University of Technology Sydney

26811 Data, Algorithms and Meaning

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2022 is available in the Archives.

UTS: Business
Credit points: 3 cp

Subject level:


Result type: Grade and marks

There are course requisites for this subject. See access conditions.


This subject introduces candidates to key machine learning algorithms and their application in real-world settings. Participants develop an understanding of big data, how algorithms work, as well as the strengths and weaknesses of big data and algorithms in the context of specific applications. Since data science problems are infused with assumptions, often with ethical and legal implications, due attention is given to questioning the assumptions behind data and approaches used to analyse it. Candidates explore ethical implications in relation to the use of machine learning algorithms and develop options on how to navigate ethical issues.