University of Technology, Sydney

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36106 Data, Algorithms and Meaning

8cp; block mode with weekly online work, 4 Saturday sessions on campus; availability: Master of Data Science and Innovation students only
There are course requisites for this subject. See access conditions.

Requisite elaboration/waiver:

Any student wishing to enrol in first- and second-year subjects concurrently must apply for a waiver.


Postgraduate

Description

This subject introduces students to key machine learning algorithms and their application in real-world settings. Participants are guided in developing an intuitive understanding of how the algorithms work, as well as their strengths and weaknesses. In addition to gaining practical experience with the algorithms, students develop an understanding of the basic principles of machine learning and the connections between different algorithms. Additionally, they are exposed to industry standard methodologies for data mining and analytics via readings and assessments. 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.

Typical availability

Autumn session, City campus


Detailed subject description.

Fee information

Information to assist with determining the applicable fee type can be found at Understanding fees.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.