• Specialization:听听Vital Skills for Data Science Specialization
  • Instructor:听Dr. Danielle Albers Szafir,听Assistant Professor of Computer Science,听Fellow in ATLAS Institute and听the Institute of Cognitive Science听and听Le谩 Norcross
  • Prior knowledge needed:听Python, Basic statistics (e.g., reading pie charts and bar charts, scatterplots)

Learning Outcomes

  • Develop a toolkit for exploring and communicating complex data using visualization
  • Produce basic data visualizations using a chosen dataset
  • Compare methods for visualizing data and understand how these methods may guide users towards different conclusions
  • Evaluate how effectively a visualization conveys target data

Course Content

Duration: 7h

In this module, you will learn the foundations of visualization design. You will walk through the key components of a visualization, how we effectively represent data using channels like color, size, and position, and some ground rules for honest and effective visualization. You will also gain preliminary exposure to Altair, a Python library for rapidly generating interactive visualizations. Each week will also include either two readings or one reading and one notebook activity.

Duration: 4h

In this module, you will learn how to choose the right visualization for a given scenario. You will learn how to reason about the different kinds of questions people ask with visualization and, how to align your design with that task. The module will cover basics of task analysis, methods for task elicitation, and foundational knowledge of visual perception for design. Each week will also include two external readings or one reading and one notebook activity.听

Duration: 3h

In this module, you will learn how to assess the effectiveness of your visualization. You will learn both qualitative and quantitative approaches for evaluating visualizations as well as how to isolate key elements for assessment and iteration. The module will cover basics of insight-based evaluation, interview studies, and experimental design and analysis. Each week will also include two external readings or one reading and one notebook activity.

Duration: 1h

You will complete a peer reviewed project worth 40% of your grade. You must attempt the final in order to earn a grade in the course. If you've upgraded to the for-credit version of this course, please make sure you review the additional for-credit materials in the Introductory module and anywhere else they may be found.

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