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Data Visualization for Developers

Course Summary

At some point in your software development career, you may be called upon to produce a graph or a chart. Delivering on even a simple request can be remarkably complex. How much data is there and where does it live? What kind of chart should you use? Shoul


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    Course Syllabus

    ● Introduction
        ◦ Introduction
        ◦ One Dataset - Two Stories
        ◦ Data Scientists, Graphic Designers, and You
    ● Charting - 1A
        ◦ Introduction
        ◦ Just Enough Math
        ◦ Telling Stories with Statistics
        ◦ The Four Rules of Visualization: Rule 1 - Start with the Story
        ◦ Rule 2 - Make the Contrast Address the Story
        ◦ Rule 3 - Do not Forget the Data
        ◦ Rule 4 - Do not Make People Think
        ◦ Selecting a Chart Type
        ◦ Fun with Chart Libraries
        ◦ More Fun with Chart Libraries
    ● Business Intelligence
        ◦ Two Questions and a Myth
        ◦ Correlation, Causation, Interpolation, and Extrapolation
        ◦ Neatness Counts
    ● Visualization Architecture
        ◦ Visualization in the Age of Big Data
        ◦ The Architecture Game - Setting the Stage
        ◦ The Architecture Game Part 1 - Data and Analytics
        ◦ The Architecture Game Part 2 - Rendering and Display
        ◦ Variations on a Theme
    ● Hands-On Visualization
        ◦ Choosing the Perfect Story and Demo Environment
        ◦ Setting Up Your Demo Environment (Don't Worry, It's Painless)
        ◦ Looking at the Data
        ◦ Remote Database: Local Analytics and Rendering
        ◦ Remote Database: Analytics and Rendering
        ◦ Retrieving and Interpreting Analytics Data
        ◦ Remote Database: Analytics and Local Rendering
        ◦ Remote Database: Local Rendering and Analytics on Both
        ◦ Conclusion

     


Course Fee:
USD 29

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Development & Implementations and Data & Information Management Community

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