This is a textbook in probability in high dimensions with a view toward applications in data sciences. It is intended for doctoral and advanced masters students

This is a textbook in probability in high dimensions with a view toward applications in data sciences. It is intended for doctoral and advanced masters students and beginning researchers in mathematics, statistics, electrical engineering, computational biology and related areas, who are looking to expand their knowledge of theoretical methods used in modern research in data sciences. A typical graduate probability course is no longer sufficient to acquire the level of mathematical sophistication that is expected from a beginning researcher in data sciences today. The proposed book intends to partially cover this gap. It presents some of the key probabilistic methods and results that may form an essential toolbox for a mathematical data scientist. This book can be used as a textbook for a basic second course in probability with a view toward data science applications. It is also suitable for self-study.