Bachelor of Applied Data Analytics
Australian National University
About
The Bachelor of Applied Data Analytics is a three year full-time (or equivalent part-time) inter-disciplinary degree that is designed to address a global shortage of graduates with skills in data analytics as applied to high-quality, data-informed decision-making.
It is designed to develop inter-disciplinary knowledge across the three base disciplines of computing, statistics and social science.
You will receive exposure to best practice in data analytics as well as an opportunity to acquire knowledge in a discipline that relies on data analytics, or deepen knowledge in one of computation, statistics, or social science.
Structure
Program Requirements
The Bachelor of Applied Data Analytics requires the completion of 144 units, of which:
A maximum of 60 units may come from completion of 1000-level courses
The 144 units must consist of:
60 units from completion of the following compulsory courses
COMP2400 Relational Databases
COMP3425 Data Mining
COMP3430 Data Wrangling
DEMO2002 Population Analysis
SOCR1001 Foundations of Social Research
SOCY2169 Online Research Methods
SOCY2166 Social Science of the Internet
SOCR3001 Data for Decision Making
STAT3011 Graphical Data Analysis
STAT3040 Statistical Learning
6 units from completion of courses from the following list:
COMP1100 Programming as Problem Solving
COMP1130 Programming as Problem Solving (Advanced)
COMP1730 Programming for Scientists
6 units from completion of courses from the following list:
COMP1110 Structured Programming
COMP1140 Structured Programming (Advanced)
6 units from completion of courses from the following list:
STAT2001 - Introductory Mathematical Statistics
MATH1115 - Advanced Mathematics and Applications 1
STAT2013 - Introductory Mathematical Statistics for Actuarial Studies
6 units from completion of courses from the following list:
STAT2008 - Regression Modelling
STAT2014 - Regression Modelling for Actuarial Studies
Either:
6 units from completion of MATH1113 Mathematical Foundations for Actuarial Studies
6 units from completion of courses from the following list:
STAT1003 Statistical Techniques
STAT1008 Quantitative Research Methods
Or:
12 units from completion of the following courses:
MATH1003 Algebra and Calculus Methods
MATH1113 Mathematical Foundations for Actuarial Studies
Or:
12 units from completion of the following courses:
MATH1013 Mathematics and Applications 1
MATH1014 Mathematics and Applications 2
MATH1115 Advanced Mathematics and Applications 1
MATH1116 Advanced Mathematics and Applications 2
48 units from completion of elective courses offered by ANU
Elective Study
Once you have met the program requirements of your degree, you may have enough electives to complete an additional elective major, minor or specialisation.
Study Options
Year 1 - 48 units
Code | Name | Units |
---|---|---|
COMP1100 | Programming as Problem Solving | 6 units |
MATH1013 | Mathematics and Applications 1 | 6 units |
Elective | 6 units | |
Elective | 6 units | |
COMP1110 | Structured Programming | 6 units |
COMP2400 | Relational Databases | 6 units |
SOCR1001 | Foundations of Social Research | 6 units |
MATH1014 | Mathematics and Applications 2 | 6 units |
Year 2 - 48 units
Code | Name | Units |
---|---|---|
COMP3425 | Data Mining | 6 units |
STAT2008 | Regression Modelling | 6 units |
DEMO2002 | Population Analysis | 6 units |
Elective | 6 units | |
COMP3430 | Data Wrangling | 6 units |
STAT2001 | Introductory Mathematical Statistics | 6 units |
SOCY2169 | Online Research Methods | 6 units |
Elective | 6 units |
Year 3 - 48 units
Code | Name | Units |
---|---|---|
SOCY2166 | Social Science of the Internet | 6 units |
STAT3040 | Statistical Learning | 6 units |
Elective | 6 units | |
Elective | 6 units | |
STAT3011 | Graphical Data Analysis | 6 units |
SOCR3001 | Data for Decision Making | 6 units |
Elective | 6 units | |
Elective | 6 units |
Entry requirements
Admission Requirements
At a minimum, all applicants must meet program-specific academic/non-academic requirements, and English language requirements. Admission to most ANU programs is on a competitive basis. Therefore, meeting all admission requirements does not automatically guarantee entry.
In line with the university's admissions policy and strategic plan, an assessment for admission may include competitively ranking applicants on the basis of specific academic achievement, English language proficiency and diversity factors.
Domestic applicants
? School leavers will be assessed on:
• the minimum Australian Tertiary Admission Rank (ATAR) requirement or equivalent for this program,
• the co-curricular or service requirement, and
• any program specific requirements that are listed below.
? Non school leavers:
a) will be assessed on:
• the minimum Australian Tertiary Admission Rank (ATAR) requirement or equivalent for this program,
b) Non school leavers who:
• complete a recognised Australian (or equivalent) post-secondary qualification, or
• complete one standard full-time year (1.0 FTE) of an Australian (or equivalent) degree qualification, or
• complete an approved tertiary preparation course/program without undertaking any further study,
will be assessed on the basis of an equivalent selection rank that is calculated upon application. Non school leavers must also meet any program specific requirements that are listed below.
International applicants
Applicants who complete a recognised secondary/senior secondary/post-secondary/tertiary sequence of study will be assessed on the basis of an equivalent selection rank that is calculated upon application. A list of commonly observed international qualifications and corresponding admission requirements can be found here. Applicants must also meet any program specific requirements that are listed below.
Diversity factors & English language proficiency
As Australia's national university, ANU is global representative of Australian research and education. ANU endeavours to recruit and maintain a diverse and deliberate student cohort representative not only of Australia, but the world. In order to achieve these outcomes, competitive ranking of applicants may be adjusted to ensure access to ANU is a reality for brilliant students from countries across the globe. If required, competitive ranking may further be confirmed on the basis of demonstrating higher-level English language proficiency.
Prerequisites
There are no formal program prerequisites. But assumed knowledge is:-ACT: Mathematical Methods (Major)/Further Mathematics/Specialist Mathematics (major)/Specialist Methods or NSW: Mathematics or equivalent. More information about interstate subject equivalencies can be found here.
Adjustment Factors
ANU offers rank adjustments for a number of adjustment factors, including for high achievement in nationally strategic senior secondary subjects and for recognition of difficult circumstances that students face in their studies. Rank adjustments are applied to Bachelor degree applicants with an ATAR at or above 70. Points are awarded in accordance with the approved schedules, and no more than 15 points (maximum 5 subject/performance-based adjustments, maximum 10 equity-based adjustments and maximum 5 Elite Athlete adjustments) will be awarded. Please note that Adjustment Factors vary and do not apply to a select few programs, please visit the ANU Adjustment Factors website for further information.
Scholarships
ANU offers a wide range of scholarships to students to assist with the cost of their studies.
Eligibility to apply for ANU scholarships varies depending on the specifics of the scholarship and can be categorised by the type of student you are. Specific scholarship application process information is included in the relevant scholarship listing.
For further information see the Scholarships website.
Learning outcomes
- Select, adapt, apply, and communicate advanced data analytics methods and techniques;
- Apply data analytics to decision making about policy, business and service delivery;
- Examine current issues in data analytics using leading-edge research and practices in the field;
- Demonstrate strong cognitive, technical, and communication skills to work independently and collaboratively to collect, process, interpret and communicate the outcomes of data analytics problems; and
- Communicate complex data analytics outcomes to diverse audiences.
Institution
