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Big Data Analytics - COM00148M

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  • Department: Computer Science
  • Module co-ordinator: Dr. Rob Alexander
  • Credit value: 15 credits
  • Credit level: M
  • Academic year of delivery: 2023-24

Module summary

This module will provide the skills in data analytics, including the preparation of data, data handling, formulating precise questions, and using tools from statistics and data mining. 

Related modules

Pre-requisite modules

Co-requisite modules

  • None

Prohibited combinations

  • None

Module will run

Occurrence Teaching period
A Online Teaching Period 3 2023-24

Module aims

This module will provide the skills in data analytics, including the preparation of data, data handling, formulating precise questions, and using tools from statistics and data mining to address those questions. The module will also cover the privacy aspects of big data and the techniques to mitigate these risks.

Module learning outcomes

By the end of this module you should be able to:

  1. Create a data set using modern database models and technology,

  2. Manipulate a data set to extract statistics and features,

  3. Critically evaluate and apply data mining techniques/tools to build a classifier or regression model, and predict values for new examples,

  4. Analyse and communicate issues with scaling up to large data sets, and use appropriate techniques to scale up the computation,

  5. Critically discuss the need for privacy, identify privacy risks in releasing information, and use design techniques to mediate these risks.

Assessment

Task Length % of module mark
Essay/coursework
Report		 N/A 100

Special assessment rules

None

Additional assessment information

Reassessment will occur within 6 weeks.

Reassessment

Task Length % of module mark
Essay/coursework
Report		 N/A 100

Module feedback

Feedback will be provided in line with University policy. 

Indicative reading

 

  • Data Mining: Practical Machine Learning Tools and Techniques, 4th Edition, Ian Witten, Eibe Frank, Mark Hall, Chris J Pal, 2016
  • Data Science, Kelleher & Tierney, 2018 
  • Principles of Database Management, Lemahieu, Broucke, and Baesens, 2018

 


The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.