High Dimensional Probability

The course will expose you to basic high-dimensional probability theory and concentration inequalities in data science and machine learning. This course will contain mathematical findings from the past 20-30 years, which are more recent than those typically covered in undergraduate coursework. You are welcome to take this course if you are interested in probability theory and intending to pursue research in data science or machine learning in the future. If you have a passion for mathematics, you might be pleased to know that this course offers proximity to the frontier of advanced mathematics and mathematical research; if you are pursuing a career in data science or machine learning, you might be pleased to know that this course provides essential preparation for understanding a substantial amount of machine learning literature. Students are expected to have *mastered* MH1201, MH2500 and MH3100.