[MUSIC] This MOOC is designed to introduce you to one of the basic data science techniques, K-means clustering. Our team of experienced instructors will consider K-means clustering from several perspectives: Machine learning, mathematics, statistics, and programming in Python. The MOOC consists of five weeks, and to pass this MOOC, you need to pass each week. My name is Jamie Ward, and I lectured on machine learning at Goldsmiths. My background is in wearable computing, where I research ways of using machine learning and wearable sensing to study human behaviors and social interactions. I will guide you through the first week of this course before passing you on to my colleagues Betty, Matthew and Larisa, who will take you through the next few weeks. >> Hello, my name is Betty Fyn-Sydney. I'm a pure mathematician with a background in statistics. I have taught mathematics to computer students at Goldsmiths for a few years now. In this course, I'll be introducing basic concepts in mathematics and statistics, that will require to enable you analyze data. At the end of the course, you should be equipped to solve real-world data science challenge using real data. >> Hi, I'm Matthew Yee-King, and I've taught programming at Goldsmiths for many years in different languages, such as C++, JavaScript, Python, and others. And also to analyze education data so we can improve the way that we teach programming. In this course, I am going to give you an introduction to the Python language, so that by the end of the course, you'll be able to put bits of Python together and build your own data processing pipelines. Now, it's not a full software engineering course, so we're not going to go into too much depth, but we're certainly going to give you the basics of Python language and how you can use it to build your own data pipelines. >> Hi, I'm Larisa Soldatova. I have taught data science for many, many years. I'm director of the online master program in data science. I also work on international research projects in the area of artificial intelligence. In this course, I will be guiding you through your data science project. I will ask you to apply techniques taught in this MOOC to a given dataset, and then present your results to a potential client. It will be an opportunity for your to demonstrate your understanding of how data clustering works. >> But for this first week, let's take a look at some of the main concepts covered in the course: data, machine learning, and K-means clustering. I will begin by exploring what we mean by data. [MUSIC]