The Advanced Machine Learning investigates the question "how can we build computer programs that automatically improve their performance through experience?" This course is designed to give students an advanced grounding in the methods, theory, mathematics and algorithms needed to do research and applications in machine learning. The topics of the course draw from machine learning, classical statistics, data mining, Bayesian statistics and information theory and other areas with focus on the latest development in the past decade in these areas. This course is intended to give students abundant hands-on experience with different machine learning algorithms and large-scale data sets. Compared to introductory courses in machine learning, this course has several distinguishing features: It investigates more advanced techniques and algorithms; is more concerned with large-scale data sets; focuses on specific application areas (in particular system health management, text processing and mobile user behavior modeling); and has a focus in which recent papers are presented and discussed.