Lesson 0
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Hello (Preface)

Short pre-course primer providing a quick preview of the class's structure and purpose before offering some background and direction on how best to use the online open source resources.
Lesson Table of Contents

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Lesson outline

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Lesson 0: Hello!

Briefly setting the stage for the course.

Objective

Short pre-course primer regarding the online version of Interactive Data Science and Visualization, offering some background and direction on how best to use the online open source resources.

Outline

This online-only lecture serves as a preface to the course. It starts by looking at the purpose and background of the class before outlining its structure. This provides additional context to the online auidence about how to take advantage of these resources in the Internet-based format.

Course purpose

Providing multiple perspectives to foster practical design and technical skills.

  • How to create world-class effective static and interactive user experiences with data, both for yourself and others.
  • Holistic design instruction and human lenses to critically consider pieces.
  • Hands-on exploration of skills to bring your ideas to life.
  • Python-based exercises with optional discussion of JavaScript.
  • Focused on hands on experimentation and experience (learn what is best felt not described).
Course background

Started at UC Berkeley but growing.

  • Originally taught as Stat 198 at UC Berkeley in 2025.
  • Some updates to materials have been made, including to make them more friendly to an online audience.
  • Designed with those studying computer and data science in mind but open to all disciplines with ample materials for multiple entrypoints.
Course structure

We take a 4 perspective approach across 6 sections with distinct but connected views into data visualization from the voices of different practitioners.

  • First lecture provides a more complete overview.
  • Traditional perception science view of information design, the discipline behind data visualization.
  • Bridge into other design disciplines, especially user-centered design.
  • Arts, semiotics, sociology, anthropology, media studies perspective on crafting and interpreting narrative.
  • Interaction perspective on creating tools which foster user-generated meaning.
How to use the course

Various types of instruction.

  • Outlines
  • Captioned videos
  • Slides
  • Rubrics, guides, manual, syllabus.

Materials can serve multiple objectives.

  • Take it cover to cover and gain a full balanced practical perspective on modern data visualization.
  • Borrow elements for your own instruction with different modalities (video, slides, outlines, exercises) available.
  • Deep dive on a specific aspect of data visualization to complement your own prior understanding.
  • Test the waters to determine if you want to take a full course.
Happy journey

I am thankful you, your perspective, and you ideas are here.

Take Aways

There are lots of ways into data visualization and it means different things in different contexts with different objectives.

  • We provide implementation exercises in Python. However, the course is also a deep exploration of design and perception science.
  • This course can be used in different ways to complement your own reading and learning with 4 sections to help you find what is most needed.
  • Start wherever feels right to you and grow, borrow liberally to add to other efforts.

Citations

[1] A. Pottinger, "TED Visualization," Gleap.org. Available: https://gleap.org/content/ted_visualization

[2] Wikipedia Contributors, "Snow-cholera-map-1.jpg." Wikimedia Foundation, Inc., 2020. Available: https://en.wikipedia.org/wiki/File:Snow-cholera-map-1.jpg

[3] A. Pottinger, L. Connor, B. Guzder-Williams, M. Weltman-Fahs, N. Gondek, and T. Bowles, "Climate-driven doubling of U.S. maize loss probability: Interactive simulation with neural network Monte Carlo," JDSSV, 2025. doi: 10.52933/jdssv.v5i3.134

[4] A. Pottinger, R. Geyer, N. Biyani, C. Martinez, N. Nathan, M. Morse, M. de Bruyn, C. Boettiger, E. Baker, K. Koy, and D. McCauley, "Global Plastics AI Policy Tool," University of California, 2024. Available: https://global-plastics-tool.org/

[5] A. Pottinger, "Food Sim SF," Gleap, 2024. Available: https://foodsimsf.com/

[6] A. S. Pottinger and G. Zarpellon, "Pyafscgap.org: Open source multi-modal Python-based tools for NOAA AFSC RACE GAP," JOSS, vol. 8, no. 86, p. 5593, Jun. 2023, doi: 10.21105/joss.05593.

License

This lesson is part of Interactive Data Science and Visualization and is released under a CC-BY-NC 4.0 license.

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Written materials

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Reading

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Works cited

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