There are nearly 200 countries in the world and thousands of state, provincial, and regional governments with literally hundreds of thousands of local governments. Each one of these governmental units needs data and information to do its administrative and legislative, work to allocate resources, and make decisions. The role of data and the need for talented and skilled people who can collect, analyze, and communicate about data is essential to the work of the public sector. >> This certificate is designed for current and future public sector professionals, who are tasked with gathering, analyzing, interpreting, and sharing data to be used in public administration and public policy making. >> The certificate has four courses, each of which is designed to equip learners with analytic and technical skills, and also how to apply them in the work of the public sector. >> The four courses are, fundamentals of public sector data analysis with R, exploratory data analysis for public administration with ggplot, assisting public sector decision makers with data and policy analysis. And finally, political and ethical considerations for data analytics in the public sector. >> Each course will help you build data analytic skills using R. >> It will also increase your understanding of the public sector, and the key ways as to how high quality data analytics are essential to the function and goals of government. >> I'm Chris Brooks. >> I'm Paula Lantz. >> We are here to introduce you to the data analytics in the public sector, the R certificate, and also to us, your instructors. >> We have enjoyed working together to design the four courses. Are very glad to be your instructors for this learning experience. Let's tell you a bit more about ourselves. I'm a faculty member in the school of information at the University of Michigan. I had the pleasure to teach hundreds of thousands of students data science courses right here on the Coursera platform. In those classes, I focused on data science and the Python ecosystem. But in this course, I'm excited to introduce you to the wonderful world of R. >> I'm a professor of public policy in health management and policy at the university of Michigan, where I teach courses on the basics of public policy, research methods for program and policy evaluation, and public health and social policy. My academic training is in social demography, epidemiology, and also health policy. Before I was a nerdy professor, which I love. I worked as a policy analyst for a county level juvenile court system, and also as an epidemiologist and policy analyst for a state health department. And in my research, which is focused on understanding and addressing social inequalities in health, I often work with the US Federal government, as well as state and local governments. Primarily with their health and social welfare services departments. I'm really excited to be part of this series, and to be providing you with some of the foundational context for the important role of data analytics in the public sector. You will mostly be learning with me and professor Brooks. But we will also be joined along the way by a number of additional experts who are eager to share their knowledge and experiences with you. >> We really want you to have an enjoyable, worthwhile, and successful learning experience. So, how can you do that? First, this certificate is building upon some knowledge and skills that you already have. We assume that you've already got some basic skills in working with data, perhaps through spreadsheets. And have been at least introduced to programming, though maybe not yet in R. We also assume that you've had some exposure to introductory statistics. >> In addition to this, you'll be most successful in this course if you take a hands on exploratory approach to learning the content. >> We've tried to make that easy. Not only do you have the videos and the notebook showing the R code, but we've embedded the R studio platform directly in the course for you to use. So there's nothing you have to install on your own computer. >> We do not assume that you have any prior experience working in the public sector, or any sort of knowledge of public administration or public policy. >> Really the main things you need to do to be successful in this series of courses include, stay engaged, and try to establish a pace for progress that's feasible for you and all the many other things you have going on in your life. >> Watching all of the videos and doing all of the activities recommended as well as required along the way. >> This will mostly involve actually performing data analytics using our studio, but there's other activities and types of applied skill building as well. >> Stay curious and passionate along the way. Know that you are investing in yourself in ways that will likely bring you new job opportunities, and very large sector of the global economy. >> Most importantly, be sure to define your own personal measure of success, and engage with the materials and skill building exercises we're providing along the way. >> We hope you'll stay with us through all four courses. >> By the end, you will have mastered skills covered in an introductory R course, along with fundamental material covered in introductory courses on public administration and public policy. >> And this includes an important theme that runs throughout the series. >> While high quality data and objective data analysts are vitally important to the work of the public sector, data alone never tells decision makers what to do. >> As this inevitably involves competing values, ethical considerations, and politics. >> So let's get started. We look forward to spending time with you, and keeping you interested and engaged as we move along. We hope you find our work together interesting, challenging, worthwhile, and most of all, fun. >> We'll see you soon in course one, the fundamentals of data analytics in the public sector, which will cover the core functions of public administration, the basics of survey and population data, and how to use the R programming language to clean data and answer questions. [MUSIC]
