 Welcome to Data Science and Introduction. I'm Barton Poulsen, and what we're going to do in this course is we're going to have a brief, accessible, and non-technical overview of the field of data science. Now, some people, when they hear data science, they start thinking things like data and think about piles of equations and numbers, and then to throw on top of that science and think about people working in their lab, they start to say, yeah, that's not for me. I'm not really a technical person, and that just seems much too techy. Well, here's the important thing to know. While a lot of people get really fired up about the technical aspects of data science, the important thing is that data science is not so much a technical discipline, but creative. And really, that's true. The reason I say that is because in data science, you use tools that come from coding and statistics and from math, but you use those to work creatively with data. The idea is that there's always more than one way to solve a problem or answer a question, most importantly, to get insight, because the goal, no matter how you go about it, is to get insight from your data. And what makes data science unique compared to so many other things is that you try to listen to all of your data, even when it doesn't fit in easily with your standard approaches and paradigms. You're trying to be much more inclusive in your analysis. And the reason you want to do that is because everything signifies, everything carries meaning, and everything can give you additional understanding and insight into what's going on around you. And so in this course, what we're trying to do is give you a map to the field of data science and how you can use it. And so now you have the map in your hands, and you can get ready to get going with data science.