Data Science W209

Data Visualization

3 units

Course Description

Visualization enhances exploratory analysis as well as efficient communication of data results. This course focuses on the design of visual representations of data in order to discover patterns, answer questions, convey findings, drive decisions, and provide persuasive evidence. The goal is to give you the practical knowledge you need to create effective tools for both exploring and explaining your data. Exercises throughout the course provide a hands-on experience using relevant programming libraries and software tools to apply research and design concepts learned.

Skill Sets

Exploratory data analysis / Effective written communication / Effective visual presentation of data / Design for human perception


Tableau / JavaScript / D3 / Illustrator / R / ggplot2 / Highcharts / Visit

Current Course Designers

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John Alexis Guerra Gómez
John Alexis Guerra Gómez
Former Lecturer

Original Course Designer

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Annette Greiner
Instructor Alumni (MIMS 2010)

Student Learning Outcomes

  • Analyze data using exploratory visualization. 

  • Build commonly requested types of visualizations as well as more advanced visualizations using ground-up customization.
  • Constructively critique existing visualizations, identifying issues of integrity as well as excellence.
  • Create useful, performant visualizations from real-world data sources, including large and complex datasets.

  • Design aesthetically pleasing static and interactive visualizations with perceptually appropriate forms and encodings.
  • Improve your own work through usability testing and iteration, with attention to context.
  • Select appropriate tools for building visualizations, and gain skills to evaluate new tools.


MIDS students only. DATASCI W203. Students must take DATASCI W205 concurrently or prior to DATASCI W209. Recommended: experience with HTML, CSS, and JavaScript, or ability to learn new programming languages quickly.

Last updated:

June 18, 2021