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Unit of Study ISY10056 - Intelligent Decision Systems (2015)
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Unit Snapshot
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Unit type
UG Coursework Unit
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Credit points
12
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AQF level
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Level of learning
Advanced
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Former School/College
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Pre-requisites
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Anti-requisites
CSC00236 Artificial Intelligence
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Enrolment information
N/A
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:
Learning outcome count | Learning outcome description | GA1 | GA2 | GA3 | GA4 | GA5 | GA6 | GA7 |
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1 | identify and discuss different decision types and the process of decision making and their relevance to decision support | |||||||
2 | describe, discuss and compare the components, characteristics and uses of expert systems, especially the application of knowledge engineering principles to the creation of knowledge bases | |||||||
3 | identify and apply the appropriate technology, development methodology and current tools for both ES and DSS requirements | |||||||
4 | identify and discuss the application of neural networks, fuzzy logic and genetic algorithms to DSS | |||||||
5 | describe, discuss, and compare cutting-edge intelligent technologies and analyse problem situations to recommend which technology (or technologies) are best suited | |||||||
6 | describe and discuss implementation, societal and organisational impacts. |
On completion of this unit, students should be able to:
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identify and discuss different decision types and the process of decision making and their relevance to decision support
- GA1:
- GA4:
- GA5:
-
describe, discuss and compare the components, characteristics and uses of expert systems, especially the application of knowledge engineering principles to the creation of knowledge bases
- GA1:
- GA4:
- GA5:
-
identify and apply the appropriate technology, development methodology and current tools for both ES and DSS requirements
- GA1:
- GA4:
- GA5:
-
identify and discuss the application of neural networks, fuzzy logic and genetic algorithms to DSS
- GA1:
- GA4:
- GA5:
-
describe, discuss, and compare cutting-edge intelligent technologies and analyse problem situations to recommend which technology (or technologies) are best suited
- GA1:
- GA4:
- GA5:
-
describe and discuss implementation, societal and organisational impacts.
- GA1:
- GA4:
- GA5:
- GA7:
Prescribed learning resources
Prescribed Texts
- No prescribed texts.
Prescribed Learning Resources may change in future Teaching Periods.