Bachelor of Applied Data Analytics (BAppDataAn)

Program Code

BAPDA

Academic Year

2022

Program Faculty

Faculty of Sciences

Special Notes

These Program Rules should be read in conjunction with the University's policies (http://www.adelaide.edu.au/policies).

Overview

This program will provide students with the practical skills and knowledge to work in roles that are responsible for communication and application of data analytics to decision-making processes to provide discipline-specific solutions. Students have the opportunity to focus on more or less quantitative forms of big data analytics in a transdisciplinary setting that focuses on data literacy, ethical data management, data handling and visualization, data analysis, machine learning and decision-making processes within the chosen discipline. In the final year of the program, students undertake a project that allows them to apply their knowledge and skills to that discipline.
 
The Bachelor of Applied Data Analytics is an AQF Level 7 program with a standard full-time duration of 3 years.

Conditions

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.

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 24 units in applied data analytics within their chosen stream including a capstone project course worth 3 units
  2. One major chosen from the following:
    • Agriculture
    • Bioinformatics
    • Environment
    • Economics
    • Geosciences
    • Physics
    • Public health
  3. Electives based on the chosen major
Core Courses

To satisfy the requirements for Core Courses students must complete courses to the value of 24 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

and

Courses to the value of 3 units from the following:

Subject / Catalogue Course Title Unit Value
MATHS 1004 Mathematics for Data Science I 3
MATHS 1012 Mathematics IB 3

and

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

and

Courses to the value of 3 units from the following:

for the more quantitative stream

Subject / Catalogue Course Title Unit Value
APP DATA 2015 Statistical Inference and Machine Learning II 3

or

Subject / Catalogue Course Title Unit Value
APP DATA 3035 Statistical Inference and Machine Learning III 3

or

for the less quantitative stream

Subject / Catalogue Course Title Unit Value
APP DATA 2020 Programming 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

and

Courses to the value of 3 units from the following:

for the more quantitative stream

Subject / Catalogue Course Title Unit Value
APP DATA 3010 Advanced Data Analysis III 3
APP DATA 3015 Numerical Modelling III 3

or

for the less quantitative stream

Subject / Catalogue Course Title Unit Value
APP DATA 3025 Machine Learning and Data Analytics III 3
APP DATA 3030 Quantitative Decision Making III 3