Discrete Math for Computer Science Students

This text teaches all the math, with the exception of linear algebra, that is needed to succeed in computer science.

**Tag(s):**
Discrete Mathematics

**Publication date**: 13 Mar 2010

**ISBN-10**:
013212271

**ISBN-13**:
9780132122719

**Paperback**:
344 pages

**Views**: 9,378

Discrete Math for Computer Science Students

This text teaches all the math, with the exception of linear algebra, that is needed to succeed in computer science.

Book Description at Amazon:

The download links are available at the bottom of the course webpage.

"Discrete Mathematics for Computer Science" is the perfect text to combine the fields of mathematics and computer science. Written by leading academics in the field of computer science, readers will gain the skills needed to write and understand the concept of proof. This text teaches all the math, with the exception of linear algebra, that is needed to succeed in computer science. The book explores the topics of basic combinatorics, number and graph theory, logic and proof techniques, and many more. Appropriate for large or small class sizes or self study for the motivated professional reader. Assumes familiarity with data structures. Early treatment of number theory and combinatorics allow readers to explore RSA encryption early and also to encourage them to use their knowledge of hashing and trees (from CS2) before those topics are covered in this course.

The download links are available at the bottom of the course webpage.

Tweet

About The Author(s)

Kenneth P. Bogart (1943 - 2005) was a professor in the Mathematics Department at Dartmouth College. Before his death in 2005, he was in the final stages of completing an NSF-sponsored project about the teaching of combinatorics through Guided Discovery.

Robert Lewis (Scot) Drysdale, III is a Professor in the Department of Computer Science at Dartmouth College. He's currently working on applications of Voronoi diagrams and Delaunay triangulations. He retired from his teaching position on April 2016.

Clifford Stein is Professor of IEOR and of Computer Science at Columbia University. His research interests include the design and analysis of algorithms, combinatorial optimization, operations research, network algorithms, scheduling, algorithm engineering and computational biology.

Book Categories

Computer Science
Introduction to Computer Science
Introduction to Computer Programming
Algorithms and Data Structures
Artificial Intelligence
Computer Vision
Machine Learning
Neural Networks
Game Development and Multimedia
Data Communication and Networks
Coding Theory
Computer Security
Information Security
Cryptography
Information Theory
Computer Organization and Architecture
Operating Systems
Image Processing
Parallel Computing
Concurrent Programming
Relational Database
Document-oriented Database
Data Mining
Big Data
Data Science
Digital Libraries
Compiler Design and Construction
Functional Programming
Logic Programming
Object Oriented Programming
Formal Methods
Software Engineering
Agile Software Development
Information Systems
Geographic Information System (GIS)

Mathematics
Mathematics
Algebra
Abstract Algebra
Linear Algebra
Number Theory
Numerical Methods
Precalculus
Calculus
Differential Equations
Category Theory
Proofs
Discrete Mathematics
Theory of Computation
Graph Theory
Real Analysis
Complex Analysis
Probability
Statistics
Game Theory
Queueing Theory
Operations Research
Computer Aided Mathematics

Supporting Fields
Web Design and Development
Mobile App Design and Development
System Administration
Cloud Computing
Electric Circuits
Embedded System
Signal Processing
Integration and Automation
Network Science
Project Management

Operating System
Programming/Scripting
Ada
Assembly
C / C++
Common Lisp
Forth
Java
JavaScript
Lua
Microsoft .NET
Rexx
Perl
PHP
Python
R
Rebol
Ruby
Scheme
Tcl/Tk

Miscellaneous
Sponsors