Skip to main content

Software Engineering Principles in Python

19 reviews

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

Start Course for Free
4 Hours15 Videos51 Exercises
41,380 LearnersTrophyStatement of Accomplishment

Create Your Free Account



By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies

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


    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!

    Play Chapter Now
    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.

    Play Chapter Now

In the following tracks

Data EngineerPython DeveloperPython Programming


Collaborator's avatar
Chester Ismay
Collaborator's avatar
Adrián Soto
Adam Spannbauer HeadshotAdam 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.
See More

Don’t just take our word for it

from 19 reviews
Sort by
  • Lucas M.
    8 months

    fun and practical

  • Aleksandr B.
    about 1 year

    It’s helpful at all

  • Muhammad M.
    about 1 year


  • Nicolas K.
    about 1 year

    at times it was a bit confusing. It would be great if soe graphics and segmentation of code are indicated

  • Maciej G.
    over 1 year

    Course was good quality, showing proper usage of packets and modules,

"fun and practical"

Lucas M.

"It’s helpful at all"

Aleksandr B.


Muhammad M.

Join over 13 million learners and start Software Engineering Principles in Python today!

Create Your Free Account



By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.