Note: This course is only available to re-enrolling students.

Course structure

Key to availability of units:
S1
Semester 1
S2
Semester 2

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

Take all units (24 points):

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
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
)
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
S1STAT4064Applied Predictive Modelling
Prerequisites

Course Enrolment in
the HON-MTHST Mathematics and Statistics [Honours]
or the 62530 Master of Data Science
or the 70550 Master of Bioinformatics
and STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
or STAT2062 Fundamentals of Probability with Applications
Incompatibility
STAT3406 Applied Statistics and Data Visualisation
Lectures: 2-hours per week; Computer Labs: 2-hours per week

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

Rules

Note: This course is only available to re-enrolling students.

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) Except as stated in (2), 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).

(2) A student who has previously achieved a result of Ungraded Pass (UP) for the ACE module is not required to repeat the module.

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 with a major in Data Science, or an equivalent qualification, as recognised by UWA; or

(b)

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

(ii) at least two years of full-time documented relevant industry experience considered by UWA to be sufficient to permit satisfactory completion of the course; and

(iii) a demonstrated data science and coding ability, as assessed 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. This course does not form part of an articulated sequence.

Course structure

7.(1) The course consists of units to a total value of 24 points.

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

Satisfactory progress

8. To make satisfactory progress in a calendar year a student must pass units to a value of at least 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 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. This rule is not applicable to this 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).