Discrete Mathematics for Data Science provides an early course in both data science and discrete mathematics, focusing on how a deeper understanding of the former can unlock a more effective implementation of the latter. Students of data science come from a variety of disciplines, with Business, Statistics, Computer Science, Economics, and Psychology among the departments offering courses on the subject. Therefore, for many students, data science is considered a means of insight into a particular field of interest, with the study of its underlying discrete mathematics not a primary objective.

This book covers the topics of discrete mathematics relevant to students of data science, offering an introduction to both the theoretical and practical elements required to be a successful data scientist. The relaxed, accessible style makes it a perfect textbook for undergraduates.

Features

· Numerous exercises and examples.

· Ideal as a textbook for a discrete mathematics course, for data science and computer science students.

· Source code and solutions provided as a supplementary resource.