In this course, we will cover the basics of visualization and how it fits into 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. You will also set up your Tableau environment, practice data loading, and perform univariate descriptive analysis of the S&P 500 stock sectors.
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加州大学尔湾分校
Since 1965, the University of California, Irvine has combined the strengths of a major research university with the bounty of an incomparable Southern California location. UCI’s unyielding commitment to rigorous academics, cutting-edge research, and leadership and character development makes the campus a driving force for innovation and discovery that serves our local, national and global communities in many ways.
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Visualization Fundamentals
Visualization is a crucial skill for data analysts across all disciplines. Viewing data graphically often provides greater intuition than by using statistics or mathematics alone. In this module, we’ll explore the fundamentals of visualization and discuss how visualizations can achieve better insight into data as well as effectively communicate results and conclusions.
Design Principles for Effective Visualizations
To create effective visuals, analysts must understand and be able to explain why specific graphical elements must be included, eliminated, or modified. In this module, we’ll investigate why certain questions are best answered by specific visual cue patterns, discuss which psychological perception theories should be considered during the construction of data visualizations, and cover the universal framework for representing visual data, the grammar of graphics.
Univariate Visualization Methods
Univariate visualization methods apply the grammar of graphics to the representation of a dataset’s fundamental properties and structures in terms of single variable mappings to visual encodings. In this module, we’ll explore specifics for how to view the data and what to visualize and discuss what mapping of data is best suited for highlighting and extracting insights from the data.
Standard Univariate Visualizations
Instead of reinventing the wheel with every visualization, analysts use several common chart types so there is no ambiguity about the decoding and interpretation of the data. In this module, we'll explore some standard tools and techniques that are used to prepare a fully crafted set of visualizations for the purpose of storytelling. Before completing this module, you will use Tableau to conduct a univariate analysis to sample data, compare dimensions vs. measures, and practice linking visualizations.
關於 Use Tableau for Your Data Science Workflow 專項課程
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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