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2023 unit information
Nil
Students will on average spend 150 hours over the trimester period undertaking the teaching, learning and assessment activities.
1 x 1.5 hour class and 1 x 1.5 hour seminar per week
1 x 1.5 hour recorded class and 1 x 1.5 hour online seminar per week
Machine Learning allows computers to learn from hidden patterns in big data to quantitatively support business decisions. In this unit, we will cover a large range of methods and algorithms that learn from big data, allowing decision makers to view previously hidden patterns and relationships and build suitable models to support business decision making.
In this unit, students will be introduced to fundamental programming concepts required by business professionals to work with machine learning concepts. This unit introduces machine learning techniques using software package Python, where the emphasis will be on solving business problems using the analysis of business data.
GLO1: Discipline-specific knowledge and capabilities
GLO3: Digital Literacy
GLO5: Problem solving
Assessment 2:
Part A: Case study (Report)
Part B: Report (Business)
Part A: 2000 words
Part B: 1000 words
Total 60%:
Part A: 40%
Part B: 20%
The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.
The texts and reading list for the unit can be found on the University Library via the link below: https://deakin.rl.talis.com/modules/MIS710.html Note: Select the relevant trimester reading list. Please note that a future teaching period's reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester's prior year reading list as a guide only.
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