Data Science 209
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.
Exploratory data analysis / Effective written communication / Effective visual presentation of data / Design for human perception
Current Course Designers
Original Course Designer
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.
Previously listed as DATASCI W209.
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