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  4. 2016-2017
  5. Computing Science
  6. CS5012: Data Mining and Visualisation

CS5012: DATA MINING AND VISUALISATION (2016-2017)

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 Postgraduate Level 5
Session First Sub Session Credit Points 15 credits (7.5 ECTS credits)
Campus None. Sustained Study No
Co-ordinators
  • Dr Wei Pang
  • Dr Chenghua Lin

Qualification Prerequisites

None.

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

  • Computing Science (CS) (Studied)
  • Any Postgraduate Programme (Studied)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

  • (Studied)

Are there a limited number of places available?

No

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 (abilities, knowledge, preferences) • Applications to real world problems: for example, medical decision support, supporting analysis of genome data.

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

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

Formative Assessment

There are no assessments for this course.

Feedback

None.

Course Learning Outcomes

None.
 

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