I’m often asked where’s the best place to get started in data science and AI. My answer is almost always the same: statistics. Statistics is the bedrock of data science and it’s a core pillar of AI. You could make the argument that statistics make up the core for understanding reality itself, but I have not had enough coffee yet to engage in such philosophical banter.

Here’s a great video on Probability vs. Likelihood. In common conversation we tend to use these words interchangeably. However, statisticians make a clear distinction that is important to understand if you want to follow their logic. Like most of statistics, they are both super simple and easy to get mixed up. F

I’ll be headed off to Las Vegas this week for an internal Microsoft event. When this video on “taking the luck out of gambling” with Mathematics, came across my desk, I thought it was timely and good enough to share.

From the video description:

Spanning mathematics, psychology, economics and physics, Adam Kucharski reveals the long and tangled history between betting and science, and explains how gambling shaped everything from probability to game theory, and chaos theory to artificial intelligence.

This video is an introduction to R programming in which I provide a tutorial on some statistical analysis (specifically using the t-test and linear regression).

It also demonstrates how to use dplyr and ggplot to do data manipulation and data visualization. Its R programming for beginners really and is filled with graphics, quantitative analysis and some explanations as to how statistics work.

If you’re a statistician, into data science or perhaps someone learning bio-stats and thinking about learning to use R for quantitative analysis, then you’ll find this video useful. Importantly, R is free.