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Data Visualization

Ross Maciejewsk, Huan Liu, and K. Selcuk Candan

Visual representations generated by statistical models help us to make sense of large, complex datasets through interactive exploration, thereby enabling big data to realize its potential for informing decisions. This specialization covers techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science to enhance the understanding of complex data.

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What's inside

Four courses

Multivariate and Geographical Data Analysis

(0 hours)

Covering the tools and techniques of both multivariate and geographical analysis, this course provides hands-on experience visualizing data that represents multiple variables.

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Introduction to Data Exploration and Visualization

This course introduces data visualization, its power, and core concepts like dataset elements, data warehouses, exploratory querying, and visual variables. It also covers statistical graphs essential for exploratory data analysis.

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Additional Tools Used for Data Visualization

(0 hours)

This course introduces Tableau, a cutting-edge visualization software. It reinforces visualization concepts and replicates visualizations from previous courses using Tableau.

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Temporal and Hierarchical Data Analysis

(0 hours)

Data repositories with cases related to subcases are called hierarchical. This course covers the representation schemes of hierarchies and algorithms that enable analysis of hierarchical data, as well as provides opportunities to apply several methods of analysis.

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Time

68 hours

Via

Coursera

Institution

Arizona State University

Instructors

Ross Maciejewsk

Huan Liu

K. Selcuk Candan

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