Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them.

chapter Chapter 1|12 pages


ByNathan Carter

chapter Chapter 2|30 pages

Programming with Data

BySean Raleigh

chapter Chapter 3|55 pages

Linear Algebra

ByJeffery Leader

chapter Chapter 4|86 pages

Basic Statistics

ByDavid White

chapter Chapter 5|53 pages


ByAmy S. Wagaman

chapter Chapter 6|52 pages

Operations Research

ByAlice Paul, Susan Martonosi

chapter Chapter 7|47 pages

Dimensionality Reduction

BySofya Chepushtanova, Elin Farnell, Eric Kehoe, Michael Kirby, Henry Kvinge

chapter Chapter 8|69 pages

Machine Learning

ByMahesh Agarwal, Nathan Carter, David Oury

chapter Chapter 9|32 pages

Deep Learning

BySamuel S. Watson

chapter Chapter 10|34 pages

Topological Data Analysis

ByHenry Adams, Johnathan Bush, Joshua Mirth