This presentation was a lightning talk given at the Society of Women Engineers' WE19 conference on Nov. 7, 2019

1. Linda Ruetz
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Learn Python! Why and How

2. Learning Outcomes
 Describe the capabilities of the Python programming
language
 Understand the numerous channels for learning Python
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3. What is Python?
 Programming Language which is:
 Free
 Cross-platform
 General purpose
 First released in 1991
 Named after British comedy group
‘Monty Python’s Flying Circus’
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4. Great Things About Python
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Compatible
Object-oriented (or not)
>>>__
Simple$ Free

5. Python Package Index (PyPI) count: nearly 200,000
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6. Libraries
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seaborn

7. Two More Reasons
 Great community support
 Python Software Foundation
 NumFOCUS, a 501(c)(3)
nonprofit charity.
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8. How Do I Install It?
 Python.org
 Packaging/distributions:
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9. How Do I Work In It? (Environments)
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10. Example data analysis code in Jupyter*
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* Coding Club tutorial

11. Example data analysis code in Jupyter
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* Coding Club tutorial

12. Example data analysis code in Jupyter
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* Coding Club tutorial

13. Example data analysis code in Jupyter
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* Coding Club tutorial

14. Resources for Learning Python
 Free tutorials
 learnpython.org (browser-based)
 Fee-based online courses
 Python For Everybody[coursera.com]
 Books
 User Groups
 Conferences
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 Podcasts
 Talk Python to Me
 Online tutors
 www.pythontutor.com
 Video courses
 Learn Python 3 The Hard Way
 Newsletters
 Real Python

15. Summary
 Python is an easy-to-read language that is relatively easy to learn
 Vast number of tested libraries/packages already written you can use
 Free and open source
 No matter what your favorite learning mode, there are resources for learning
Python!
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16. 16
xkcd.com

17. Contact information
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Linda.Ruetz@abbott.com

18. Additional Resources
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19. Free tutorials
 learnpython.org (browser-based)
 Python.org/about/gettingstarted

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20. Online courses
 Python For Everybody[coursera.com]
 The Data Science Toolbox[coursera.com]
 Learning Python with PyCharm[lynda.com]
 Introduction to Python: Absolute Beginner[edx.com]
 Introduction to Computer Science and Programming Using Python[edx.com]
 AI Programming with Python[udacity.com]
 Introduction to Computing in Python[edx.com]
 Python I: Essentials[quickstart.com]
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21. Books
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Sources:
• Oreilly.com
• HumbleBundle.com
• https://www.java67.com/2017/05/top-7-free-python-programming-books-pdf-online-download.html

22. Conferences
 PyCon: Annual, venue varies
 2 days of tutorials ahead of conference
 SciPy: Annually in July in Austin, TX
 Several days of tutorials ahead of conference
 PyData: Educational program of NumFocus
 PyData NYC: Nov. 4-6, 2019
 PyData Los Angeles: Dec. 3-5, 2019
 PyData Austin: Dec. 7-8, 2019
 OSCON (O’Reilly Open Source Convention)
 Videos from conferences: https://pyvideo.org/
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23. More Conferences
 PyCarolinas (North and South Carolina, United States)
 PyOhio (Ohio, United States)
 PyTexas (Texas, United States)
 PyGotham (New York, United States)
 PyBay (California, United States)
 PyCascades (Seattle, WA)
 Women Who Code Python Summit
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24. User Groups
 Local/Regional User Groups
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25. Podcasts
 Talk Python To Me
 From Python Import Podcast
 Podcast.init
 Python Bytes
 Python Testing
 Radio Free Python
 O’Reilly Programming
 Test and Code
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26. Online Tutors
 www.codementor.io
 https://tutorme.com
 www.pythontutor.com
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27. Video Courses
 Talk Python Training
 Learn Python 3 The Hard Way
 Learn More Python 3 the Hard Way: The Next Step for New Python
Programmers
 YouTube:
 PyDataTV
 Cory Schafer
 Data School
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28. Weekly newsletters
 Import Python Newsletter
 Pycoder's Weekly
 Python Weekly
 Python Tricks
 KDNuggets
 Real Python
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