Hello, and welcome to the SQL for Data Science course. My name is Sadie St. Lawrence, and I'm your instructor and guide for this course. I'm a data scientist for VSP Global, where I build data stories, predictive models, and work with machine learning algorithms to help the organization improve their services, identify new markets, and a whole host of other things. In addition to working at VSP, I'm the Executive Director of Women in Data, where we focus on providing economic opportunities for women in data and fostering global data literacy. With Women in Data, I've led multiple training sessions in data science, which I love because teaching is where my real passion lies. For me, an understanding of SQL is so fundamental to any successful data scientist, so I'm excited to help you learn all about it. If you're taking this course, you might not be too surprised by the fact that data is everywhere. Well, here in the 21st century, data is being collected all the time to help organizations optimize their work. And whether we are aware of it or not, data is being collected and being stored on all of us. Everything from what you buy at the store to what movies you watch, music you listen to, books you read, your fashion choices, how you use your smart phones, searches you may done in internet, your health, what vehicle you drive, what advertisements convince you to make a purchase, and I could go on and on. Outside the business world, of course, data is collected for an important climate change research, healthcare, and medical analysis purposes and trying to solve the universe's greatest mysteries. Data is even being collected on you right now as you're participating in this course, in order to help Coursera figure out how to improve everyone's online learning experiences. So in the 21st century, data is key. Everyone is collecting it all the time. And I really feel it's those people who can use and interact with data, those who use it to critically think and provide insight out of it to make better decisions, those are going to be the people who shape the very world we live in. These people are data scientists. And I think Data Science is one of the most rewarding and interesting fields you can get into right now. But to be a good data scientist, you need to know how to retrieve and work with data. And to do that, you need to be very well versed in SQL, the standard language for communicating with databases. The purpose of this course is to give you a primer in the fundamentals of SQL, and working with data so that you can begin analyzing it for data science purposes. Asking the right questions, and coming up with good answers to deliver valuable insights for your organization. In this course, we cover a lot of ground. In fact, I really start at the beginning. Well, having a little bit of knowledge of SQL will already help you out. I'm not going to assume you know anything about SQL. I'm really going to start from square one here. You'll learn all about SQL syntax, common statements, concepts and terminology. We'll discuss how to write both simple and complex queries to help you select data from tables and work with it. And we'll talk about working with different types of data like strings and numbers. We'll also discuss methods for you to filter down and pare your results. And we'll talk about creating new tables altogether, and moving data into them. I'll introduce to you to common operators like WHERE, LIKE, ORDER BY, BETWEEN. And we'll talk about how to combine data using various types of joints. We'll even go over how to use case statements, and spend a little time on concepts like data governance and profiling. Along the way, you'll participate in discussions about data and work on real world programming assignments in order for you to practice your newly learned skills. No matter your level of experience, I promise you that by the time you finish this course, you'll be able to interpret the structure, meaning and relationships in source data and use SQL as a professional to shape your data for targeted analysis purposes. As you can probably tell, I'm really excited about this course. And I hope you are too. All right, so let's go ahead and dive in.