MN50752: Data mining & machine learning
[Page last updated: 15 October 2020]
![]() | 2020/1 |
![]() | School of Management |
![]() | 10 [equivalent to 20 CATS credits] |
![]() | 200 |
![]() | Masters UG & PG (FHEQ level 7) |
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![]() | CW 100% |
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Description: | Aims: This unit will enable you to build on the skills and knowledge from unit 'Databases & Business Intelligence' and will teach you how to discover patterns in data (e.g. customer profiles of a retailer) using algorithms, as well as how to apply machine learning methods to pattern recognition problems. Learning Outcomes: * Choose appropriate algorithms to detect previously unknown rules and patterns within data and infer their business implications [CILO:K1, K3] * Measure the accuracy and precision of the rules and patterns detected [CILO:I1] * Model business challenges as data mining and machine learning models [CILO:I3, P4] * Apply ethical principles in the collection, conversion and analysis of data [CILO:I4, K5] * Use state-of-the-art data mining software [CILO:P2]. Skills: See LO Section. Content: Topics covered include Clustering , Pattern Recognition, and Classification Methods. |
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MN50752 is Compulsory on the following programmes:School of Management
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