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Last modified: 28 Jun 2018 10:27

Course Overview

This course aims to make students familiar with basic data mining and visualisation techniques and software tools. Students will learn how to analyse complex datasets by applying data pre-processing, exploration, clustering and classification, time series analysis, and many other techniques. This course will also cover text mining and qualitative modelling. Through this course students will be able to analyse real-world datasets in various domains and discover novel patterns from them. This course is particularly suitable for those who are interested in working as data analysts or data scientists in the future.

Course Details

Study Type Undergraduate Level 4
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus None. Sustained Study No
  • Dr Wei Pang
  • Dr Chenghua Lin

What courses & programmes must have been taken before this course?


What other courses must be taken with this course?


What courses cannot be taken with this course?


Are there a limited number of places available?


Course Description

  • Data Mining: basic statistics, advanced data analysis techniques such as trend detectors, pattern detectors, qualitative models, basic data mining techniques such as classification and clustering.
  • Visualization: information visualization (basic concepts, advanced techniques such as treemaps); supporting user variation (abillities, knowledge, preferences)
  • Applications to real world problems: for example, medical decision support, supporting analysis of genome data

Further Information & Notes

Assistive technologies may be required for any student who is unable to use a standard keyboard/mouse/computer monitor. Any students wishing to discuss this further should contact the School Disability Co-ordinator. To be taken as part of the BSc honours programme in Computing Science.

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers

Details, including assessments, may be subject to change until 31 August 2023 for 1st half-session courses and 22 December 2023 for 2nd half-session courses.

Summative Assessments

1st Attempt: 1 two-hour written examination (75%); continuous assessment (25%).

Resit: One 2-hour examination (100%). Only the marks obtained at first attempt can be used for Honours classification.

Formative Assessment

During lectures, the Personal Response System and/or other ways of student interaction will be used for formative assessment. Additionally, practical sessions will provide students with practice opportunities and formative assessment.


Formative feedback for in-course assessments will be provided in written form. Additionally, formative feedback on performance will be provided informally during practical sessions.

Course Learning Outcomes


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