The most important factor for mastering data science is …
Projects can be great for mastering data science, but you have to choose your projects carefully.
This article will give you tips on how to choose a project that’s appropriate for your skill level (and tell you some pitfalls to watch out for).
A few days ago, I was inspired by a set of photographs of Earth from space, at night.
The images are amazing, so I decided to try to replicate them using R.
After you master the basics of R and ggplot2, you need to learn the little details.
A great example of this is plot annotation.
Adding little details like plot annotations help you communicate more clearly and “tell a story” with your plots.
In this post, I want to walk you through the logic of building a map, step by step …
Data science, artificial intelligence, automation, and other advanced technologies are reshaping the world.
As the world changes who’s likely to succeed?
The last few posts at Sharp Sight have been fairly intense.
Let’s make a quick map …
In several recent blog posts, I’ve emphasized the importance of data analysis.
My main point has been, that if you want to learn data science, you need to learn data analysis. Data analysis is the foundation of practical data science.
With that statement in mind, I want to show you step-by-step what an analysis looks like in R …
For a couple of years, I’ve been writing about the importance of data analysis, saying that data analysis is essentially the foundation of data science itself. While I admit that there’s room for argument (and I admit that the reality is a little more nuanced) I still firmly believe that data analysis is the true […]