Math for Programming
Book Details
Format
Paperback / Softback
ISBN-10
171850358X
ISBN-13
9781718503588
Publisher
No Starch Press,US
Imprint
No Starch Press,US
Country of Manufacture
US
Country of Publication
GB
Publication Date
Apr 22nd, 2025
Print length
504 Pages
Weight
946 grams
Dimensions
23.40 x 18.00 x 3.20 cms
Product Classification:
Computer programming / software developmentMaths for computer scientists
Ksh 8,100.00
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This book summarizes all the core mathematical topics a typical professional software engineer needs to know. In condensing the various concepts covered in an undergraduate computer science program into a single volume, it provides an excellent starting point for independent study, or a refresher for those who haven't been in a classroom for years. Early chapters cover preliminary subjects like number representation systems, set theory, and Boolean algebra, followed by a dive into the field of discrete mathematics, including functions, induction proofs, number theory, combinatorics, graphs, and trees. Later sections examine essential topics in probability, statistics, linear algebra, and calculus. Rather than confine itself to abstract theory, the book focuses on practical applications and numerical methods at the level typically encountered by working software developers. In addition, hands-on code examples in Python and C make the topics concrete.
This book summarizes all the core mathematical topics a typical professional software engineer needs to know. In condensing the various concepts covered in an undergraduate computer science program into a single volume, it provides an excellent starting point for independent study, or a refresher for those who haven''t been in a classroom for years. Early chapters cover preliminary subjects like number representation systems, set theory, and Boolean algebra, followed by a dive into the field of discrete mathematics, including functions, induction proofs, number theory, combinatorics, graphs, and trees. Later sections examine essential topics in probability, statistics, linear algebra, and calculus. Rather than confine itself to abstract theory, the book focuses on practical applications and numerical methods at the level typically encountered by working software developers. In addition, hands-on code examples in Python and C make the topics concrete.
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