Course Structure

As this course covers a broad range of ways that data visualizations can be used in the data analysis process, there will also be a large number of topics that will be touched upon. Below is a summary of topics that will be covered in the remaining lessons in this course.

Lesson 2: Design of Visualizations

Before getting into the actual creation of visualizations later in the course, this lesson introduces design principles that will be useful both in exploratory and explanatory analysis. You will learn about different data types and ways of encoding data. You will also learn about properties of visualizations that can impact both the clarity of messaging as well as their accuracy.

Lessons 3-5: Exploration of Data

These lessons systematically present core visualizations in exploratory data analysis. Exploration starts with univariate visualizations to identify trends in distribution and outliers in single variables. Bivariate visualizations follow, to show relationships between variables in the data. Finally, multivariate visualization techniques are presented to identify complex relationships between three or more variables at the same time.

Lesson 6: Explanatory Visualizations

This lesson describes considerations that should be made when moving from exploratory data analysis to explanatory analysis. When polishing visualizations to present to others, you will need to consider what findings you want to focus on and how to use visualization techniques to highlight your main story. This lesson also provides tips for presentation of results and how to iterate on your presentations.

Lesson 7: Visualization Case Study

In this lesson, you will bring together everything from the previous lessons in an example case study. You will be presented with a dataset and perform an exploratory analysis. You will then take findings from that analysis and polish them up for presentation as explanatory visualizations.

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