Data Science major
Strong computing and data analysis skills are becoming necessary in an ever-increasing number of disciplines and workplace contexts. This major focuses on data and scientific computation including technologies for efficient and effective data collection, conversion, analysis, visualisation, interpretation, storage, search, synthesis and provision through the internet. Many professional organisations use computing resources extensively for information analysis, storage, communication and distribution, providing you with many diverse career options as a graduate. The Data Science major provides students with practical computing and information technology skills.
Outcomes
Students are able to (1) understand that different programming languages have different strengths, and make an effective and efficient choice for solving a given problem; (2) write programs to carry out data manipulation tasks for both textual and numerical data; (3) write programs to perform data conversion for different purposes and to allow applications to be interfaced together; (4) employ computing tools to carry out appropriate statistical analyses of data, present results in a meaningful way, and interpret them in subject terms; (5) understand the many different ways of storing data, and the implications for storage space and ease of retrieval; (6) design appropriate schemas for storing information in databases, and access, sort and join data using query languages; (7) use scientific computing languages for problem solving, analysis, modelling, and visualisation of numerical data; (8) understand key data storage and knowledge discovery principles and techniques, and how to discover and extract knowledge from massive data stores; (9) understand the way in which features can be used to identify patterns in large volumes of data, and use tools and techniques to search (or 'mine') for patterns or relationships; (10) appreciate the issues associated with very large volumes of data and very high speed processing (as may be required, for example, for the Square Kilometre Array), and how these can be tackled using high-performance computing (supercomputing); (11) understand the primary mechanisms through which information is shared in the twenty-first century (through the internet), format data according to international standards for manual viewing and automated access, and write client and server programmes to facilitate such access; (12) work in teams to carry out projects in a professional setting for an industry or third party client, including requirements analysis, design, implementation, testing and documentation; (13) appreciate the ethical responsibilities of professional practice in computing; (14) communicate effectively in various media including writing and oral presentations; and (15) demonstrate basic research skills that can be applied in higher level studies.
Degree-specific major
Data Science can be taken as a degree-specific major in the following degree courses:
BP004 Bachelor of Science
BH005 Bachelor of Philosophy (Honours)
Overview of unit sequence
Data Science is a degree-specific single major comprising:
- two Level 1 units
- two Level 2 units
- four Level 3 units
- three Level 1 complementary units
- one Level 2 complementary unit
- one Level 3 complementary unit
| Key to availability of units: |
|---|
| S1 = Semester 1; S2 = Semester 2; SS = summer teaching period |
Level 1
Take all units (12 points):
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S1, S2 | CITS1401 | Computational Thinking with Python |
|
| S2, SS | CITS1402 | Relational Database Management Systems |
|
Take all complementary units (12 points) or, for students who have Mathematics: Methods ATAR or WACE Mathematics 3A/3B or equivalent or higher, take only STAT1400 (6 points):
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S1, S2 | MATH1720 | Mathematics Fundamentals |
|
| S1, S2 | STAT1400 | Statistics for Science |
Level 2
Take all units (12 points):
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S2 | CITS2002 | Systems Programming |
|
| S1, S2 | CITS2401 | Computer Analysis and Visualisation |
|
Take the following complementary unit:
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S1 | STAT2401 | Analysis of Experiments |
|
Level 3
Take all units (24 points):
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S2 | CITS3200 | Professional Computing | |
| S1 | CITS3401 | Data Warehousing |
|
| S2 | CITS3402 | High Performance Computing |
|
| S1 | CITS3403 | Agile Web Development |
|
Take the following complementary unit:
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S2 | CITS3004 | Cybersecurity |
|
Choosing your degree-specific major
You must satisfy the requirements of a degree-specific major before you complete your course. The flexible structure of an undergraduate course allows you to try out a number of different subjects to see what interests you before nominating your degree-specific major. You have the choice to either nominate your degree-specific major when you first enrol in the course or delay nominating it until your second year.
To plan the first year of your study without nominating a degree-specific major, you are advised to choose units that will pave the way to two or more degree-specific majors that are of interest to you. For examples of the choice of units available in first year, search the first-year study plans .
To fully understand the structure of an undergraduate course, read the course structure information and the Undergraduate Degree Course Rules.
The following example illustrates how the Data Science degree-specific major can be included in the Bachelor of Science course.
There are more choices open to you. For more examples, search the study plans .
Choosing a second major
You also have the option to choose a second major from those available in the Bachelor of Arts, Bachelor of Biomedical Science, Bachelor of Commerce, Bachelor of Design Only available to re-enrolling students. or Bachelor of Science course, giving you the opportunity to pursue your interests no matter how different they are.
The following example illustrates how the Data Science degree-specific major can be combined with a second major in the Bachelor of Science course.
For more examples of combinations of majors, search the study plans .
Data Science can also be taken as a second major.
Second major
Data Science can be taken as a second major in the following degree courses:
- BP001 Bachelor of Arts
- BP006 Bachelor of Biomedical Science
- BP002 Bachelor of Commerce
- BP003 Bachelor of Design Only available to re-enrolling students.
- BP004 Bachelor of Science
- BH005 Bachelor of Philosophy (Honours)
Overview of unit sequence
The Data Science second major is a single major comprising:
- two Level 1 units
- two Level 2 units
- four Level 3 units
- one Level 1 additional unit
| Key to availability of units: |
|---|
| S1 = Semester 1; S2 = Semester 2; SS = summer teaching period |
Level 1
Take all units (12 points):
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S1, S2 | CITS1401 | Computational Thinking with Python |
|
| S2, SS | CITS1402 | Relational Database Management Systems |
|
Take all additional unit(s) (6 points) (not required for students who have Maths: Methods ATAR or equivalent or higher).
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S1, S2 | MATH1720 | Mathematics Fundamentals |
|
Level 2
Take all units (12 points):
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S2 | CITS2002 | Systems Programming |
|
| S1, S2 | CITS2401 | Computer Analysis and Visualisation |
|
Level 3
Take all units (24 points):
| Availability | Unit code | Unit name | unit requirements |
|---|---|---|---|
| S2 | CITS3200 | Professional Computing | |
| S1 | CITS3401 | Data Warehousing |
|
| S2 | CITS3402 | High Performance Computing |
|
| S1 | CITS3403 | Agile Web Development |
|
Choosing a second major
The flexible structure of an undergraduate course allows you the option of including a second major. You have the choice to either nominate your second major when you first enrol in the course or delay it until your second year. For a major to be recorded on your academic record it must be nominated before the requirements of the course are completed.
To fully understand the structure of an undergraduate course, read the course structure information and the Undergraduate Degree Course Rules.
The following example illustrates how Data Science can be included as a second major in an undergraduate degree course.
For more examples of combinations of majors, search the study plans .
Data Science can also be taken as a degree-specific major.