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Course Outline

Day 1:

  • Introduction to data visualization
  • The importance of data visualization
  • Data visualization versus data mining
  • Human cognition
  • HMI
  • Common pitfalls

Day 2:

  • Different types of curves
  • Drill down curves
  • Plotting categorical data
  • Multi-variable plots
  • Data glyphs and icon representation

Day 3:

  • Plotting KPIs with data
  • Examples of R and X charts
  • What-if dashboards
  • Parallel axes mixing
  • Combining categorical and numeric data

Day 4:

  • Different roles in data visualization
  • How data visualization can be misleading
  • Disguised and hidden trends
  • A case study on 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.

 28 Hours

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