David was a Director of the Python Software Foundation for six years, and remains co-chair of its Trademarks Committee, its Python-Cuba working group, and of the Scientific Python Working Group.
He wrote the columns, Charming Python and XML Matters for IBM developerWorks, short books for O'Reilly, and the Addison-Wesley book Text Processing in Python, has spoken at multiple OSCon's, PyCon's, and at AnacondaCon, and was invited keynote speaker at PyCon-India, PyCon-UK, PyCon-ZA, PyCon Belarus, PyCon Cuba, and PyData SF.
David created the data science training program for Anaconda Inc. and was a senior trainer for them. Before that, he worked for 8 years with the folks (D. E. Shaw Research) who have built the world's fastest, highly-specialized (down to the ASICs and network layer), supercomputer for performing molecular dynamics. He is pleased to find Python has become the default high-level language for most scientific computing projects.
Michael is a data scientist in Seattle. Over his career, he has worked for major enterprises and venture-backed startups delivering sophisticated analysis and technology project management services from hyperlocal demographics inference to market share forecasting.
Michael received a MS Economics, a BS Computer Science, and a BS International Affairs from the Georgia Institute of Technology.
We offer a courses covering a wide variety of topics in data science and scientific Python (and scientific computing beyond Python as well). We especially like those great projects sponsored by NumFOCUS, but generally admire and contribute to the entire numeric and scientific Python tool stack.
Within a framework of some general "tracks" or "programs" we know work well from our years of experience training professionals at many different levels of experience, we can customize syllabi to fit the needs of your particular company or organization.
From data analysis, to visualization, to machine learning, to heavy duty number crunching and parallel computing, we are eager to help your team gain more in depth knowledge and a broader perspective on the scientific and data-oriented programming tools that will let them get their jobs done.
Some of the areas we are happy to cover include:
Contact us by email at email@example.com