Applications of Data Science

Postgraduate | 2026

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Mode icon
Mode
Mode
Your study will be 100% online
100% online
area/catalogue icon
Area/Catalogue
INFO 5045
Course ID icon
Course ID
203977
Campus icon
Campus
Online
Level of study
Level of study
Postgraduate
Unit value icon
Unit value
6
Course owner
Course owner
School of Comp Sc & IT
Course level icon
Course level
5
Work Integrated Learning course
Work Integrated Learning course
No
Study abroad and student exchange icon
Inbound study abroad and exchange
Inbound study abroad and exchange
The fee you pay will depend on the number and type of courses you study.
No
University-wide elective icon
University-wide elective course
No
Single course enrollment
Single course enrolment
No

Course overview

A practical introduction to data modelling, analysis and prediction using contemporary software packages. An overview of common techniques and their implementation in software libraries. Selection of tools and techniques that are appropriate for different types and scale of data. Validation and interpretation of process outputs.

Course learning outcomes

  • Generate unsupervised and supervised methods to gain Information to bring about solutions
  • Formulate a range of regression methods as part of supervised learning
  • Formulate a range of classification methods as part of supervised learning
  • Construct tree methods to map non-linear relationships as part of supervised learning
  • Investigate the role of machine learning method in support of all the other techniques

Availability

Census date Icon
Census date
Fri 17/07/2026
Enrol by date
Enrol by date
Fri 26/06/2026
Last day to W
Last day to W
Mon 03/08/2026
Last day to WF
Last day to WF
Mon 17/08/2026

Class details

Online

Class number
Class number 44013
Section
Section 01OL
Size
Size 500
Available
Available 500
Dates Days Time Campus Location Instructor
- Online ,
Notes:
Available to Master of Data Science (Applied) or Graduate Diploma in Data Science (Applied) students only.

Prerequisite(s)

  • must have completed all of COMP5057 Foundations of Computer Science - Python A/COMP6029 OL Human and Ethical Factors in Computer Science/INFO5043 Data Taming, Modelling and Visualisation AND must have completed 1 of INFO5044 Applied Data Science/MATH5023 Applied Data Science and Mathematics

Corequisite(s)

N/A

Antirequisite(s)

  • must not have completed DATA7301OL Applications of Data Science at the University of Adelaide

Assumed knowledge

N/A

Textbook(s)

N/A

Inherent requirements

N/A

Other resources

N/A

Assessment

N/A

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The Student Contribution amount displayed below is for students commencing a new program from 2021 onwards. If you are continuing in a program you commenced prior to 1 January 2021, or are commencing an Honours degree relating to an undergraduate degree you commenced prior to 1 January 2021, you may be charged a different Student Contribution amount from the amount displayed below. Please check the Student Contribution bands for continuing students here. If you are an international student, or a domestic student studying in a full fee paying place, and are continuing study that you commenced in 2025 or earlier, your fees will be available here before enrolments open for 2026.

Degree list
The following degrees include this course
Graduate Diploma in Data Science (Applied)