 Now, something that I've mentioned several times when talking about data science, and I'll do it again in this conclusion, is that it's important to give people next steps. So I'm going to do that for you right now. If you're wondering what to do after having watched this very general overview course, I can give you a few ideas. Number one, maybe you want to start trying to do some coding in R or Python, we have courses for those. You might want to try doing some data visualization, one of the most important things that you can do. You may want to brush up on statistics and maybe some math that goes along with it. And you may want to try your hand at machine learning. All of these will get you up and rolling in the practice of data science. You can also try looking at data sourcing find the information that you're going to do. But no matter what happens, try to keep it in context. So for instance, data science going to be applied to marketing and sports and health and education and the arts and really a huge number of other things. And we will have courses here at data lab.cc that talk about all of those. You may also want to start getting involved in the community of data science. One of the best conferences that you can go to is O'Reilly Strata, which means several times a year around the globe. There's also predictive analytics world again, several times a year around the world. Then there's much smaller conferences I love tapestry or tapestry conference.com, which is about storytelling in data science. And extract a one day conference about data stories that's put on by import IO, one of the great data sourcing applications that's available for scraping web data. If you want to start working with actual data, a great choice is to go to Kaggle.com. And they sponsored data science competitions, which actually have cash rewards. But there's also wonderful data sets you can work with there to find out how they work and compare your results to those of other people. And once you're feeling comfortable with that, you may actually try turning around and doing some service data kind.org is the premier organization for data science as humanitarian service. They do major projects around the world. I love their examples. There are other things you can do. There's an annual event called do good data. And then data lab CC will be sponsoring twice a year data lab surets, which are opportunities for people in the Utah area to work with local nonprofits on their data. But above all of this, I want you to remember this one thing data science is fundamentally democratic. It's something that everybody needs to learn to do in some way shape or form. The ability to work with data is a fundamental ability. And everybody would be better off by learning to work with data intelligently and sensitively. Or to put it another way, data science needs you. Thanks so much for joining me for this introductory course. I hope it's been good. And I look forward to seeing you in the other courses here at data lab dot CC.