Bachelor of Artificial Intelligence
2025 Deakin University Handbook
| Year | 2025 course information |
|---|---|
| Award granted | Bachelor of Artificial Intelligence |
| Deakin course code | S308E |
| Faculty | Faculty of Science, Engineering and Built Environment |
| Campus | ERC Institute, Singapore |
| Duration | 3 years full-time or part-time equivalent |
| Course Map - enrolment planning tool | The course maps are for new students commencing from Trimester 1 2025: Course maps for commencement in previous years are available on the Course Maps webpage or please contact a Student Adviser in Student Central. |
| Australian Qualifications Framework (AQF) recognition | The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 7 |
New course from Trimester 1, 2025. This course is intended for students studying onshore in Singapore, with located learning support provided by ERC Institute. This course is not available to domestic and international students studying online or onshore at campuses in Australia. | |
Course sub-headings
- Course overview
- Indicative student workload
- Career opportunities
- Course Learning Outcomes
- Course rules
- Minors
- Course structure
- Details of minor sequences
Course overview
Deakin’s Bachelor of Artificial Intelligence equips you with the knowledge and skills to design, develop and evolve computational 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 curriculum, ensuring what you learn is at the cutting edge of industry expectations and capabilities.
You will have access to fully equipped computer labs with state-of-the-art software and technologies, ensuring you graduate with the specialist skills to design and build the intelligent systems of the future.
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 are spending 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.
The rise of intelligent systems such as self-driving cars and smart digital assistants has created a 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 will 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 will be well-equipped to work on the design, development and operation of AI-driven software solutions and will work alongside software engineers, data scientists, application developers and business analysts, to ensure AI is appropriately integrated into software solutions.
Indicative student workload
You can expect to participate in a range of teaching activities each week. This could include lectures, 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.
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 be equipped with the specialist knowledge 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 engineer/scientist, data analyst, AI technology engineer, AI ethicist or an AI architect to name a few.
Course location
This program, delivered by Deakin University and ERC Institute is an exciting partnership between two quality institutions. It provides an opportunity for international students to experience the best of Australian teaching and learning practices while based in Singapore. This course is not available to international students studying online or onshore at campuses in Australia.
Equipment requirements
The learning experiences and assessment activities within this course require that students have access to a range of technologies beyond a desktop computer or laptop. Students will be required to purchase minor equipment, such as small single board computers, microcontrollers and sensors, which will be used within a range of units in this course. This equipment is also usable by the student beyond their studies. Equipment requirements and details of suppliers will be provided on a per-unit basis. The indicative cost of this equipment for this course is AUD$500.
For information regarding hardware and software requirements, please refer to the Bring your own device (BYOD) guidelines via the School of Information Technology website in addition to the individual unit outlines in the Handbook.
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. |
Course rules
To complete the Bachelor of Artificial Intelligence students must pass 24 credit points and meet the following course rules to be eligible to graduate:
- DAI001 Academic Integrity and Respect at Deakin (0-credit-point compulsory unit) in their first study period
- SIT010 Safety Induction Program (0-credit-point compulsory unit)
- STP010 Career Tools for Employability (0-credit-point compulsory unit)
- 17 credit points of core units
- 3 credit points of Artificial Intelligence capstone units
- 1 minor (4 credit points)
- a maximum of 10 credit points at level 1
- a minimum of 6 credit points at level 3
Students are required to meet the University's academic progress and conduct requirements. See the enrolment codes and terminology to help make sense of the University's vocabulary.
Minors
Refer to the details of each minor sequence for availability.
Course structure
Core
Year 1 - Trimester 1
| DAI001 | Academic Integrity and Respect at Deakin (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 |
| SIT112 | Introduction to Data Science and Artificial Intelligence |
Year 1 - Trimester 2
| SIT232 | Object-Oriented Development |
| SIT202 | Computer Networks and Communication |
| SIT194 | Introduction to Mathematical Modelling |
Year 1 - Trimester 3
| SIT103 | Database Fundamentals |
Year 2 - Trimester 1
| SIT221 | Data Structures and Algorithms |
| SIT215 | Computational Intelligence |
| SIT220 | Data Wrangling |
Plus one (1) minor 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 unit (one (1) credit point)
Year 2 - Trimester 3
One (1) capstone unit (one (1) credit point):
| SIT306 | IT Placements and Industry Experience ^+ |
Year 3 - Trimester 1
| SIT330 | Natural Language Processing |
Plus one (1) minor unit (one (1) credit point)
Plus one (1) capstone unit (one (1) credit point):
| SIT374 | Team Project (A) - Project Management and Practices ^~ |
Year 3 - Trimester 2
| SIT319 | Deep Learning |
| SIT332 | Robotics, Computer Vision and Speech Processing |
Plus one (1) minor unit (one (1) credit point)
Plus one (1) capstone unit (1 credit point):
| SIT378 | Team Project (B) - Execution and Delivery ^ |
^ 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.
# Corequisite of STP010 Career Tools for Employability (0-credit point compulsory unit).
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 |
| SIT226 | Cloud Automation Technologies |
| SIT323 | Cloud Native Application Development |
| SIT314 | Software Architecture and Scalability for Internet-Of-Things |
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 |