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Software Engineering for Data Scientists in Python

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

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4 Hours15 Videos51 Exercises30,142 Learners4100 XPPython Programmer TrackPython Programming Track

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Course Description

Data scientists can experience huge benefits by learning concepts from the field of software engineering, allowing them to more easily reutilize their code and share it with collaborators. In this course, you'll learn all about the important ideas of modularity, documentation, & automated testing, and you'll see how they can help you solve Data Science problems quicker and in a way that will make future you happy. You'll even get to use your acquired software engineering chops to write your very own Python package for performing text analytics.
  1. 1

    Software Engineering & Data Science

    Free

    Why should you as a Data Scientist care about Software Engineering concepts? Here we'll cover specific Software Engineering concepts and how these important ideas can revolutionize your Data Science workflow!

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    Python, data science, & software engineering
    50 xp
    The big ideas
    50 xp
    Python modularity in the wild
    100 xp
    Introduction to packages & documentation
    50 xp
    Installing packages with pip
    50 xp
    Leveraging documentation
    100 xp
    Conventions and PEP 8
    50 xp
    Using pycodestyle
    100 xp
    Conforming to PEP 8
    100 xp
    PEP 8 in documentation
    100 xp
  2. 2

    Writing a Python Module

    Become a fully fledged Python package developer by writing your first package! You'll learn how to structure and write Python code that you can be installed, used, and distributed just like famous packages such as NumPy and Pandas.

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In the following tracks

Python ProgrammerPython Programming

Collaborators

chester
Chester Ismay
adriansoto
Adrián Soto
Adam Spannbauer Headshot

Adam Spannbauer

Machine Learning Engineer at Eastman

Adam is a machine learning engineer at Eastman Chemical Company. His work history has had a focus on NLP projects using open source data science tools such as Python, R, and Shiny. He stays active in the open source community on GitHub, mostly working on side-projects involving computer vision. Adam holds degrees from Maryville College and the University of Tennessee.
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