Graduate Diploma in Artificial Intelligence and Machine Learning (GDipAIMLearn)
Graduate Diploma in Artificial Intelligence and Machine Learning (GDipAIMLearn)
Program Code
GDAIM
Program Faculty
Faculty of Sciences, Engineering and Technology
Academic Year
2025
These Program Rules should be read in conjunction with the University's policies (https://www.adelaide.edu.au/policies).
Overview
The Graduate Diploma in Artificial Intelligence and Machine Learning will provide graduates with a foundation in Artificial Intelligence and Machine Learning and allow for the identification and application of emerging developments and considerations. Artificial Intelligence and Machine Learning are rapidly evolving spaces with implications for the future of work and our daily lives.
In this program, students undertake a variety of core and elective courses, designed to provide knowledge of the techniques and theory of machine learning, and their basis in computer science and mathematics The program provides advanced standing to further learning in the Master of Artificial Intelligence and Machine Learning.
The Graduate Diploma in Artificial Intelligence and Machine Learning is an AQF Level 8 qualification with a standard full-time duration of 1 year.
Program Learning Outcomes
- Explain and use the techniques and methods of applied machine learning and artificial intelligence to meet industry needs.
- Identify, implement and analyse machine learning and artificial intelligence approaches and techniques suitable for industry datasets.
- Demonstrate strong independent and collaborative problem solving skills to develop software based machine learning solutions.
- Evaluate and select appropriate machine learning and artificial intelligence platforms to solve real-world problems.
- Follow ethical, social and legal considerations arising from the application of machine learning and artificial intelligence.
Conditions
Interruption of program: Students must apply for permission from the Faculty before taking a Leave of Absence. Any extension of the leave without approval will result in the loss of place in the program but an application may be made to be re-admitted to the program subject to the admission procedures in place at the time.
Program Maximum Duration: As specified in Table 1 of the Coursework Academic Programs Policy, this program must be completed within a Maximum Duration which includes any periods of non-enrolment, leave of absence or approved study at other institutions for credit towards a Program.
Academic Program Rules for Graduate Diploma in Artificial Intelligence and Machine Learning
There shall be a Graduate Diploma in Artificial Intelligence and Machine Learning.
Qualification Requirements
To qualify for the Graduate Diploma in Artificial Intelligence and Machine Learning, the student must complete satisfactorily a program of study consisting of the following requirements with a combined total of not less than 24 units, comprising:
- Core courses to the value of 18 units
- Elective courses to the value of 6 units
Core Courses
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Core Courses
To satisfy the requirements for Core Courses students must complete courses to the value of 18 units.
All of the following courses must be completed:
Subject/Catalogue Course Title Unit Value COMP SCI 7210 Foundations of Computer Science A 3 COMP SCI 7211 Foundations of Computer Science B 3 COMP SCI 7212 Human and Ethical Factors in Computer Science 3 COMP SCI 7327 Concepts in Artificial Intelligence and Machine Learning 3 COMP SCI 7328 Concepts in Cyber Security 3 PROJMGNT 5021 Project Management Fundamentals 3
Electives
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Electives
To satisfy the requirements for Electives students must complete courses to the value of 6 units.
Courses to the value of 6 units from the following:
Subject/Catalogue Course Title Unit Value COMP SCI 7314 Statistical Machine Learning 3 COMP SCI 7315 Computer Vision 3 COMP SCI 7317 Using Machine Learning Tools PG 3 COMP SCI 7318 Deep Learning Fundamentals 3 COMP SCI 7416 Applied Machine Learning 3 COMP SCI 7417 Applied Natural Language Processing 3 MATHS 7027 Mathematical Foundations of Data Science 3 PHIL 7005 Machine Learning and Artificial Intelligence 3 STEM 7555 STEM Internship 3