C6004 Master of Data Science

The course comprises 96 credit points structured into three parts: Part A. Foundations for advanced data science studies, Part B. Core master's study  and Part C. Advanced practice

Part A. Foundations for advanced data science studies

These studies will provide an orientation to the field of data science at graduate level. They are intended for students whose previous qualification is not in a cognate field.

Part B. Core master's study

These studies draw on best practices within the broad realm of data science practice and research. You will gain a critical understanding of theoretical and practical issues relating to data science. 

Part C. Advanced practice 

The focus of these studies is professional or scholarly work that can contribute to a portfolio of professional development. You have two options: 

• a research pathway including a thesis. If you wish to use this master's course as a pathway to a higher degree by research you should take this first option. 
• a program of coursework involving advanced study and an industry experience studio project. 

Master's entry points

Depending on prior qualifications you may receive entry level credit (a form of block credit) which determines your point of entry to the course:

• If you are admitted at entry level 1 you complete 96 credit points, comprising Part A, Part B and Part C.
• If you are admitted at entry level 2 you complete 72 credit points, comprising Part B and Part C.

If you intend to specialise in Bioinformatics, you must complete both BMS level 5 units in Part B (12 credit points) and one BMS level 5 elective unit (6 credit points) from Part C. Please note that the Bioinformatics option is not available in Vietnam.

Note: If you are eligible for credit for prior studies you may elect not to receive the credit and complete one of the higher credit-point options.

Course progression map

The course progression map provides guidance on unit enrolment for each semester of study.

The course comprises 96 points structured into three parts: Part A. Foundations for advanced data science studies (24 points), Part B. Core master's study (48 points) and Part C. Advanced practice (24 points).

Units are 6 points unless otherwise stated.

Part A. Foundations for advanced data science studies (24 points)

You must complete four units (24 points):

• FIT9132 Introduction to databases
• FIT9136 Algorithms and programming foundations in Python
• FIT9137 Introduction to computer architecture and networks
• MAT9004 Mathematical foundations for data science

Part B. Core master's study (48 points)

You must complete:

a. five units (30 points)

• FIT5125 IT research methods
• FIT5145 Introduction to data science
• FIT5147 Data exploration and visualisation
• FIT5196 Data wrangling
• FIT5197 Statistical data modelling

b. three units (18 points) selected from:

• FIT5149 Applied data analysis
• FIT5201 Machine learning
• FIT5202 Data processing for big data
• FIT5205 Data in Society
• FIT5212 Data analysis for semi-structured data
• FIT5230 Malicious AI
• BMS5021 Introduction to bioinformatics
• BMS5022 Advanced bioinformatics: techniques for efficient genome, transcriptome and proteome analysis

Part C. Advanced practice (24 points)

You must complete either a. or b. below:

a. Minor thesis research:*

• FIT5126 Masters thesis part 1
• FIT5127 Masters thesis part 2
• FIT5228 Masters thesis part 3
• FIT5229 Masters thesis final

Enrolment in the research units is dependent on available supervisors and projects. Eligible students will be ranked based on their entire academic record and assessed for suitability to undertake the research component of this program.

* To be eligible for the research option, you must have successfully completed 24 credit points of level 5 FIT-coded units and have achieved an overall average of at least 75% across four completed FIT-coded level 5 units, and have achieved at least a distinction (70%) in FIT5125 IT research methods. If you are undertaking a single semester project you must have achieved an overall average of at least 80% across four completed FIT-coded level 5 units.

* For research projects in Bioinformatics, you must have successfully completed 24 points of level 5 units, and have achieved an overall average of at least 75% across all completed level 5 units, and have achieved at least a distinction in FIT5125 IT research methods and BMS5021 Introduction to bioinformatics.

b. Industry experience:

• FIT5120 Industry experience studio project (12 points)
• FIT5122 Professional practice
• one level 5 elective unit (6 points). You must have the required prerequisites for the unit you choose. Note: Some units may have restrictions on enrolments.