Graduate Certificate of Artificial Intelligence
2021 Deakin University Handbook
| Year | 2021 course information |
|---|---|
| Award granted | Graduate Certificate of Artificial Intelligence |
| Government subsidised short course | In 2021, the Australian Government's Job-ready Graduates package is providing a limited number of Commonwealth Supported Places (CSPs) in this course. |
| Course Map | Government subsidised short course – Trimester 1 2021 course map Government subsidised short course - Trimester 2 2021 course map For course advice please contact a Student Adviser. |
| Campus | Offered at Waurn Ponds (Geelong) |
| Cloud Campus | Yes |
| Duration | 0.5 year full-time or part-time equivalent |
| Deakin course code | S536J |
| 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 8. |
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
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 around the globe.
Deakin’s Graduate Certificate of Applied Artificial Intelligence provides IT professionals with foundational knowledge of artificial intelligence and the skills necessary to design and develop advanced solutions using artificial intelligence.
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 have a thorough understanding of the design, development, and operation of software solutions involving artificial intelligence.
Indicative student workload
You can expect to participate in a range of teaching activities each week, with units requiring on average 150 hours of study per credit point. This could include classes, seminars, practicals, studios and online interaction. You can refer to the individual unit details in the course structure for more information. In additional to scheduled activities, you will need to study and complete assessment tasks in your own time.
Career opportunities
Graduates of the Graduate Certificate of Applied Artificial Intelligence will be able to engage effectively with specialists in the area of artificial intelligence.
Participation requirements
Elective units may be selected that include compulsory placements, work-based training, community-based learning and collaborative research training arrangements.
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. Refer to the relevant unit guide.
Pathways
Upon completion of the Graduate Certificate of Artificial Intelligence you could use the credit points you’ve earned to enter into further study, including:
Master of Applied Artificial Intelligence
Master of Applied Artificial Intelligence (Professional)
Fees and charges
Fees and charges vary depending on your course, the type of fee place you hold, your commencement year and your study load. To find out about the fees and charges that apply to you, visit the Current students fees website or our handy Fee estimator to help estimate your tuition fees.
The Australian Government's Job-ready Graduates package provided a limited number of Commonwealth Supported Places (CSPs) for this course.
Course Learning Outcomes
| Deakin Graduate Learning Outcomes | Course Learning Outcomes |
| Discipline-specific knowledge and capabilities | Develop a broad knowledge of the technologies of artificial intelligence. |
| Communication | Prepare a range of technical and user-oriented documentation using adequate structure, terminology. |
| Digital literacy | Identify, select and use a range of digital technologies and tools to generate, manage and share digital resources associated with advanced artificial intelligence concepts and solutions. |
| Critical thinking | In assessing complex artificial intelligence scenarios, critically evaluate arguments, hypothesis, systems and proposals to identify basic statements. In assessing complex 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 complex 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 complex problems utilising advanced artificial intelligence. Apply expert, specialised technical skills and knowledge in modelling methods and processes to understand problems, handle abstraction and design novel artificial intelligence solutions. |
Approved by Faculty Board 27 June 2019
Course rules
To complete the Graduate Certificate of Artificial Intelligence, students must attain 4 credit points (part-time over 1 year) as detailed below.
The course comprises a total of 4 credit points, which must include the following:
- 3 credit points of core units
- 1 credit point Level 7 SIT elective unit (excluding SIT771, SIT772, SIT773 and SIT774)
- completion of STP050 Academic Integrity (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
| STP050 | Academic Integrity (0 credit point unit) |
| SIT720 | Machine Learning |
| SIT787 | Mathematics for Artificial Intelligence |
| SIT719 | Analytics for Security and Privacy |
Plus one level 7 SIT elective unit (one credit point)
Work experience
You will have an opportunity to undertake a discipline-specific internship placement as part of your course. deakin.edu.au/sebe/wil.
Further information
Student Central can help you with course planning, choosing the right units and explaining course rules and requirements.
- Contact Student Central