Boot Camp Tales
A Curriculum Synopsis
Somewhere in one of our bootcamp slide decks we define a “data scientist” as someone who knows more about programming than your average statistician, and more about statistics than your average programmer. I found that clever.
Note that this definition doesn’t preclude knowing more about programming than your average programmer, nor being more stats savvy than your average statistician; these extremes could be included, but would be a measure of strength over and above what we call setting a lower bar.
As a code school instructor, my job is to look towards raising my students above that lower bar, and at the end of 2024 this means taking the Python path into programming, and a machine learning (ML) approach into stats.
I’m like the conductor slash tour guide from London to Berlin, on a train bound for Beijing eventually. We start with basic Python and work our way up through Data Analysis and then Data Visualization. These three are separate modules, with more modules to follow.
When working through Python basics, I start mentioning statistics in an historical context, talking about:
(a) how in my experience the stats folks have always been hungry for computer power and
(b) how we might explore the subject by following some of it fissures and…
