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MN50752: Data mining & machine learning

[Page last updated: 15 October 2020]

Follow this link for further information on academic years Academic Year: 2020/1
Further information on owning departmentsOwning Department/School: School of Management
Further information on credits Credits: 10      [equivalent to 20 CATS credits]
Further information on notional study hours Notional Study Hours: 200
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 2
Further information on unit assessment Assessment Summary: CW 100%
Further information on unit assessment Assessment Detail:
  • Coursework (CW 100%)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites:
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.
Further information on programme availabilityProgramme availability:

MN50752 is Compulsory on the following programmes:

School of Management

Notes:

  • This unit catalogue is applicable for the 2020/21 academic year only. Students continuing their studies into 2021/22 and beyond should not assume that this unit will be available in future years in the format displayed here for 2020/21.
  • Programmes and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.