This is it folks! This is the first of the special episodes I want to do from time to time, to expand our perspective and get inspired by what’s going on elsewhere. The guests will not come directly from the Bayesian world, but will still be related to science or programming.
For the first episode of the kind, I had the chance to chat with Michael Kennedy! Michael is not only a very knowledgeable and respected member of the Python community, he’s also the founder and host of Talk Python To Me, the most popular Python podcast. He’s the founder and chief author at Talk Python Training, where he develops many Python developer online courses. 
And before that, Michael was a professional software trainer for over 10 years – he has taught numerous developers throughout the world! But Michael is not only an entrepreneur and teacher – he’s also a father, a husband, and a proud inhabitant of Portland, OR! 
As you’ll hear, our conversation spanned a large array of topics — the role of Python in science and research; how it came to be so important in data science, and why; what are Python’s threats and weaknesses and how it should evolve to not become obsolete. Michael also has interesting thoughts on the role of programming in education and how it relates to geometry — but I’ll let you discover that one by yourself…
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ (https://bababrinkman.com/) !
Links from the show:
Michael on Twitter: https://twitter.com/mkennedy (https://twitter.com/mkennedy)
The Talk Python Podcast: https://talkpython.fm/ (https://talkpython.fm/)
The Python Bytes Podcast: https://pythonbytes.fm/ (https://pythonbytes.fm/)
Michael's blog: https://blog.michaelckennedy.net/ (https://blog.michaelckennedy.net/)
Michael on Crowdcast: https://www.crowdcast.io/mkennedy (https://www.crowdcast.io/mkennedy)
Jupytext -- Turn Jupyter Notebooks to scripts and (R) Markdown files: https://jupytext.readthedocs.io/en/latest/introduction.html (https://jupytext.readthedocs.io/en/latest/introduction.html)



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