The field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience. After initial successes within the domain of games such as chess or backgammon, research in machine learning now plays an essential role in dozens of applications that affect us on a daily basis: movie recommender systems on Netflix, automated speech recognition on your home PC, autonomous vehicles in perilous terrain, face detection systems in cameras, spam detection in your inbox -- and of course search engines as the gateway to the internet. In the last twenty years, machine learning has not only expanded into an essential technology, it has also developed a mature theoretical foundation. This course will provide a broad introduction to the theory and practice of machine learning. It will cover learning algorithms such as neural networks and support vector machines and explore applications such as automatic spam-filtering and web-search ranking.