Delve into the rapidly emerging field of data science and learn to apply it to your future career. Touted as the “sexiest job of the 21st century” by the Harvard Business Review, and the best current job by Forbes magazine in 2016, students with data science skills are sought after across all industries. Data science techniques will enhance your employability regardless of the degree you are studying. Why? Because “big data” and advanced problem solving skills inform decision making and innovation for all organisations. Scientists are transforming the research frontier by using machine learning techniques to find Higgs bosons, classify galaxies or unravel genetic codes. Businesses are using the same techniques to identify credit card fraud, perform social network analysis and to develop automatic approaches to targeted marketing. In this course, you will become familiar with all major modern approaches to data science, including machine learning techniques and big data analysis strategies. Critically, students in this course will learn via an innovative and multi-disciplinary approach to problem solving. After a basic introduction to the different types of data analysis problem, students will be introduced to a variety of algorithms from the research frontier. To keep the course accessible to a broad audience, no mathematical knowledge will be assumed, and students will instead gain a hands-on, intuitive knowledge of how the algorithms work by using simple spreadsheet examples. A wide variety of problems from physics, chemistry, biology, health sciences and business will be used to encourage students to view problems through the lens of a different discipline; this will enhance your ability to spot innovative solutions to research problems in your own field. For business students, it will give you an ability to determine what your company or employer needs to remain competitive. Through this topic, you will develop transferable skills that will allow you to connect science to everyday issues, and you will also learn how to use real-world problems to solve new problems in science.