Note: This unit will only have online classes in 2022. All lectures and tutorials will be available online only.
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|
|College/School||College of Sciences and Engineering
School of Information and Communication Technology
|Discipline||Information & Communication Technology|
|Coordinator||Professor Byeong Kang|
|Available as student elective?||Yes|
|Delivered By||University of Tasmania|
|Location||Study period||Attendance options||Available to|
- International students
- Domestic students
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Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.
|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 (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2022 are indicative and subject to change. Finalised census dates for 2022 will be available from the 1st October 2021. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
- 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 to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
PrerequisitesKIT205 OR KIT206
On Campus: 2-hour lecture weekly, 2-hour tutorial weekly
|Assessment||Assignment 1 (40%)|Assignment 2 (30%)|Workshop Exercises (30%)|
|Timetable||View the lecture timetable | View the full unit timetable|
Required readings will be listed in the unit outline prior to the start of classes.
|Links||Booktopia textbook finder|
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