Mathematical Tools for Data Science

This course presents the mathematical intuition, theory, and techniques driving the numerical computation methods used for processing and analyzing data in various real-life problems. Topics include dimensionality reduction, linear and non-linear approximation, frequency and wavelet analysis, and a glimpse into the mathematics of deep neural networks, classification, large-scale and high-performance numerical computing. Each topic will be motivated by a data analysis challenge, introduce the mathematical intuition, theory and techniques used to address it, and conclude with a coding component with real data.