Machine Learning and Applications unit (KXO220)

Introduction

In this unit, you will learn the basic knowledge and understanding of machine learning and deep learning, along with their use in areas such as computer vision, data analytics, and text mining. You will build key skills to prepare and analyse data, train and evaluate models, and apply suitable machine learning algorithms and tools to solve different problems.

Summary

Unit name	Machine Learning and Applications
Unit code	KXO220
Credit points	12.5
College/School	Sciences and Engineering School of Information and Communication Technology
Discipline	Information & Communication Technology
Coordinator	Doctor Wenli Yang
Available as an elective?	No
Delivered By	University of Tasmania
Level	Intermediate

Learning Outcomes

• Understand the concepts of different categories of machine learning and deep learning methods.
• Apply suitable algorithms and tools to solve different problems.
• Prepare and analyse data, build and evaluate models, and assess solutions for practical problems.

Fee Information

Field of Education	Commencing Student Contribution 1,3	Grandfathered Student Contribution 1,3	Approved Pathway Course Student Contribution 2,3	Domestic Full Fee 4
			not applicable

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.

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Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.

Requisites

Prerequisites

KIT101 OR KIT108

Teaching

Teaching Pattern	On-Campus enrolments in Shanghai: Self-Study (online): 2hr/week Workshop (online): 2hr/week Tutorials (in the computer lab): 2 hr/week. For this unit, on-campus students are expected to attend face-to-face lab classes.
Assessment	Lab Exercises (30%)|Lab Test (30%)|Assignment 2 (40%)
Timetable	View the lecture timetable | View the full unit timetable

Textbooks

Required	Required readings will be listed in the unit outline prior to the start of classes.

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