Data Visualisation Analytics module (CS31001)

Explore how to extract valuable information from large datasets.

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In today's data-driven world, the ability to effectively analyse and visualise data is becoming increasingly important across a wide range of industries, such as healthcare, finance, and digital marketing.

This module provides you with the skills and knowledge needed to make sense of complex datasets and communicate insights effectively.

By studying statistical methods, exploring data visualisation techniques, and learning how to mine data from vast datasets, you will be able to tackle real-world problems and make data-driven decisions. 

What you will learn

In this module, you will:

  • study basic frequentist statistics
  • explore how to visualise data and information effectively
  • learn about the methodologies of the Cross-Industry Standard Process for Data Mining (CRISP-DM)
  • explore various data mining algorithms and their use cases
  • work with industry standards and techniques for data visualisation and analytics

By the end of this module, you will be able to:

  • understand and explain the importance of statistics in today's world
  • select appropriate statistical techniques and data visualisations
  • discuss various data mining techniques
  • select appropriate data mining techniques for real-world problems

Assignments / assessment

  • statistical techniques (30%)
  • data mining application development (20%)
  • data visualisation application development (50%)

This module does not have a final exam.

Teaching methods / timetable

You will learn by taking a hands-on approach. This will involve taking part in tutorials and practical sessions.

Learning material is provided through videos, review notes, examples, and tutorial questions.

This is a half-semester module. You will study another 10 credit module during the other half of this semester.


This module is available on following courses: