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Julie Pai and Majed Al-Ghandour

This specialization covers the foundations of visualization in the context of the data science workflow. Through the application of interactive visual analytics, students will learn how to extract structure from historical data and present key points through graphical storytelling. Additional topics include data manipulation, visualization foundations, audience identification, ethical considerations, dashboard creation, and report generation. Demonstrations of the basic visualization techniques used in Tableau will be included with a hands-on project.

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What's inside

Three courses

Data Visualization Best Practices

In this course, we will cover the basics of visualization and its role in the Data Science workflow. We will focus on the main concepts behind the purpose of visualization and the design principles for creating effective, easy-to-communicate results.

Data Storytelling

This course covers advanced data storytelling concepts, exploring the relationship between visual aspects and data understanding. We'll examine how these concepts work together through data storytelling. After reviewing key points on avoiding problematic visualizations and data misrepresentation, you'll continue working in Tableau performing multivariate descriptive analysis of the S&P 500 stock sectors.

Dashboarding and Deployment

This course covers analytical dashboarding, including best practices for design, creating a unified analytical environment, and deploying visualizations. You will learn advanced visualization techniques and develop an information layout of the biggest gainers and losers in the financial markets, comparing those movements to economic data.

Learning objectives

  • Explain fundamental concepts behind visualizations.​
  • Setup and perform data analysis using industry-standard models​.
  • Create a tableau dashboard implementing major tasks of analytics deployment: define business goals, prepare data, select, model, and present results.

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