Visual Analytics – Data science Training Course

Overview

This classroom based training session will contain presentations and computer based examples and case study exercises to undertake.

Requirements

Experience of analysis, statistics and producing data an advantage

Course Outline

  1. Introduction to Visual Analytics
    • 5 Principles of Data Visualisation
    • Tables vs charts
    • What makes visualisations effective
    • Gestalt Principles of Visual Perception
  2. Types of charts and how to choose the right one
    • Common types of charts
    • Choosing the right chart for your data
    • Understanding your audience
    • Handling missing data
  3. Advanced charts
    • Sankey
    • Radar
    • Treemap
    • Heatmap
    • Boxplot, violin plot
    • Choosing the right chart for your data
    • Choosing the right chart for your audience
    • Eliminating clutter from charts
  4. Storytelling with data
    • The importance of storytelling
    • Building a narrative structure
    • Drawing attention
    • Including call to action
  5. Creating dashboards and infographics
    • Exploratory vs explanatory analysis
    • How to convey your message
    • Live presentation vs report
    • Visualisations that are simple, informative and engaging
    • The characteristics of a good dashboard
    • The characteristics of a good infographic
  6. Common mistakes and misleading charts
    • Charts that should be avoided
    • How we are being deceived by colour, scale and size
  7. Visual analytics case studies

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