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Introduction to Python for Data Science

This is a set of notes used for teaching Python to students that have never used Python, or programmed in any language. In a usual semester, it takes approximately 4 weeks (meeting twice a week for an hour) to go through the material, for a freshmen undergraduate class.

Notes

  • The notes are in the form of iPython notebooks and are stored under the /notes folder.
  • You can open the notes in Google Colab. With Google Colab, you can save your work in your Google Drive.
  • If you do not want to use Google Colab, you can launch the notes in Binder, which is a temporary Jupyter server launched on-demand. Note that the Binder server will shutdown after a period of idleness. If you want to save your work, and you should save the notes locally to your computer.

Videos

Exercises for nbgrader (for Educators)

  • If you would like to get access to the autograded assignments that we have developed, please contact me at panos@stern.nyu.edu.

Recommended Books

Additional Books for Learning Python

  • How To Think Like a Computer Scientist: An interactive guide to programming and Python. The book "Python for Everybody" (listed above) is partially based on this book.
  • Learn Python the Hard Way: An introduction to programming and Python. It targets complete beginners. It used a drill-based approach for teaching, which can be tedious at times. Nevertheless, it is considered one of the standard textbooks for learning Python.

Online Classes

Additional Pointers

Python Exercises

Credits

  • I have stolen relied heavily on the "Python for Everybody" and the "How To Think Like a Computer Scientist" books to develop the structure and the material for the notes.
  • The initial version of the notebooks came from Josh Attenberg, from his course "Practical Data Science" that was taught at NYU/Stern.
  • Katherine Hoffmann contributed to the development of the current notebooks.

License

  • Outside NYU, the material is licensed under the Creative Commons Attribution-ShareAlike 4.0 license. If you are working within NYU, note that any usage of the material is strictly prohibited.

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Notes for the "Introduction to Programming for Data Science" class

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