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Colors for Data Science A-Z: Data Visualization Color Theory

Learn how to apply colour theory to improve your Data Science & Analytics data visualisations and presentations

  1. Topics
  2. Development
  3. Data Science Fundamentals

Colors for Data Science A-Z: Data Visualization Color Theory

InstructorPatrycja Hannagan
Duration3h 47m
Students7,961
Rating4.7 (1,448)
Sponsored
Price
$14.99
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Comidoc Analysis

Color theory fundamentals and tool-based visualization

Strengths

Technical Color Fundamentals

Covers essential concepts such as tints, shades, saturation, and the distinction between RGB and CMYK.

Practical Tool Integration

Provides instruction on using industry-standard tools like Adobe Color, Paletton, and ColorBrewer for palette creation.

Editorial course preview

What the public course preview actually shows

These 4 complementary views highlight concrete, legible examples from the course presentation.

Preview 1 of 4

Educational slide titled Tints, Shades and Saturation featuring a labeled color wheel and a photo of two presenters.

Preview 2 of 4

A screenshot of the Adobe Color CC interface displaying a complementary color scheme with a large color wheel, five swatches, and RGB HEX sliders.

Preview 3 of 4

Screenshot of the ColorBrewer web interface displaying a color scheme selection panel and a choropleth map of the United States

Preview 4 of 4

A Tableau Public dashboard displaying a scatter plot where colored dots represent different demographic groups across vitamin dose and test score metrics.

Applied Visualization Walkthrough

Includes a project-led segment using Tableau Public to demonstrate color application on real data examples.

Limitations

Manual Selection Focus

Instruction centers on manual color selection and lacks coverage of automated or programmatic methods.

Best suited to

  • Aspiring data presenters
  • Beginners seeking design fundamentals
  • Analysts using Tableau Public

Less suited to

  • Data scientists requiring automated color workflows
  • Advanced users looking for programmatic palette generation

Comidoc Score

7.1/10

Recommended
Beginner-friendly

Comidoc verdict

Technical mechanics of color, such as saturation and achromatic properties, form the core of the instruction. This foundation is paired with practical tool usage for generating palettes and a project walkthrough using Tableau Public to ground these theories in data visualization.

Instruction focuses on manual selection processes rather than automated or programmatic methods. One learner signal notes the absence of ways to automate color choices through code or advanced workflows.

This profile suits those looking to build a fundamental understanding of color theory to improve their presentation skills.

Score breakdown

Curriculum depth
8.8

The curriculum covers a wide range of technical properties and practical tool applications, though one signal notes the absence of automation techniques.

Applied learning
7.3

Learning is supported by section quizzes and a specific project walkthrough involving Tableau Public.

Clarity & experience
5.0

No substantive sampled-review evidence was available to move teaching clarity away from a neutral assessment.

Currency & reliability
6.5

The curriculum includes instruction on specific tools like Color Brewer 2.0.

Audience fit
6.5

Selected from the course's public promotional preview. These images document visible presentation material only; they do not represent the complete paid curriculum.

The curriculum aligns with the goal of improving data science presentations through color theory and tool usage.

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