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Course Outline

Day 1:

  • What is data visualisation?
  • Why it matters
  • Data visualisation versus data mining
  • Human cognition
  • HMI
  • Common pitfalls

Day 2:

  • Different types of curves
  • Drill-down curves
  • Categorical data plotting
  • Multi-variable plots
  • Data glyph and icon representation

Day 3:

  • Plotting KPIs with data
  • R and X chart examples
  • What-if dashboards
  • Parallel axes mixing
  • Categorical data combined with numeric data

Day 4:

  • The many facets of data visualisation
  • How data visualisation can mislead
  • Disguised and hidden trends
  • A case study using student data
  • Visual queries and region selection

Requirements

A foundational understanding of data plotting—including X-Y graphs, histograms, and scatter plots—along with a general grasp of data trends and time-series graphing is required.

 28 Hours

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