Algorithmic Thinking, 2nd Edition (Paperback)

Daniel Zingaro

ISBN 10: 1718503229 / ISBN 13: 9781718503229

Edité par No Starch Press,US, San Francisco, 2024

A propos de cet article

Paperback. Get in the game and learn essential computer algorithms by solving competitive programming problems, in the fully revised second edition of the bestselling original. (Still no math required!)Get in the game and learn essential computer algorithms by solving competitive programming problems, in the fully revised second edition of the bestselling original. (Still no math required!)Are you hitting a wall with data structures and algorithms? Whether you're a student prepping for coding interviews or an independent learner, this book is your essential guide to efficient problem-solving in programming.UNLOCK THE POWER OF DATA STRUCTURES & ALGORITHMS-Learn the intricacies of hash tables, recursion, dynamic programming, trees, graphs, and heaps. Become proficient in choosing and implementing the best solutions for any coding challenge.REAL-WORLD, COMPETITION-PROVEN CODE EXAMPLES-The programs and challenges in this book aren't just theoretical-they're drawn from real programming competitions. Train with problems that have tested and honed the skills of coders around the world.GET INTERVIEW-READY-Prepare yourself for coding interviews with practice exercises that help you think algorithmically, weigh different solutions, and implement the best choices efficiently.WRITTEN IN C, USEFUL ACROSS LANGUAGES-The code examples are written in C and designed for clarity and accessibility to those familiar with languages like C++, Java, or Python. If you need help with the C code, no problem- We've got recommended reading, too.Algorithmic Thinking is the complete package, providing the solid foundation you need to elevate your coding skills to the next level. "An introduction to solving problems with algorithms and data structures, using competitive programming examples. Topics covered include recursion, dynamic programming, graphs, greedy algorithms, heaps, hash tables, segment trees, and other data structures for efficiently handling data"-Provided by publisher"-- Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781718503229

Détails bibliographiques

Titre : Algorithmic Thinking, 2nd Edition (Paperback)

Éditeur : No Starch Press,US, San Francisco

Date d'édition : 2024

Reliure : Paperback

Etat : new

Edition : 2ème Édition

A propos de ce titre

Synopsis :

Get in the game and learn essential computer algorithms by solving competitive programming problems, in the fully revised second edition of the bestselling original. (Still no math required!)

Are you hitting a wall with data structures and algorithms? Whether you’re a student prepping for coding interviews or an independent learner, this book is your essential guide to efficient problem-solving in programming.

UNLOCK THE POWER OF DATA STRUCTURES & ALGORITHMS:
Learn the intricacies of hash tables, recursion, dynamic programming, trees, graphs, and heaps. Become proficient in choosing and implementing the best solutions for any coding challenge.

REAL-WORLD, COMPETITION-PROVEN CODE EXAMPLES:
The programs and challenges in this book aren’t just theoretical—they’re drawn from real programming competitions. Train with problems that have tested and honed the skills of coders around the world.

GET INTERVIEW-READY:
Prepare yourself for coding interviews with practice exercises that help you think algorithmically, weigh different solutions, and implement the best choices efficiently.

WRITTEN IN C, USEFUL ACROSS LANGUAGES:
The code examples are written in C and designed for clarity and accessibility to those familiar with languages like C++, Java, or Python. If you need help with the C code, no problem: We’ve got recommended reading, too.

Algorithmic Thinking is the complete package, providing the solid foundation you need to elevate your coding skills to the next level.

À propos de l?auteur:

Dr. Daniel Zingaro is an award-winning associate professor of mathematical and computational sciences at the University of Toronto Mississauga. He is well known for his uniquely interactive approach to teaching and internationally recognized for his expertise in active learning. He is also the author of Learn to Code by Solving Problems (No Starch Press) and co-author of Learn AI-Assisted Python Programming.