Communications in the Digital Age |
MMK368 | Business Marketing |
Retail Management
Campuses
Burwood (Melbourne), Online
Unit set code
MN-M30009
Overview
This minor provides you with an understanding of what underpins management and operations in today’s retailing sector. Retail business are finding it increasingly difficult to compete without adopting innovation as new retailers (e.g. Amazon), increasingly impact the retail landscape at the expense of more traditional bricks and mortar stores. There is a strong emphasis in the minor on the dynamic nature of retailing including evolving trends through the increasing prevalence of digital marketing technologies, which are changing every aspect of the retailing landscape.
Units
MMK101 | Marketing Fundamentals |
Plus three (3) units from:
MMK217 | Retail Management |
MIS313 | Strategic Supply Chain Management |
MMK280 | Brand Management |
MMK317 | Advanced Retail Management |
Security Management
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000003
Overview
This minor will provide the opportunity for you to use your gained managerial and cyber security skills to assist companies in their planning, governance and change policies to help ensure their resilience and defence of related threats.
Units
MIS211 | Cyber Security and Governance |
MMH356 | Change Management |
MMM132 | Management |
SIT284 | Cyber Security Management |
Sports Analytics
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000020
Overview
This minor provides specialisation in Sports and Exercise data analysis, which will enable students to have specific domain knowledge to work with the experts of the field and introduce using data science tools in Sports and Exercise. Students who are interested in the field of Sports and Exercise and want to work as a data scientist in this area are encouraged to do this minor.
Units
HSE010 | Exercise and Sport Laboratory Safety (0 credit points) |
HSE104 | Research Methods and Data Analysis in Exercise and Sport |
HSE202 | Biomechanics |
HSE311 | Applied Sports Science 1 |
HSE314 | Applied Sports Science 2 |
Sustainability and Environmental Science
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000021
Overview
This minor provides specialisation in Sustainability and Environmental Science, which will enable students to have specific domain knowledge to work with the experts of the field and introduce using data science tools. Students who are interested in the field of Sustainability and Environmental Science and want to work as a data scientist in this area are encouraged to do this minor.
Units
SLE101 | Environmental Techniques and Monitoring |
SLE121 | Environmental Sustainability |
SLE207 | Environmental Planning and Impact Assessment |
SLE239 Introduction to Geographic Information Systems [No longer available for enrolment from 2024, alternate unit SLE245]
Virtual and Augmented Reality
Campuses
Burwood (Melbourne), Online
Unit set code
MN-S000009
Overview
Virtual and augmented reality technologies are revolutionising business processes, disrupting the way companies work with complex data sets, and enhancing educational and training practices. They contribute to novel therapies and treatments, allow access to opportunities despite physical and geographical restrictions and have redefined the way we represent and interact with digital media whether it be our holiday souvenir snapshots or the latest interactive gaming experience.
Units
SIT183 | Interactive Application Design for Virtual and Augmented Reality |
SIT283 | Development for Virtual and Augmented Reality |
SIT253 | Content Creation for Interactive Experiences |
SIT383 | Assembling Virtual and Augmented Reality Experiences |
Other course information
Course duration - additional information
Course duration may be affected by delays in completing course requirements, such as accessing or completing work placements.
Further information
Student Central can help you with course planning, choosing the right units and explaining course rules and requirements.
- Contact Student Central
Other learning experiences
To broaden your experience of the world, you will have an opportunity to participate in overseas placements and study tours as an elective option in your course.