Bachelor of Artificial Intelligence
2019 Deakin University Handbook
| Year | 2019 course information |
|---|---|
| Award granted | Bachelor of Artificial Intelligence |
| Course Map | 2019 course map |
| Campus | Offered at Burwood (Melbourne) |
| Cloud Campus | 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. |
New course commencing Trimester 1 2020 | |
Course sub-headings
- Course overview
- Indicative student workload
- Career opportunities
- Participation requirements
- Mandatory student checks
- Pathways
- Fees and charges
- Course Learning Outcomes
- Course rules
- Course structure
- Work experience
- Other learning experiences
Course overview
Artificial intelligence is driving digital disruption, with new technology helping redefine many industries. Many companies are looking to take advantage of recent advances in artificial intelligence, which is creating a large demand for skilled professionals. Deakin’s Bachelor of Artificial Intelligence will equip you with the knowledge and skills necessary to design, develop, and evolve software solutions that take advantages of the latest advances in artificial intelligence.
As an artificial intelligence specialist, you will work alongside software engineers, data scientists, application developers and business analysts, applying your specialist knowledge to ensure artificial intelligence is appropriately integrated into software solutions from a technical and human perspective.
You will gain hands-on experience in the development of software solutions and the use and development of artificial intelligence. Our world-leading research in artificial intelligence feed directly into our classrooms, meaning that you’ll be learning at the cutting edge of industry expectations and capabilities.
As a graduate you will be well-equipped to work on the design, development, and operation of software solutions involving artificial intelligence.
Units in the course may include assessment hurdle requirements.
Indicative student workload
The award conferred upon completion is recognised in the Australian Qualifications Framework at Level 7.
Career opportunities
AI offers an exciting future for students as more industries spend time and money on 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. Click here for more information.
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, your fee category and the year you started. To find out about the fees and charges that apply to you, visit www.deakin.edu.au/fees.
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 14 March 2019
Course rules
To complete the Bachelor of Artificial Intelligence, students must attain 24 credit points.
The course comprises a total of 24 credit points, which must include the following:
- 20 core units (totalling 20 credit points)
- 4 credit points of elective units
- level 1 - maximum of 10 credit points
- levels 2 and 3 - minimum of 14 credit points over both levels
- completion of STP050 Academic Integrity (0-credit point compulsory unit)
- completion of SIT010 Safety Induction Program (0-credit point compulsory unit)
- completion of STP010 Introduction to Work Placements (0-credit point compulsory unit)
Students are required to meet the University's academic progress and conduct requirements. Click here for more information.
Course structure
Core
Year 1 - Trimester 1
| STP050 | Academic Integrity (0 credit points) |
| SIT010 | Safety Induction Program (0 credit points) |
| STP010 | Introduction to Work Placements (0 credit points) |
| SIT102 | Introduction to Programming |
| SIT192 | Discrete Mathematics |
| SIT111 | Algorithms and Computing Systems |
| SIT114 | Introduction to Artificial Intelligence |
Year 1 - Trimester 2
| SIT232 | Object-Oriented Development |
| SIT103 | Data and Information Management |
| SIT202 | Networks and Communications |
| SIT194 | Introduction to Mathematical Modelling |
Year 2 - Trimester 1
| SIT221 | Data Structures and Algorithms |
| SIT215 | Artificial and Computational Intelligence |
Plus two elective units
Year 2 - Trimester 2
| SIT315 | Programming Paradigms |
| SIT223 | Professional Practice in Information Technology |
| SIT292 | Linear Algebra for Data Analysis |
Plus one elective unit
Year 2 - Trimester 3
| SIT306 | IT Placement |
Year 3 - Trimester 1
| SIT374 | Project Design |
| SIT307 | Data Mining and Machine Learning |
| SIT319 | Deep Learning ^ |
Plus one elective unit
Year 3 - Trimester 2
| SIT302 | Project Delivery |
| SIT316 | Optimisation and Constraint Programming |
| SIT314 | Developing Scalable Internet-Of-Things Applications |
^ available from 2022
Course structure
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 between 6 – 12 weeks (conditions apply, please refer to deakin.edu.au/sebe/wil.)
Elective units may also provide additional opportunities for Work Integrated Learning 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.
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.