UWA Handbook 2017

Course details

Master of Data Science (coursework or coursework and dissertation)

The Master of Data Science will prepare its graduates for a career in this rapidly expanding field of work. It will equip them with the necessary knowledge and skills to understand and apply appropriate analytical methodologies to transform the way an organisation achieves its goals and objectives, to deal effectively with large data management tasks, to master the statistical and machine learning foundations on which data analytics is built, and to evaluate and communicate the effectiveness of new technologies.

Course overview

Course overview

Course titleMaster of Data Science (coursework or coursework and dissertation)
Award abbreviationMDSc
Course code62530
Course typemaster's degree by coursework or by coursework and dissertation
Statuscurrent / 2017
Administered byFaculty of Engineering, Computing and Mathematics
CRICOS code093310E
COURSE DETAILS
  
Intake periodsBeginning of year and mid-year
Attendance typefull- or part-time (Student visa holders should read Education Services for Overseas Students Act 2000 for more information.)
ArticulationThe Master of Data Science has the following exit awards: 62230 Graduate Certificate in Data Science (24 points), 62330 Graduate Diploma in Data Science (48 points)
Credit points required96
A standard full-time load is 24 points per semester.
Standard course duration1.5 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 Faculty
Maximum course duration2 years full-time (or equivalent part-time) comprising up to 96 points of taught study (see Rule 5 for further information)
Professional accreditationMaster of Data Science (coursework or coursework and dissertation) is accredited by: Australian Computer Society (ACS).
Time limit5 years
Delivery modeinternal
Locations offeredUWA (Perth)
Domestic fee typePostgraduate fee-paying/FEE-HELP
Course Coordinator(s)Professor Amitava Datta

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

Course structure

Course structure

Key to availability of units:
S1 = Semester 1; S2 = Semester 2; N/A = not available in 2017

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

Note: Units that are indicated as N/A may be available in 2018 or 2019.

Note: Students are advised to refer to the recommended study guides available on the ECM website.

Students who have completed degree studies in a non-cognate area, or equivalent as recognised by the Faculty, must complete relevant conversion units up to the value of 24 points from this group, as advised by the Faculty.

S1, S2CITS1401Problem Solving and Programming
S2CITS1402Relational Database Management Systems
S1, S2CITS2401Computer Analysis and Visualisation
S1, S2STAT1400Statistics for Science
S1, S2STAT1520Economic and Business Statistics
S1STAT2401Analysis of Experiments
S2STAT2402Analysis of Observations

Take all units (36 points):

S2CITS4009Introduction to Data Science
S2CITS5503Cloud Computing
S1CITS5504Data Warehousing
N/ACITS5508Advanced Data Mining
S2STAT4063Computationally Intensive Methods in Statistics
S1STAT4064Applied Predictive Modelling

Take unit(s) to the value of 36 points, including a minimum of 18 points at Level 5.

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

Group A

S1CITS4008Scientific Communication
S1CITS4402Computer Vision
S1CITS4403Computational Modelling
S2CITS4404Artificial Intelligence and Adaptive Systems
S1CITS4407Open Source Tools and Scripting
S2CITS4419Mobile and Wireless Computing
S1, S2CITS5011Data Science Research Project Part 1
S1, S2CITS5012Data Science Research Project Part 2
S1, S2CITS5013Data Science Research Project Part 3 (12 points)
S1CITS5505Agile Web Development
S2CITS5506The Internet of Things
S2CITS5507High Performance Computing
S1, S2GENG5505Project Management and Engineering Practice
S2INMT5526Business Intelligence
S1, S2MGMT5504Data Analysis and Decision Making
S2PUBH5769Biostatistics II
N/APUBH5802Advanced Analysis of Linked Health Data
S1STAT4065Multilevel and Mixed-Effects Modelling
S1STAT4066Bayesian Computing and Statistics
S2STAT4067Applied Statistics and Data Visualisation

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

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 module

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, 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 Applications 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:

  • 62230 Graduate Certificate in Data Science (24 points)
  • 62330 Graduate Diploma in Data Science (48 points)

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

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

Course structure

7.(1) The course consists of units to a total value of 96 points (maximum value) which include conversion units to a value of 24 points.

(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 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 ACE 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 under Rule 8 is assigned the status of 'Good Standing'.

(2) Unless the Faculty 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 8 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 in—

(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.