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Unit of Study AIT91001 - Computational Intelligence and Machine Learning (2019)
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Unit Snapshot
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Unit typeo
PG Coursework Unit
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Credit points
12
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AQF level
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Level of learning
Introductory
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Former School/College
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Pre-requisites
- CSC72003 - Programming II OR
- CSC81002 - Fundamentals of Programming unless one of these units has been approved for advanced standing.
Learning outcomes and graduate attributes
Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.
On completion of this unit, students should be able to:
GA1 | GA2 | GA3 | GA4 | GA5 | GA6 | GA7 | ||
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1 | identify and evaluate the evolution and recent trends in computational intelligence and machine learning | |||||||
2 | critically analyse real-world machine learning problems and compare between a range of solutions in a variety of contexts | |||||||
3 | develop, create and implement machine learning solutions to complicated problems | |||||||
4 | plan and implement parts of the tasks in a machine learning pipeline to complete a predictive analysis problem to satisfaction |
On completion of this unit, students should be able to:
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identify and evaluate the evolution and recent trends in computational intelligence and machine learning
- GA4:
- GA5:
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critically analyse real-world machine learning problems and compare between a range of solutions in a variety of contexts
- GA2:
- GA4:
- GA5:
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develop, create and implement machine learning solutions to complicated problems
- GA2:
- GA4:
-
plan and implement parts of the tasks in a machine learning pipeline to complete a predictive analysis problem to satisfaction
- GA2:
- GA4:
Prescribed learning resources
Prescribed Texts
- No prescribed texts.
Prescribed Learning Resources may change in future Teaching Periods.