Computing and Data Science major

Organisations across all industries and sectors are increasingly using data science in information analysis, storage, communication and distribution. In the Bachelor of Advanced Computer Science (Computing and Data Science) you will acquire the computing and data science knowledge and skills to understand and apply appropriate analytical methods to transform the way an organisation achieves its 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; putting you in high demand in the growing data science job market and providing you with many diverse career options as a graduate. This major will prepare you with practical skills in data science technologies for data collection, cleaning, conversion, analysis, visualisation, interpretation, storage, search, synthesis and cloud management.

Outcomes

Students are able to (1) apply data visualisation, interpretation, storage and synthesis skills in complex real-world settings; (2) use predictive modelling to forecast future trends, outcomes and scenarios; (3) discuss the opportunities and constraints of contemporary data science practice as it applies in various industries; (4) work effectively as a team member and as a team leader for real-world data science projects; (5) communicate data science, modelling and analytics clearly in oral, graphical and written formats; and (6) extend knowledge in data science through research, experimentation and analysis.

Broadening guidelines

All students studying towards a Bachelor's Degree at UWA are required to Broaden their studies by completing a minimum of four units (24 points) of study outside their degree specific major. Broadening is your opportunity to explore other areas of interest, investigate new disciplines and knowledge paradigms and to shape your degree to suit your own aspirations and interests. Many of you will be able to undertake more than this minimum amount of broadening study and we encourage you to do so if this suits your aspirations. Over the next few months you will find here some broadening suggestions related to your degree-specific major. While we know that many students value guidance of this sort, these are only suggestions and students should not lose sight of the opportunity to explore that is afforded by your Broadening Choices. Advice can also be sought from your Allocated Student Advising Office.

Prerequisites

Mathematics Methods ATAR

Computing and Data Science can only be taken as a degree-specific major in the following degree courses:

BH008 Bachelor of Advanced Computer Science [Honours]
BH005 Bachelor of Philosophy (Honours)

Overview of unit sequence

Computing and Data Science is a degree-specific double major comprising:

  • six Level 1 units
  • five Level 2 units
  • seven Level 3 units
  • six Level 2 complementary units
Key to availability of units:
S1 = Semester 1; S2 = Semester 2; N/A = not available in 2021

Note: Units that are indicated as N/A may be available in 2022 or 2023.

Level 1

Degree-specific major units
Take all units (36 points):

Students are recommended to take MATH1722 Mathematics Foundations: Specialist as an elective.

Availability Unit code Unit name unit requirements
S1, S2 CITS1001 Software Engineering with Java
Prerequisites:
Mathematics Applications ATAR
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
CITS1200 Java Programming, CITS1220 Software Engineering
S2 CITS1003 Introduction to Cybersecurity
Incompatibility:
CITS3004 Cybersecurity (ID 6150)
S1, S2 CITS1401 Computational Thinking with Python
Prerequisites:
Mathematics Applications ATAR
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
S2 CITS1402 Relational Database Management Systems
Prerequisites:
Mathematics Applications ATAR
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
CITS2232 Databases
S1 PHIL1001 Ethics for the Digital Age: An Introduction to Moral Philosophy
Incompatibility:
PHIL1107 Ethics, Free Will and Meaning
S1, S2 STAT1400 Statistics for Science
Prerequisites:
Mathematics Applications ATAR
or
MATH1720 Mathematics Fundamentals
or
equivalent
or
higher
Incompatibility:
STAT1520 Economic and Business Statistics

Level 2

Degree-specific major units
Take all units (30 points):
Availability Unit code Unit name unit requirements
S2 CITS2002 Systems Programming
Prerequisites:
Mathematics Methods ATAR
or
MATH1721 Mathematics Foundations: Methods
Incompatibility:
CITS1210 C Programming, CITS2230 Operating Systems, CITS1002 Programming and Systems
S1 CITS2200 Data Structures and Algorithms
Prerequisites:
CITS1001 Software Engineering with Java and (Mathematics Methods ATAR
or
MATH1721 Mathematics Foundations: Methods
or
equivalent
or
higher)
S2 CITS2402 Introduction to Data Science
Prerequisites:
CITS1401 Computational Thinking with Python
or
CITS2401 Computer Analysis and Visualisation
S1 STAT2401 Analysis of Experiments
S2 STAT2402 Analysis of Observations

Level 3

Degree-specific major units
Take all units (42 points):
Availability Unit code Unit name unit requirements
S2 CITS3001 Algorithms, Agents and Artificial Intelligence
Prerequisites:
CITS2200 Data Structures and Algorithms
S1 CITS3002 Computer Networks
Prerequisites:
CITS1002 Programming and Systems
or
CITS2002 Programming and Systems
Incompatibility:
CITS3230 Computer Networks, CITS3231 Security and Privacy
S2 CITS3200 Professional Computing
Prerequisites:
enrolment in one of the following majors: MJD-ARIDM Artificial Intelligence; MJD-CMPSC Computer Science; MJD-CDSDM Computing and Data Science; MJD-CYBER Cybersecurity; MJD-DATSC Data Science; MJD-ENGSC Engineering Science (Software Engineering); MJD-ICYDM International Cybersecurity and completion of at least 84 points, including (CITS1401 Computational Thinking with Python (ID 411)
or
CITS1001 Software Engineering with Java (ID 296)) and (CITS2002 Systems Programming (ID 4722)
or
CITS2200 Data Structures and Algorithms (ID 300)
or
CITS2402 Introduction to Data Science (ID 7427))
S1 CITS3401 Data Warehousing
Prerequisites:
CITS1402 Relational Database Management Systems
Incompatibility:
CITS5504 Data Warehousing (ID 5245)
S1 CITS3403 Agile Web Development
Prerequisites:
CITS1001 Software Engineering with Java (ID 296)
or
CITS1401 Computational Thinking with Python (ID 411)
or
CITS2002 Systems Programming (ID 4722)
or
equivalent
Incompatibility:
CITS4230 Internet Technologies
S2 STAT3064 Statistical Learning
Prerequisites:
(STAT2401 Analysis of Experiments
or
STAT2062 Fundamentals of Probability with Applications) and (MATH1720 Mathematics Fundamentals (ID 5107)
or
MATH1012 Mathematical Theory and Methods (ID 6013))
N/A STAT3401 Advanced Data Analysis
Prerequisites:
(STAT2401 Analysis of Experiments and STAT2402 Analysis of Observations)
or
STAT3405 Introduction to Bayesian Computing and Statistics
Incompatibility:
STAT4065 Multilevel and Mixed-Effects Modelling (ID 6203)

Level 4

Degree-specific major units
Take all units (48 points):
Availability Unit code Unit name unit requirements
N/A CITS4010 Computer Science Honours Research Project Part 1
Prerequisites:
enrolment in the Bachelor of Advanced Computer Science [Honours]
N/A CITS4011 Computer Science Honours Research Project Part 2
Prerequisites:
CITS4010 Computer Science Honours Research Project Part 1
S2 CITS5503 Cloud Computing
Prerequisites:
enrolment in the BH008 Bachelor of Advanced Computer Science [Honours] (International Cybersecurity major
or
Computing and Data Science major)
or
HON-CMSSE Computer Science and Software Engineering
or
62510 Master of Information Technology
or
62530 Master of Data Science
or
62550 Master of Professional Engineering (Software Engineering)
or
42630 Master of Business Analytics and completion of 12 points of programming-based units
S1 CITS5508 Machine Learning
Prerequisites:
enrolment in the BH008 Bachelor of Advanced Computer Science [Honours] (Artificial Intelligence major
or
Computing and Data Science major)
or
HON-CMSSE Computer Science and Software Engineering
or
62510 Master of Information Technology
or
62530 Master of Data Science
or
62550 Master of Professional Engineering (Software Engineering)
or
42630 Master of Business Analytics and completion of 12 points of programming-based units
S1 STAT4062 Statistical Modelling and Inference
Prerequisites:
STAT3061 Random Processes and their Applications (ID 371)
or
STAT3401 Advanced Data Analysis (ID 394)
S1 STAT4066 Bayesian Computing and Statistics
Prerequisites:
STAT1400 Statistics for Science
or
STAT1520 Economic and Business Statistics
or
MATH1012 Mathematical Theory and Methods
or
STAT2401 Analysis of Experiments (ID 390)
or
STAT2402 Analysis of Observations (ID 389)
Incompatibility:
STAT3405 Introduction to Bayesian Computing and Statistics

Choosing your degree-specific major

Specialised degrees – Bachelor of Advanced Computer Science (Honours), Bachelor of Automation and Robotics, Bachelor of Environmental Design, Bachelor of Music

You must satisfy the requirements of the degree-specific major in your degree before you complete your course.

Bachelor of Philosophy, Politics and Economics

This comprehensive degree does not allow you to choose a double major.

General degrees

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 Computing and Data Science degree-specific major can be included in the Bachelor of Advanced Computer Science [Honours] course.

Example 1:
Course Study Plan: CSPH008-CDSDM

There are more choices open to you. For more examples, search the study plans .