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
  • two Level 2 complementary units
Key to availability of units:
S1 = Semester 1; S2 = Semester 2; SS = summer teaching period

Level 1

Degree-specific major units
Take all units (12 points):
Availability Unit code Unit name unit requirements
S1, S2 CITS1401 Problem Solving and Programming
Prerequisites:
Mathematics Applications ATAR
or
WACE Mathematics 2C/2D
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
S2, SS CITS1402 Relational Database Management Systems
Prerequisites:
Mathematics Applications ATAR
or
WACE Mathematics 2C/2D
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
CITS2232 Databases
Complementary units
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
Incompatibility:
ATAR Mathematics Methods; WACE Mathematics 3A/3B; MATH0700 Preparatory Mathematics; ECON1111 Quantitative Methods for Business and Economics;
or
equivalent
or
higher
S1, S2 STAT1400 Statistics for Science
Prerequisites:
Mathematics Applications ATAR
or
Mathematics Methods ATAR
or
WACE Mathematics 2C/2D
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
STAT1510 Statistics A, STAT1520 Economic and Business Statistics

Level 2

Degree-specific major units
Take all units (12 points):
Availability Unit code Unit name unit requirements
S2 CITS2002 Systems Programming
Incompatibility:
CITS1210 C Programming, CITS2230 Operating Systems, CITS1002 Programming and Systems
S1, S2, SS CITS2401 Computer Analysis and Visualisation
Prerequisites:
Mathematics Methods ATAR
or
WACE Mathematics 3A/3B
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Complementary units
Take all complementary units (12 points):
Availability Unit code Unit name unit requirements
S1, S2 ENSC2011 Global Challenges in Engineering
Incompatibility:
ENSC1001 Global Challenges in Engineering
S1 STAT2401 Analysis of Experiments
Prerequisites:
STAT1400 Statistics for Science
or
STAT1520 Economic and Business Statistics
or
MATH1002 Mathematical Methods 2
or
MATH1012 Mathematical Theory and Methods
or
MATH1020 Calculus, Probability and Statistics (students enrolled in the Master of Data Science may take one of these units as a co-requisite)
Incompatibility:
STAT2227 Applied Linear Modelling

Level 3

Degree-specific major units
Take all units (24 points):
Availability Unit code Unit name unit requirements
S2 CITS3200 Professional Computing
Prerequisites:
completion of 12 points from: CITS2002 Systems Programming; CITS2200 Data Structure and Algorithms;
or
CITS2401 Computer Analysis and Visualisation
S1 CITS3401 Data Warehousing
Prerequisites:
CITS1402 Relational Database Management Systems (formerly CITS1402 Introduction to Databases)
or
CITS2232 Databases; for pre-2012 courses: CITS1402 Relational Database Management Systems (formerly CITS1402 Introduction to Databases)
or
CITS2232 Databases
Incompatibility:
CITS4243 Advanced Databases
S2 CITS3402 High Performance Computing
Prerequisites:
CITS1002 Programming and Systems
or
CITS2002 Programming and Systems
S1 CITS3403 Agile Web Development
Prerequisites:
CITS1401 Problem Solving and Programming
or
CITS1001 Object-oriented Programming and Software Engineering
or
CITS2002 Systems Programming
or
CITS1002 Programming and Systems; for pre-2012 courses: one of CITS1200 Java Programming
or
CITS1001 Object-oriented Programming and Software Engineering
or
CITS1210 C Programming
or
CITS1002 Programming and Systems
or
CITS2002 Systems Programming
or
CITS1220 Software Engineering
Incompatibility:
CITS4230 Internet Technologies

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.

Example: Course Study Plan: CSP004-DATSC

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.

Example: Course Study Plan: CSP004-DATSC-Generic

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:

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

Second major units
Take all units (12 points):
Availability Unit code Unit name unit requirements
S1, S2 CITS1401 Problem Solving and Programming
Prerequisites:
Mathematics Applications ATAR
or
WACE Mathematics 2C/2D
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
S2, SS CITS1402 Relational Database Management Systems
Prerequisites:
Mathematics Applications ATAR
or
WACE Mathematics 2C/2D
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
CITS2232 Databases
Second major units
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
Incompatibility:
ATAR Mathematics Methods; WACE Mathematics 3A/3B; MATH0700 Preparatory Mathematics; ECON1111 Quantitative Methods for Business and Economics;
or
equivalent
or
higher

Level 2

Second major units
Take all units (12 points):
Availability Unit code Unit name unit requirements
S2 CITS2002 Systems Programming
Incompatibility:
CITS1210 C Programming, CITS2230 Operating Systems, CITS1002 Programming and Systems
S1, S2, SS CITS2401 Computer Analysis and Visualisation
Prerequisites:
Mathematics Methods ATAR
or
WACE Mathematics 3A/3B
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher

Level 3

Second major units
Take all units (24 points):
Availability Unit code Unit name unit requirements
S2 CITS3200 Professional Computing
Prerequisites:
completion of 12 points from: CITS2002 Systems Programming; CITS2200 Data Structure and Algorithms;
or
CITS2401 Computer Analysis and Visualisation
S1 CITS3401 Data Warehousing
Prerequisites:
CITS1402 Relational Database Management Systems (formerly CITS1402 Introduction to Databases)
or
CITS2232 Databases; for pre-2012 courses: CITS1402 Relational Database Management Systems (formerly CITS1402 Introduction to Databases)
or
CITS2232 Databases
Incompatibility:
CITS4243 Advanced Databases
S2 CITS3402 High Performance Computing
Prerequisites:
CITS1002 Programming and Systems
or
CITS2002 Programming and Systems
S1 CITS3403 Agile Web Development
Prerequisites:
CITS1401 Problem Solving and Programming
or
CITS1001 Object-oriented Programming and Software Engineering
or
CITS2002 Systems Programming
or
CITS1002 Programming and Systems; for pre-2012 courses: one of CITS1200 Java Programming
or
CITS1001 Object-oriented Programming and Software Engineering
or
CITS1210 C Programming
or
CITS1002 Programming and Systems
or
CITS2002 Systems Programming
or
CITS1220 Software Engineering
Incompatibility:
CITS4230 Internet Technologies

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.

Example: Course Study Plan: CSPGeneric-DSMGeneric-DATSC

For more examples of combinations of majors, search the study plans .

Data Science can also be taken as a degree-specific major.