Course overview

Description
This course provides its graduates with the necessary knowledge and skills to explain and apply appropriate information technology (IT) methodologies to help an individual or organisation achieve its goals and objectives. Students also learn to appreciate the scientific foundations on which IT are built, and to anticipate the changing direction of IT and evaluate and communicate the effectiveness of new technologies. Read more about each specialisation and their program level outcomes.
Course title
Master of Information Technology (coursework)
Award abbreviation
MIT
Course code
62510
Course type
Master's degree by coursework only
Status
Current / 2025
Administered by
Physics, Mathematics and Computing
CRICOS code
083866G

Course details

Intake periods
Beginning of year and mid-year
Attendance type
Full- or part-time (Student visa holders should read Education Services for Overseas Students Act 2000 for more information.)
Articulation
The Master of Information Technology has the following exit awards: 60220 Graduate Certificate in Information Technology (24 points) (24 points), 60320 Graduate Diploma in Information Technology (48 points) (48 points)
Credit points required
96
A standard full-time load is 24 points per semester.
Standard course duration
1.5 years full-time (or equivalent part-time) comprising 72 points of taught units and 24 points of admission credit, as recognised and granted by the School
Maximum course duration
2 years full-time (or equivalent part-time) comprising up to 96 points of taught study (see Rule 5 for further information)
Professional accreditation
Master of Information Technology (coursework) is accredited by: Australian Computer Society (ACS).
Time limit
5 years
Delivery mode
Internal
Locations offered
UWA (Perth)
Domestic fee type
Commonwealth supported and/or HECS-HELP
Available to international students
Yes. For information on international student fees see 'Student Procedures: Fees'. (Enquiries: https://www.uwa.edu.au/askuwa)
Course Coordinator(s)
Professor Amitava Datta
Fees
Visit the fees calculator.

Prospective students should see the Future Students website for details on admission requirements, intake periods, fees, availability to international students, careers information etc.

Specialisations

SP-APCMP Applied Computing
SP-ARTIN Artificial Intelligence
SP-SOFSY Software Systems

Course structure

Key to availability of units:
S1
Semester 1
S2
Semester 2
N/A
not available in 2025 – may be available in 2026 or 2027
NS
non-standard teaching period

All units have a value of six points unless otherwise stated.

Students who have completed degree studies in a non-cognate area, or equivalent as recognised by the School, must complete relevant conversion units up to the value of 24 points as determined by the School upon offer of admission and by the scope of a student's prior study. Students choose either CITS2002 or CITS2005.

AvailabilityUnit codeUnitnameUnit requirementsContact hours
S1, S2CITS1003Introduction to Cybersecurity
Incompatibility
CITS3004 Cybersecurity
Lectures: 2-hours per week; Workshop/Practicals: 2-hours per week
S1, S2CITS1401Computational Thinking with Python
Prerequisites
Successful completion of
Mathematics Methods ATAR or equivalent
or MATH1721 Mathematics Foundations: Methods
or MATX1721 Mathematics Foundations
or
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
or BH011 Bachelor of Engineering (Honours)
Incompatibility
CITS2401 Computer Analysis and Visualisation
Lectures: 2-hours per week; Labs: 2-hours per week; WorkshopS: 1-hour per week
S1, S2CITS1402Relational Database Management Systems
Prerequisites

Successful completion of
Mathematics Applications ATAR or equivalent
or MATH1720 Mathematics Fundamentals or equivalent
or MATX1720 Mathematics Fundamentals

or Enrolment in 62510 Master of Information Technology
or 62530 Master of Data Science
Incompatibility
CITS2232 Databases
lectures: 2 hours per week; labs: 2 hours per week
S2CITS2002Systems Programming
Prerequisites
Successful completion of
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation

or
Enrolment in
62510 Master of Information Technology
and Successful completion of
CITS1401 Computational Thinking with Python
Incompatibility
CITS1002 Programming and System
Lectures: 3-hours per week; Laboratories: 2-hours per week
S1CITS2005Object Oriented Programming
Prerequisites
ATAR Mathematics Methods
or MATH1721 Mathematics Foundations: Methods or equivalent
or MATX1721 Mathematics Foundations
or Enrolment in
62510 Master of Information Technology
and CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation
Incompatibility
CITS1001 Software Engineering with Java
or CITX1001 Software Engineering with Java
Lectures: 2 hours per week; workshops: 1 hour per

Take all units (24 points):

AvailabilityUnit codeUnitnameUnit requirementsContact hours
S1CITS4401Software Requirements and Design
Prerequisites
Enrolment in
62510 Master of Information Technology
and Successful completion of
CITS1401 Computational Thinking with Python

or
Enrolment in
62550 Master of Professional Engineering
or BH008 Bachelor of Advanced Computer Science [Honours]
S1, S2CITS5206Information Technology Capstone Project
Prerequisites
Enrolment in
62510 Master of Information Technology
and 48 points Level 4
and Level 5 units
and Successful completion of
CITS5505 Agile Web Development
Incompatibility
CITS3200 Professional Computing
Clinic: 3-hours per week
S1CITS5505Agile Web Development
Prerequisites
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
and Successful completion of
CITS1401 Computational Thinking with Python
Incompatibility
CITS3403 Agile Web Development
Lectures: 2-hours per week; Laboratories: 2-hours per week
S1, S2PHIL4100Ethics and Critical Thinking
Prerequisites
Enrolment in
62510 Master of Information Technology
3 hours per week

Take unit(s) to the value of 24 points, including a minimum of 12 points at Level 5.

Note: Note: Enrolment in the Masters Research Project is by invitation only.

Group A
AvailabilityUnit codeUnitnameUnit requirementsContact hours
S1AUTO4508Mobile Robots
Prerequisites
Enrolment in 62550 Master of Professional Engineering (Electrical and Electronic Engineering specialisation
or Mechanical Engineering specialisation
or Software Engineering specialisation)
or
Enrolment in
62510 Master of Information Technology
and Successful completion of
CITS1401 Computational Thinking with Python

or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree and a WAM of at least 50
and Successful completion of
( 96 points and ( CITS1001 Software Engineering with Java
or CITX1001 Software Engineering with Java
or CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation
) )
Incompatibility
GENG5508 Robotics
lectures and laboratories
S2CITS4009Computational Data Analysis
Prerequisites
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
or 62560 Master of Renewable and Future Energy
or 62550 Master of Professional Engineering (SP-ECHEM Chemical Engineering specialisation
or SP-EMINI Mining Engineering specialisation
or the SP-ESOFT Software Engineering specialisation)
or 72530 Master of Environmental Science (SP-SSDSC Sensing and Spatial Data Science specialisation)

or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and Successful completion of
96 points
lectures: 2 hours per week; labs: 2 hours per week
S2CITS4012Natural Language Processing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 62550 Master of Professional Engineering
or BH008 Bachelor of Advanced Computer Science [Honours]
or ( Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation
Lectures: 2-hours per week; Laboratories: 2-hours per week.
S1CITS4402Computer Vision
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62530 Master of Data Science
or
62550 Master of Professional Engineering and SP-EBIOM Biomedical Engineering specialisation
or SP-EELEC Electrical and Electronic Engineering specialisation
or SP-ESOFT Software Engineering specialisation
or
53560 Master of Physics and SP-MEDPH Medical Physics
or 73660 Master of Medical Physics
or
BH008 Bachelor of Advanced Computer Science [Honours] and MJD-ARIDM Artificial Intelligence
or
Bachelor of Engineering (Honours) or an associated Combined Degree
and Successful completion of
96 points
and CITS2401 Computer Analysis and Visualisation
or CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
Incompatibility
CITS4240 Computer Vision
S2CITS4403Computational Modelling
Prerequisites
Enrolment in
BH008 Bachelor of Advanced Computer Science [Honours]
or HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 73660 Master of Medical Physics
or ( 61550 Master of Professional Engineering and Software Engineering specialisation
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation or equivalent
S1CITS4404Artificial Intelligence and Adaptive Systems
Prerequisites
Successful completion of
CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or CITS2402 Introduction to Data Science
or ELEC3020 Embedded Systems
or ( CITS1401 Computational Thinking with Python
and CITS4009 Computational Data Analysis
)
S1CITS4407Open Source Tools and Scripting
Prerequisites
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
or 72530 Master of Environmental Science
or 42630 Master of Business Analytics
N/ACITS4419Mobile and Wireless Computing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62530 Master of Data Science
or 62550 Master of Professional Engineering
or BH008 Bachelor of Advanced Computer Science [Honours]
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
and Successful completion of
CITS3002 Computer Networks
Lectures: 1 hour per week, Labs: 2 hours per week
S1, S2CITS5014Data and Information Technologies Research Project Part 1
Prerequisites
Enrolment in
62530 Master of Data Science
or 62510 Master of Information Technology
and Completion of at least 24 points of level 4/5 CITS/STAT/PHIL units and UWA weighted average mark (WAM) of at least 70 percent across ALL completed level 4 / level 5 CITS/STAT/PHIL units
Incompatibility
CITS5011 Data Science Research Project Part 1
S1, S2CITS5015Data and Information Technologies Research Project Part 2
Prerequisites
Enrolment in
62530 Master of Data Science
or 62510 Master of Information Technology
and Successful completion of
CITS5014 Data Science Research Project Part 1
Incompatibility
CITS5012 Data Science Research Project Part 2
S2CITS5017Deep Learning
Prerequisites
Successful completion of
CITS5508 Machine Learning
lectures: 2 hours per week; laboratories: 2 hours per week.
S2CITS5501Software Testing and Quality Assurance
Prerequisites

Enrolment in
62510 Master of Information Technology
or BH008 Bachelor of Advanced Computer Science [Honours]

and Successful completion of CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points
and CITS3301 Software Requirements and Design

or Enrolment in
62550 Master of Professional Engineering
S2CITS5503Cloud Computing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
or BH008 Bachelor of Advanced Computer Science [Honours]
or MJD-ICYDM International Cybersecurity
or MJD-CDSDM Computing and Data Science
and

Successful completion of
( CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or CITS2200 Data Structures and Algorithms
or CITS2402 Introduction to Data Science
or ( CITS1401 Computational Thinking with Python
and CITS4009 Computational Data Analysis

or BUSN5101 Programming for Business
and BUSN5002 Fundamentals of Business Analytics
)
or Enrolment in 62550 Master of Professional Engineering
Software Engineering specialisation
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points
and 12 points of programming-based units
S1CITS5504Data Warehousing
Prerequisites
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
and
CITS1401 Computational Thinking with Python
and CITS1402 Relational Database Management Systems
or
BUSN5101 Programming for Business
and INMT5526 Business Intelligence
Incompatibility
CITS3401 Data Warehousing
lectures: 2 hours per week; labs: 2 hours per week
S1CITS5506The Internet of Things
Prerequisites
Enrolment in
( 62510 Master of Information Technology
or 62530 Master of Data Science

and Successful completion of CITS1401 Computational Thinking with Python )
or
Enrolment in
62550 Master of Professional Engineering
Lectures: 2-hours per week; Labs: 3-hours per week
S2CITS5507High Performance Computing
Prerequisites

Enrolment in
( 62510 Master of Information Technology
or 62530 Master of Data Science

and 12 points of programming-based units )
or Enrolment in 62550 Master of Professional Engineering Software Engineering specialisation
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points including 12 points of programming-based units
Incompatibility
CITS3402 High Performance Computing
or SHPC4002 Advanced Computational Physics
S1CITS5508Machine Learning
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
or 62550 Master of Professional Engineering
or 53560 Master of Physics
or BH008 Bachelor of Advanced Computer Science [Honours]
or 73660 Master of Medical Physics
or ( Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or BUSN5101 Programming for Business
or CITS2401 Computer Analysis and Visualisation
lectures: 2 hours per week; labs: 2 hours per week for 11 weeks from week 2
S1, S2ENVT4411Geographic Information Systems Applications
Incompatibility
Unit(s) GEOG2201 Geographic Information Systems (ID 1384)
The total workload for the unit is 150 hours. This includes podcasts for viewing and reading to be undertaken prior to attending one compulsory 3-hour workshop per week where students will be contributing to interactive discussions together with practical lab work using GIS software. Completion of the practical workshop labs is necessary to enable skills for completing written unit assessment. Independent learning is required throughout the unit.
S1, S2GENG5507Risk, Reliability and Safety
Prerequisites
Enrolment in
62550 Master of Professional Engineering
or Enrolment in
62510 Master of Information Technology
or Enrolment in
62520 Master of Low Emission Energy Technologies
or Enrolment in
62560 Master of Renewable and Future Energy
or Enrolment in 73660 Master of Medical Physics
or

Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and Successful completion of
( 120 points and ( MATH1011 Multivariable Calculus
or MATX1011 Multivariable Calculus
and MATH1012 Mathematical Theory and Methods
or MATX1012 Mathematical Theory and Methods
)
lectures: 2 hour per week; practical classes: 1 hour per week; workshops: 3 hours per week
S1, S2INMT5518Supply Chain AnalyticsNonelectures/seminars/workshops: up to 3 hours per week
S1, S2INMT5526Business Intelligence
Prerequisites
Unit(s) INMT5518 Supply Chain Analytics
or Unit(s) BUSN5002 Fundamentals of Business Analytics
or Unit(s) BUSN5101 Programming for Business or equivalent
or Unit(s) CITS1401 Computational Thinking with Python or equivalent
lectures/seminars/workshops: up to 3 hours per week
S1, S2MGMT5504Data Analysis and Decision Making
Incompatibility
MGMT5513 Data Driven Decision Making
lectures/seminars/workshops: up to 3 hours per week
NS, S1, S2SVLG5001McCusker Centre for Citizenship Internship
Prerequisites
The vast Majority of students - No prerequistes
or Enrolment in
20820 Juris Doctor and the following units ( LAWS4101 Foundations of Law and Lawyering
and LAWS4102 Criminal Law .
and LAWS4103 Contract
and LAWS4104 Property
and LAWS4106 Torts
and LAWS4109 Legal Theory and Ethics
)
Incompatibility
for Juris Doctor students: LAWS5174 Legal Internship
Internship experience: approximately 100 hours; McCusker Centre attendance: approximately 8 hours

Applied Computing specialisation

Take unit(s) to the value of 24 points, including a minimum of 12 points at Level 5.

AvailabilityUnit codeUnitnameUnit requirementsContact hours
S2CITS4009Computational Data Analysis
Prerequisites
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
or 62560 Master of Renewable and Future Energy
or 62550 Master of Professional Engineering (SP-ECHEM Chemical Engineering specialisation
or SP-EMINI Mining Engineering specialisation
or the SP-ESOFT Software Engineering specialisation)
or 72530 Master of Environmental Science (SP-SSDSC Sensing and Spatial Data Science specialisation)

or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and Successful completion of
96 points
lectures: 2 hours per week; labs: 2 hours per week
S2CITS4012Natural Language Processing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 62550 Master of Professional Engineering
or BH008 Bachelor of Advanced Computer Science [Honours]
or ( Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation
Lectures: 2-hours per week; Laboratories: 2-hours per week.
S1CITS4402Computer Vision
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62530 Master of Data Science
or
62550 Master of Professional Engineering and SP-EBIOM Biomedical Engineering specialisation
or SP-EELEC Electrical and Electronic Engineering specialisation
or SP-ESOFT Software Engineering specialisation
or
53560 Master of Physics and SP-MEDPH Medical Physics
or 73660 Master of Medical Physics
or
BH008 Bachelor of Advanced Computer Science [Honours] and MJD-ARIDM Artificial Intelligence
or
Bachelor of Engineering (Honours) or an associated Combined Degree
and Successful completion of
96 points
and CITS2401 Computer Analysis and Visualisation
or CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
Incompatibility
CITS4240 Computer Vision
S2CITS4403Computational Modelling
Prerequisites
Enrolment in
BH008 Bachelor of Advanced Computer Science [Honours]
or HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 73660 Master of Medical Physics
or ( 61550 Master of Professional Engineering and Software Engineering specialisation
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation or equivalent
S1CITS4404Artificial Intelligence and Adaptive Systems
Prerequisites
Successful completion of
CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or CITS2402 Introduction to Data Science
or ELEC3020 Embedded Systems
or ( CITS1401 Computational Thinking with Python
and CITS4009 Computational Data Analysis
)
S1CITS4407Open Source Tools and Scripting
Prerequisites
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
or 72530 Master of Environmental Science
or 42630 Master of Business Analytics
N/ACITS4419Mobile and Wireless Computing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62530 Master of Data Science
or 62550 Master of Professional Engineering
or BH008 Bachelor of Advanced Computer Science [Honours]
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
and Successful completion of
CITS3002 Computer Networks
Lectures: 1 hour per week, Labs: 2 hours per week
S2CITS5017Deep Learning
Prerequisites
Successful completion of
CITS5508 Machine Learning
lectures: 2 hours per week; laboratories: 2 hours per week.
S2CITS5501Software Testing and Quality Assurance
Prerequisites

Enrolment in
62510 Master of Information Technology
or BH008 Bachelor of Advanced Computer Science [Honours]

and Successful completion of CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points
and CITS3301 Software Requirements and Design

or Enrolment in
62550 Master of Professional Engineering
S2CITS5503Cloud Computing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
or BH008 Bachelor of Advanced Computer Science [Honours]
or MJD-ICYDM International Cybersecurity
or MJD-CDSDM Computing and Data Science
and

Successful completion of
( CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or CITS2200 Data Structures and Algorithms
or CITS2402 Introduction to Data Science
or ( CITS1401 Computational Thinking with Python
and CITS4009 Computational Data Analysis

or BUSN5101 Programming for Business
and BUSN5002 Fundamentals of Business Analytics
)
or Enrolment in 62550 Master of Professional Engineering
Software Engineering specialisation
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points
and 12 points of programming-based units
S1CITS5504Data Warehousing
Prerequisites
Enrolment in
62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
and
CITS1401 Computational Thinking with Python
and CITS1402 Relational Database Management Systems
or
BUSN5101 Programming for Business
and INMT5526 Business Intelligence
Incompatibility
CITS3401 Data Warehousing
lectures: 2 hours per week; labs: 2 hours per week
S1CITS5506The Internet of Things
Prerequisites
Enrolment in
( 62510 Master of Information Technology
or 62530 Master of Data Science

and Successful completion of CITS1401 Computational Thinking with Python )
or
Enrolment in
62550 Master of Professional Engineering
Lectures: 2-hours per week; Labs: 3-hours per week
S2CITS5507High Performance Computing
Prerequisites

Enrolment in
( 62510 Master of Information Technology
or 62530 Master of Data Science

and 12 points of programming-based units )
or Enrolment in 62550 Master of Professional Engineering Software Engineering specialisation
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points including 12 points of programming-based units
Incompatibility
CITS3402 High Performance Computing
or SHPC4002 Advanced Computational Physics
S1CITS5508Machine Learning
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
or 62550 Master of Professional Engineering
or 53560 Master of Physics
or BH008 Bachelor of Advanced Computer Science [Honours]
or 73660 Master of Medical Physics
or ( Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or BUSN5101 Programming for Business
or CITS2401 Computer Analysis and Visualisation
lectures: 2 hours per week; labs: 2 hours per week for 11 weeks from week 2

Artificial Intelligence specialisation

Take all units (24 points):

AvailabilityUnit codeUnitnameUnit requirementsContact hours
S2CITS4012Natural Language Processing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 62550 Master of Professional Engineering
or BH008 Bachelor of Advanced Computer Science [Honours]
or ( Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or CITS2401 Computer Analysis and Visualisation
Lectures: 2-hours per week; Laboratories: 2-hours per week.
S1CITS4404Artificial Intelligence and Adaptive Systems
Prerequisites
Successful completion of
CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or CITS2402 Introduction to Data Science
or ELEC3020 Embedded Systems
or ( CITS1401 Computational Thinking with Python
and CITS4009 Computational Data Analysis
)
S2CITS5017Deep Learning
Prerequisites
Successful completion of
CITS5508 Machine Learning
lectures: 2 hours per week; laboratories: 2 hours per week.
S1CITS5508Machine Learning
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
or 62550 Master of Professional Engineering
or 53560 Master of Physics
or BH008 Bachelor of Advanced Computer Science [Honours]
or 73660 Master of Medical Physics
or ( Bachelor of Engineering (Honours) or an associated Combined Degree
and 96 points
)
and Successful completion of
CITS1401 Computational Thinking with Python
or CITX1401 Computational Thinking with Python
or BUSN5101 Programming for Business
or CITS2401 Computer Analysis and Visualisation
lectures: 2 hours per week; labs: 2 hours per week for 11 weeks from week 2

Software Systems specialisation

Take all units (24 points):

AvailabilityUnit codeUnitnameUnit requirementsContact hours
S2CITS5501Software Testing and Quality Assurance
Prerequisites

Enrolment in
62510 Master of Information Technology
or BH008 Bachelor of Advanced Computer Science [Honours]

and Successful completion of CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points
and CITS3301 Software Requirements and Design

or Enrolment in
62550 Master of Professional Engineering
S2CITS5503Cloud Computing
Prerequisites
Enrolment in
HON-CMSSE Computer Science and Software Engineering
or 62510 Master of Information Technology
or 62530 Master of Data Science
or 42630 Master of Business Analytics
or BH008 Bachelor of Advanced Computer Science [Honours]
or MJD-ICYDM International Cybersecurity
or MJD-CDSDM Computing and Data Science
and

Successful completion of
( CITS2002 Systems Programming
or CITS2005 Object Oriented Programming
or CITS2200 Data Structures and Algorithms
or CITS2402 Introduction to Data Science
or ( CITS1401 Computational Thinking with Python
and CITS4009 Computational Data Analysis

or BUSN5101 Programming for Business
and BUSN5002 Fundamentals of Business Analytics
)
or Enrolment in 62550 Master of Professional Engineering
Software Engineering specialisation
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points
and 12 points of programming-based units
S1CITS5506The Internet of Things
Prerequisites
Enrolment in
( 62510 Master of Information Technology
or 62530 Master of Data Science

and Successful completion of CITS1401 Computational Thinking with Python )
or
Enrolment in
62550 Master of Professional Engineering
Lectures: 2-hours per week; Labs: 3-hours per week
S2CITS5507High Performance Computing
Prerequisites

Enrolment in
( 62510 Master of Information Technology
or 62530 Master of Data Science

and 12 points of programming-based units )
or Enrolment in 62550 Master of Professional Engineering Software Engineering specialisation
or
Enrolment in
Bachelor of Engineering (Honours) or an associated Combined Degree
and 120 points including 12 points of programming-based units
Incompatibility
CITS3402 High Performance Computing
or SHPC4002 Advanced Computational Physics

See also the rules for the course and the Student Rules.

Rules

Applicability of the Student Rules, policies and procedures

1.(1) The Student Rules apply to students in this course.

(2) The policy, policy statements and guidance documents and student procedures apply, except as otherwise indicated in the rules for this course.

Academic Conduct Essentials and Communication and Research Skills modules

2.(1) A student who enrols in this course for the first time irrespective of whether they have previously been enrolled in another course of the University, must undertake the Academic Conduct Essentials module (the ACE module) and the Communication and Research Skills module (the CARS module).

(2) A student must successfully complete the ACE module within the first teaching period of their enrolment. Failure to complete the module within this timeframe will result in the student's unit results from this teaching period being withheld. These results will continue to be withheld until students avail themselves of a subsequent opportunity to achieve a passing grade in the ACE module. In the event that students complete units in subsequent teaching periods without completing the ACE module, these results will similarly be withheld. Students will not be permitted to submit late review or appeal applications regarding results which have been withheld for this reason and which they were unable to access in the normally permitted review period.

English Language competency requirements

3. To be considered eligible for consideration for admission to this course an applicant must satisfy the University's English language competence requirement as set out in the University Policy on Admission: Coursework.

Admission requirements

4. To be considered for admission to this course an applicant must have—

(a) a bachelor's degree, or an equivalent qualification, as recognised by UWA;

and

(b) the equivalent of a UWA weighted average mark of at least 65 per cent;

and

(c) completed Mathematics Methods ATAR, or equivalent, as recognised by UWA.

Admission ranking and selection

5. Where relevant, admission will be awarded to the highest ranked applicants or applicants selected based on the relevant requirements.

Articulations and exit awards

6.(1) This course has the following exit awards:

  • 60220 Graduate Certificate in Information Technology (24 points)
  • 60320 Graduate Diploma in Information Technology (48 points)

(2) A student who withdraws from the Master of Information Technology course before completing it, but after completing Level 4 and Level 5 units to the value of 24 points, may apply to the School to be awarded the Graduate Certificate in Information Technology.

(3) A student who withdraws from the Master of Information Technology course before completing it, but after completing Level 4 and Level 5 units to the value of 48 points, may apply to the School to be awarded the Graduate Diploma in Information Technology.

Course structure

7.(1) The course consists of units to a total value of 96 points (maximum value) which includes conversion units to a value of 24 points, course core units and specialisation units. The course comprises the following specialisations :

  • SP-APCMP Applied Computing
  • SP-ARTIN Artificial Intelligence
  • SP-SOFSY Software Systems

(2) Units must be selected in accordance with the course structure, as set out in these rules.

(3) Students who have completed a bachelor's degree with a major in a cognate area, or equivalent as recognised by the Faculty are granted credit for conversion units up to a value of 24 points.

Satisfactory progress

8. To make satisfactory progress a student must pass units to a point value greater than half the total value of units in which they remain enrolled after the final date for withdrawal without academic penalty.

9. A student who has not achieved a result of Ungraded Pass (UP) for the Communication and Research Skills module (the CARS module) when their progress status is assessed will not have made satisfactory progress even if they have met the other requirements for satisfactory progress in Rule 8.

Progress status

10.(1) A student who makes satisfactory progress in terms of Rule 8 is assigned the status of 'Good Standing'.

(2) Unless the relevant board determines otherwise because of exceptional circumstances—

(a) a student who does not make satisfactory progress for the first time under Rule 8 is assigned a progress status of 'On Probation';

(b) a student who does not make satisfactory progress for the second time under Rule 8 is assigned a progress status of 'Suspended';

(c) a student who does not make satisfactory progress for the third time under Rule 8 is assigned a progress status of 'Excluded'.

11. A student who does not make satisfactory progress in terms of Rule 9 is assigned the progress status of 'On Probation', unless they have been assigned a progress status of 'Suspended' or 'Excluded' for failure to meet other satisfactory progress requirements in Rule 8.

Award with distinction

12. To be awarded the degree with distinction a student must achieve a course weighted average mark (WAM) of at least 80 per cent which is calculated based on—

(a) all units above Level 3 attempted as part of the course that are awarded a final percentage mark;

(b) all relevant units above Level 3 undertaken in articulating courses of this University that are awarded a final percentage mark;

and

(c) all units above Level 3 completed at this University that are credited to the master's degree course.

Deferrals

13. Applicants awarded admission to the course are entitled to a deferral of up to 12 months, as per the University Policy on: Admissions (Coursework).

Additional rules
Specialisations

14. Students may complete a maximum of two specialisations in this course.