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Overview

The Master of Computer Science (Artificial Intelligence) provides education in artificial intelligence systems development and exploitation that solves real-world problems using contemporary technologies while leveraging aspects of human intelligence. It enable computing graduates to extend their skills in an important emerging area, preparing students for either higher degree study or … For more content click the Read More button below.

Student guidance

Program of study overview

Program of study notes

Program of study
72 Units

Admission requirements

Admission requirements

Assumed knowledge

English Language requirements

Aims

The course has been designed with industry input to prepare students to become computing professionals able to: 

  • Adapt and utilise the range of technologies that underpin machine learning and artificial intelligence, with the ability to apply them to a range of contemporary challenges whilst being mindful of the ethical implications of intelligent systems 
  • Analyse complex computational and data related problems from both a theoretical and practical perspective  
  • Draw on a range of different algorithms to develop solutions to complex computational problems using the most appropriate programming paradigm
  • Manage the development of solutions, and communicate effectively with experts across the computing discipline including computer hardware, systems software and end-user application development 
  • Work effectively both as an individual, as part of a team and as a technical manager of a team 
  • Exhibit a strong, practical understanding of professional and ethical responsibilities

Learning outcomes

On completion of the course you will be able to:
1.
Design and create integrated artificial intelligence and machine learning solutions to a broad spectrum of problem domains
2.
Select, justify and evaluate artificial intelligence and machine learning algorithms based on deep understanding of the technology and an awareness of implementation complexity
3.
Analyse abstract problems from a real-world setting, creating appropriate computational solutions
4.
Formalise and verify algorithms for correctness and performance with respect to a variety of metrics
5.
Understand the research directions of artificial intelligence and machine learning and build on that research to complete research problems
6.
Implement programs in various programming languages and paradigms
7.
Understand and analyse human factors and apply ethical and professional practices
8.
Work collaboratively in a team and communicate effectively in a variety of contexts

Student progression rules

Students must have achieved a GPA of at least 5 in 36 units of Year 1 topics to be able to take the Coursework with Research Component stream.

Note that students who wish to use their masters qualification to satisfy entry into a Flinders University research higher degree are required to have completed at least an 18 unit postgraduate research component.

Professional accreditation and recognition

Professional accreditation

Associations

Course/Course specialisation association