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Data Processing in Shell

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

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4 Hours13 Videos46 Exercises12,792 Learners3550 XPData Engineer Track

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Course Description

We live in a busy world with tight deadlines. As a result, we fall back on what is familiar and easy, favoring GUI interfaces like Anaconda and RStudio. However, taking the time to learn data analysis on the command line is a great long-term investment because it makes us stronger and more productive data people.

In this course, we will take a practical approach to learn simple, powerful, and data-specific command-line skills. Using publicly available Spotify datasets, we will learn how to download, process, clean, and transform data, all via the command line. We will also learn advanced techniques such as command-line based SQL database operations. Finally, we will combine the powers of command line and Python to build a data pipeline for automating a predictive model.

  1. 1

    Downloading Data on the Command Line


    In this chapter, we learn how to download data files from web servers via the command line. In the process, we also learn about documentation manuals, option flags, and multi-file processing.

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    Downloading data using curl
    50 xp
    Using curl documentation
    50 xp
    Downloading single file using curl
    100 xp
    Downloading multiple files using curl
    100 xp
    Downloading data using Wget
    50 xp
    Installing Wget
    50 xp
    Downloading single file using wget
    100 xp
    Advanced downloading using Wget
    50 xp
    Setting constraints for multiple file downloads
    50 xp
    Creating wait time using Wget
    100 xp
    Data downloading with Wget and curl
    100 xp
  2. 4

    Data Pipeline on the Command Line

    In the last chapter, we bridge the connection between command line and other data science languages and learn how they can work together. Using Python as a case study, we learn to execute Python on the command line, to install dependencies using the package manager pip, and to build an entire model pipeline using the command line.

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In the following tracks

Data Engineer


adriansotoAdrián Sotohillary-green-lermanHillary Green-Lerman
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Susan Sun

Data Person

I want to make a statistically significant difference in the world.

My expertise lies in design-based strategic data consulting for start-ups, data-related training & education, conscientious application of data science for business, and pro bono data work for social change.
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Lloyds Banking Group

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Harvard Business School

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Decision Science Analytics, USAA