Bachelor of Applied Data Analytics (BAppDataAn)

Program Code


Academic Year


Special Notes

These Program Rules should be read in conjunction with the University's policies (


This program provides students with discipline-specific knowledge and data analytics skills. Students will have a major in one discipline of either economics, public health or science coupled with skills in statistics, programing, data management, visualization, communication, and ethics. Students are encouraged to undertake internships, and overseas study tours, and are eligible to be part of the University of Adelaide Deloitte Academy program. In the final year of the program, students undertake a project that allows them to apply their knowledge and skills in their chosen discipline using real-world examples and with industry and government.
The Bachelor of Applied Data Analytics is an AQF Level 7 program with a standard full-time duration of 3 years.

Program Learning Outcome
1. Demonstrate a coherent understanding of the discipline and decision science by: 1.1 articulating deep knowledge of the discipline 1.2 explaining the role and relevance of the discipline and the application of data analysis to decision science in society.
2. Exhibit depth and breadth of big data analytics knowledge and decision science by: 2.1 understanding the value of data to the discipline 2.2 understanding the statistical and numerical approaches to interpreting discipline data 2.3 being aware of the need to use data in decision-making responsibly and ethically.
3. Critically analyse and solve discipline-based big-data problems by: 3.1 designing and planning an investigation 3.2 selecting and applying techniques to conduct an investigation 3.3 gathering, synthesising and critically evaluating information from a range of sources to apply in decision-making processes.
4. Be effective communicators of big data (and its analysis) within the cognate discipline by communicating results, information, or arguments, to a range of audiences, for a range of purposes, and using a variety of modes.
5. Be accountable for their own learning and professional work by: 5.1 being independent and self-directed learners 5.2 working effectively, responsibly and safely in an individual or team context 5.3 demonstrating knowledge of the regulatory frameworks relevant to their disciplinary area and personally practicing ethical conduct 5.4 demonstrating and articulating personal capabilities in preparation for employment.

Interruption of program: Students must apply for permission from the Executive Dean or delegate before taking a Leave of Absence. Any extension of the leave without approval will result in the loss of place in the program but an application may be made to be re-admitted to the program subject to the admission procedures in place at the time.

Program Maximum Duration: As specified in Table 1 of the Coursework Academic Programs Policy, this program must be completed within a Maximum Duration which includes any periods of non-enrolment, leave of absence or approved study at other institutions for credit towards a Program.

Academic Program Rules for Bachelor of Applied Data Analytics

There shall be a Bachelor of Applied Data Analytics.

Qualification Requirements
Academic Program: 

To qualify for the degree of Bachelor of Applied Data Analytics, the student must complete satisfactorily a program of study consisting of the following requirements with a combined total of not less than 72 units:

  1. Core courses to the value of 30 units including a capstone project to the value of 3 units.
  2. One major of at least 27 units chosen from the following:
    • Agriculture
    • Bioinformatics
    • Economics
    • Environment
    • Geosciences
    • Physics
    • Public health
  3. Electives, inclusive of Broadening Electives, to the value of up to 15 units.
  4. Level I courses to a maximum of 30 units.
  5. Level III Science courses to the value of at least 24 units.
Core Courses

To satisfy the requirements for Core Courses students must complete courses to the value of 30 units.

Level I

All of the following courses must be completed:

Subject / Catalogue Course Title Unit Value
APP DATA 1010 Ethics and Data Management I 3
SCIENCE 1500 Introductory Data Science - Becoming Smart About Data 3


Courses to the value of 3 units from the following:

Subject / Catalogue Course Title Unit Value
ECON 1008 Data Analytics I 3
STATS 1000 Statistical Practice I 3
STATS 1005 Statistical Analysis and Modelling I 3

Level II

All of the following courses must be completed:

Subject / Catalogue Course Title Unit Value
APP DATA 2010 Data Handling and Visualisation II 3
APP DATA 2015 Data Taming and Prediction 3
APP DATA 2020 Programming II 3
STATS 2107 Statistical Modelling and Inference II 3

Level III

All of the following courses must be completed:


Subject / Catalogue Course Title Unit Value
APP DATA 3020 Capstone Project in Applied Data Analytics III 3


All of the following courses must be completed:

Subject / Catalogue Course Title Unit Value
STATS 3001 Statistical Modelling III 3
STATS 3022 Data Science III 3