Web development for data scientists
Episode 3 of bite-sized data science
Data science is interdisciplinary, almost by definition. A good data scientist is one part statistician, one part subject matter expert, and one part developer.
How do you check each of these boxes, though? Most of the stats and model-building that you’ll need to know you can pick up through MOOCs like Udacity, and Fast.ai. And most of the subject matter experience you need, you can learn on the job, or by reading Wikipedia articles.
But what about the developer box? What does “development” mean in the context of data science? Figuring that out is probably the most challenging aspect of getting on your feet data science-wise, since most people who get into data science get in it for the algorithms and the model-building.
They typically don’t have a good sense of how to write clean code, or how to do web development — or why it’s even important.
And that’s exactly why Wesley is starting to focus his attention on web dev during his mentorship this week.
