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SQL for Exploratory Data Analysis Essential Training

Learn how to use SQL to understand the characteristics of data sets destined for data science and machine learning. The course begins with an introduction to exploratory data analysis and how it differs from hypothesis-driven statistical analysis. Instructor Dan Sullivan explains how SQL queries and statistical calculations, and visualization tools like Excel and R, can help you verify data quality and avoid incorrect assumptions. Next, find out how to perform data-quality checks, reveal and recover missing values, and check business logic. Discover how to use box plots to understand non-normal distribution of data and use histograms to understand the frequency of data values in particular attributes. Dan also explains how to use the chi square test to understand dependencies and measure correlations between attributes. The course concludes with a collection of tips and best practices for exploratory data analysis.

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    LinkedIn Learning

    Rating Not enough ratings
    Length 44m 7s
    Starts On Demand (Start anytime)
    Cost $29/month (Access to entire library- free trial available)
    From LinkedIn Learning
    Instructor Dan Sullivan
    Download Videos Only via the LinkedIn Learning mobile app
    Language English
    Subjects IT & Networking Data Science
    Tags IT Big Data

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    LinkedIn Learning

    Rating Not enough ratings
    Length 44m 7s
    Starts On Demand (Start anytime)
    Cost $29/month (Access to entire library- free trial available)
    From LinkedIn Learning
    Instructor Dan Sullivan
    Download Videos Only via the LinkedIn Learning mobile app
    Language English
    Subjects IT & Networking Data Science
    Tags IT Big Data

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