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Data and AI

Data Visualization

Build practical understanding of visual encodings, chart selection, scales, annotations, uncertainty, and accessibility, then use it for turning data into clear comparisons, patterns, and decision-ready stories.

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Level
Beginner to advanced foundations
Subject area
Data and AI
Learning outcomes
4 focused outcomes

Topic overview

Learn the foundations of Data Visualization.

Data Visualization connects visual encodings, chart selection, scales, annotations, uncertainty, and accessibility with practical decisions and tasks. Guided examples, comparison, practice, and feedback help learners apply these ideas to turning data into clear comparisons, patterns, and decision-ready stories. The goal is to make each step easier to explain, check, and improve.

Learning outcomes for Data Visualization

  1. 1

    Explain the main ideas and vocabulary involved in visual encodings, chart selection, scales, annotations, uncertainty, and accessibility

  2. 2

    Follow a repeatable process for turning data into clear comparisons, patterns, and decision-ready stories

  3. 3

    Compare examples, identify common mistakes, and improve an approach

  4. 4

    Complete an independent data visualization task and reflect on the result

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Suggested route

How to learn Data Visualization step by step.

01

Build the foundation

Explain the main ideas and vocabulary involved in visual encodings, chart selection, scales, annotations, uncertainty, and accessibility

02

Practise with feedback

Follow a repeatable process for turning data into clear comparisons, patterns, and decision-ready stories

03

Practise with feedback

Compare examples, identify common mistakes, and improve an approach

04

Apply and reflect

Complete an independent data visualization task and reflect on the result

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