The Master of Computer Science degree is designed to provide postgraduate studies in Computer Science at a professional level and also prepare students for the Master of Philosophy or doctoral research programs.The Master of Computer Science is professionally accredited by the Australian Computer Society.
This degree requires satisfactory completion of:
Year 1
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI814
|
IT Project Management
|
6
|
Autumn, Spring
|
|
CSCI851
|
Advanced Programming
|
6
|
Autumn, Spring
|
|
CSCI803
|
Algorithms and Data Structures
|
6
|
Spring
|
Select one of the following
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI835
|
Database Systems
|
6
|
Autumn, Spring
|
|
CSCI862
|
System Security
|
6
|
Spring
|
|
CSIT826
|
Human Computer Interaction
|
6
|
Spring
|
Plus one of the following
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
MTS9302
|
Corporate Network Management
|
6
|
Autumn
|
|
ISIT925
|
Strategic Network Design
|
6
|
Spring
|
|
And
|
|
|
|
|
CSIT940
|
Research Methodology
|
6
|
Autumn, Spring
|
Year 2
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI920
|
Contemporary Topics in Computer Science
|
6
|
Autumn
|
Students must take one of the following:*
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI991
|
Project
|
12
|
Annual, Spring 2020/Autumn 2021
|
|
CSCI992
|
Professional Project
|
12
|
Annual, Spring 2020/Autumn 2021
|
Plus 3 subjects (18 cp) towards a major plus 4 subjects (24cp) from CSCI Graduate Subject List - see listing below
OR 2 subjects (12cp) in a no major option plus 5 subjects (30cp) from CSCI Graduate Subject List - see listing below
* Enrolment in CSCI991 Project (12cp) will be permitted for students who receive final grade of 75% or above in CSIT940 Research Methodology and an average of 75% or greater in all other subjects. Where students receive a final grade of less than 75% in CSIT940 Research Methodology or do not achieve a 75% average in all other subjects, the candidate must enrol in CSCI992 Professional Project (12cp ). Interested students should contact the Academic Program Director whilst undertaking CSIT940 Research Methodology. In addition, CSCI991 Project or CSCI992 Professional Project must be completed in the major that the student completed or if completing the no major option related to the advanced subject that they complete.
Candidates may choose to complete a major in:
-
Intelligent Systems
-
Machine Learning and Big Data
-
Network and Information Security
-
Software Engineering
Or may wish to complete the 'No Major' option.
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI964
|
Computational Intelligence^
|
6
|
Autumn
|
|
CSCI924
|
Reasoning and Learning
|
6
|
Spring
|
|
CSCI944
|
Perception and Planning
|
6
|
Spring
|
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI933
|
Machine Learning Algorithms and Applications
|
6
|
Autumn
|
|
CSCI935
|
Computer Vision Algorithms and Systems
|
6
|
Spring
|
|
CSCI946
|
Big Data Analytics^
|
6
|
Spring
|
|
Subject Code
|
subject Name
|
Credit Points
|
Session(s)
|
|
CSCI968
|
Advanced Network Security^
|
6
|
Autumn
|
|
INFO912
|
Mathematics for Cryptography
|
6
|
Autumn
|
|
CSCI971
|
Advanced Computer Security
|
6
|
Spring
|
|
CSCI910
|
Software Requirements, Specifications and Formal Methods^
|
6
|
Autumn
|
|
CSCI926
|
Software Testing and Analysis
|
6
|
Autumn
|
|
CSCI927
|
Service-Oriented Software Engineering
|
6
|
Spring
|
Complete one of the following group of 2 subjects
Group 1
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI964
|
Computational Intelligence^
|
6
|
Autumn
|
|
CSCI924
|
Reasoning and Learning
|
6
|
Spring
|
Group 2
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI933
|
Machine Learning Algorithms and Applications
|
6
|
Autumn
|
|
CSCI946
|
Big Data Analytics^
|
6
|
Spring
|
Group 3
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI968
|
Advanced Network Security^
|
6
|
Autumn
|
|
CSCI971
|
Advanced Computer Security
|
6
|
Spring
|
Group 4
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI910
|
Software Requirements, Specifications and Formal Methods^
|
6
|
Autumn
|
|
CSCI927
|
Service-Oriented Software Engineering
|
6
|
Spring
|
Plus a subject from the CSCI Graduate Subject List
Please note that the subjects marked ^ above have pre-requisites.
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI910
|
Software Requirements, Specifications and Formal Methods
|
6
|
Autumn
|
|
CSCI924
|
Reasoning and Learning
|
6
|
Spring
|
|
CSCI926
|
Software Testing and Analysis
|
6
|
Autumn
|
|
CSCI927
|
Service-Oriented Software Engineering
|
6
|
Spring
|
|
CSCI933
|
Machine Learning Algorithms and Applications
|
6
|
Autumn
|
|
CSCI935
|
Computer Vision Algorithms and Systems
|
6
|
Spring
|
|
CSCI944
|
Perception and Planning
|
6
|
Spring
|
|
CSCI946
|
Big Data Analytics
|
6
|
Spring
|
|
CSCI964
|
Computational Intelligence
|
6
|
Autumn
|
|
CSCI968
|
Advanced Network Security
|
6
|
Autumn
|
|
CSCI971
|
Advanced Computer Security
|
6
|
Spring
|
Cognate Subject
Students may complete 1 of these subjects. Students wishing to undertake a second subject from this list must obtain prior approval from the Academic Program Director. Further, students must seek approval from the Subject Coordinator to ensure they have assumed knowledge.
|
Subject Code
|
Subject Name
|
Credit Points
|
Session(s)
|
|
CSCI941
|
Advanced Topics in Computer Science A
|
6
|
Not offered in 2020
|
|
CSCI942
|
Advanced Topics in Computer Science B
|
6
|
Not offered in 2020
|
|
CSCI943
|
Advanced Topics in Computer Science C
|
6
|
Not offered in 2020
|
|
ECTE903
|
Image and Video Processing
|
6
|
Spring
|
|
INFO911
|
Data Mining and Knowledge Discovery
|
6
|
Autumn
|
|
INFO912
|
Mathematics for Cryptography
|
6
|
Autumn
|
|
INFO913
|
Information Theory
|
6
|
Not offered in 2020
|
Information on academic and English language requirements, as well as eligibility for credit for prior learning, is available from the Course Finder.
Course Learning Outcomes are statements of learning achievement that are expressed in terms of what the learner is expected to know, understand and be able to do upon completion of a course. Students graduating from this course will be able to:
CLO Description
1 Solve complex real world problems by integrating computer science methods with effective management strategies and by developing and using computer applications.
2 Research, synthesise and apply key information and expert judgement in computer software design and project planning.
3 Interpret theoretical, practical and professional information and communicate knowledge, ideas and procedures to both computer scientists and stakeholders.
4 Employ independent learning strategies to update own knowledge in the field and keep pace with innovations in computer science techniques, industry trends and standards
5 Work as an individual and as a member of a team in a manner consistent with ethical and professional standards.
