MN50752: Data mining & machine learning
[Page last updated: 05 August 2021]
| Academic Year: | 2021/2 |
| Owning Department/School: | School of Management |
| Credits: | 10 [equivalent to 20 CATS credits] |
| Notional Study Hours: | 200 |
| Level: | Masters UG & PG (FHEQ level 7) |
| Period: |
|
| Assessment Summary: | CW 80%, EX 20% |
| Assessment Detail: |
|
| Supplementary Assessment: |
|
| Requisites: | |
| 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. |
| Programme availability: |
MN50752 is Compulsory on the following programmes:School of Management
|
Notes:
|