Professional Development is unfortunately non-existent for many of us in the public sector. Besides the skills I gained in college and grad school, I am self-taught as far as practical data analysis. So, let’s take PD into our own hands with online learning.
This series will focus on the steps needed to refresh our memories in math and statistics; move on to data science and analyses of various degrees of difficulty (including resources for Python and R); and finally move on to visualization and machine learning–all with practical applications to our work in public sector data analysis.
To start off the series on Professional Development, I will focus on the building blocks for data science and analysis: math and statistics. This might seem like an unnecessary step, but as data analysts we need to have a solid foundation in both subjects to move on to more advanced topics.