The automated identification of significant patterns in data has become an essential tool in many scientific processes that require an analysis of large data sets. Recently, a large number of statistical and algorithmic developments have been based on machine learning formalisim. The primary objective of this course is to provide a solid mathematical foundation of the fundamental concepts applied within this developments.  This course is designed for graduate students majoring in mathematics as well as mathematically inclined graduate engineering students. At the end of this course, the students will:

• Have a solid background in mathematical foundations of basic machine learning  concepts.
• Gain a deep understanding of the basic items in machine learning and connect practical questions arising from the use of machine learning with fundamental choices in the mathematical model.
• Use the computational tools  available to implement key machine learning algorithms.