In the capstone project, you will get to apply your new data analytics skills to do pretty much what you learn in the four courses of the specialization. That is, you will select the data set you want to work with. And identify the research question an the variables you will use to answer the question. You will conduct data management, examine descriptive statistics, and do some data visualization based on what you learned in the first course of the specialization. You will apply what you learned in the second course to conduct some preliminary statistical analyses. Finally, you will apply any of the statistical methods that you learned about in the regression and machine learning courses, then interpret and write about your findings. The blogging that you have been doing all along in the specialization will help you with writing up your final project. You have a few options to choose from for your Capstone project. First, you can work with our industry partner DrivenData to help them solve some of the world's biggest social challenges by joining one of their learning competitions. DrivenData hosts online challenges where our global community of data scientists competes to come up with the best statistical model for difficult predictive problems that make a difference in the world. To be a part of this, all you have to do is check out the DrivenData website, watch their introductory video and then see what challenges are being currently offered. For the Capstone course you want to limit your choices to the challenges that are for learning and exploring. The competitions with cash prices are cool, but the rules of those competitions limit the amount of outside feedback you can get while you're competing. Given that this class is all about feedback, the cash prize challenges won't work. But you can definitely enter the cash prize competitions after you complete the specialization in our master data analyst. Once you've had a chance to review the available challenges, if you decide you want to enter one then register yourself as a DrivenData competitor. Read the rules of the competition. Download the data and data documentation and get started. You'll document your data analytic process in your milestone assignments and in your final capstone report. The same way as everyone else in the course. If you decided entering a challenge is not for you right now, you can choose from one of the real world datasets that we have made available for use in the capstone course. Check out the dataset descriptions and review the documentation for the datasets that interest you. Then you can download the dataset you want to work with and get started. Finally, you're welcome to use your own dataset. But if you plan to use your own data, you should keep in mind that your final capstone project will be due in about five weeks. So make sure that the data are pretty clean and fairly well documented to avoid spending way too much time on data management. It's rare to find a data set that doesn't require some cleaning. But really messy datasets can take a great deal of time to clean. Regardless of what you choose as your data source, all Capstone projects will be required to meet certain criteria. Specifically you'll write a 2,000 to 2,500 word Capstone report that summarizes your capstone project. The report should include a title, an introduction to the research question, a method section, a results section and a conclusions and limitations section. We'll provide plenty of detailed instruction about what you need to include in each of the sections of your final report.