The aim of this unit is to provide students with the foundation knowledge and understanding of Machine Learning and its applications in various domains including computer vision, data analytics and text mining. This unit will equip students with essential knowledge that is needed for developing smart software applications by using machine learning algorithms and tools.
|Unit name||Machine Learning and Applications|
|Faculty/School||College of Sciences and Engineering
School of Information and Communication Technology
|Discipline||Information & Communication Technology|
|Available as student elective?||Yes|
|Location||Study period||Attendance options||Available to|
- International students
- Domestic students
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|Study Period||Start date||Census date||WW date||End date|
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (see withdrawal dates explained for more information).
Explain concepts of different categories of machine learning methods
Apply suitable tools and techniques to develop machine learning methods to solve practical problems.
Evaluate machine learning solutions toward characteristics of practical problems
|Field of Education||Commencing Student Contribution 1||Grandfathered Student Contribution 1||Approved Pathway Course Student Contribution 2||Domestic Full Fee|
1 Please refer here more information on student contribution amounts.
2 Information on eligibility and Approved Pathway courses can be found here
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to this page to get an indicative course cost.
KIT205 or KIT206
2-hour lecture weekly, 2-hour tutorial weekly
AT1 - Assignment 40%
AT2 - Report 30%
AT3 - Workshop (regular lab exercises) 30%
|Timetable||View the lecture timetable | View the full unit timetable|
|Links||Booktopia textbook finder|
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