Algorithmic Thinking 2nd Edition
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Author |
: Daniel Zingaro |
Publisher |
: No Starch Press |
Total Pages |
: 409 |
Release |
: 2020-12-15 |
ISBN-10 |
: 9781718500808 |
ISBN-13 |
: 1718500807 |
Rating |
: 4/5 (08 Downloads) |
Synopsis Algorithmic Thinking by : Daniel Zingaro
A hands-on, problem-based introduction to building algorithms and data structures to solve problems with a computer. Algorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems. Line-by-line breakdowns of the code will teach you how to use algorithms and data structures like: The breadth-first search algorithm to find the optimal way to play a board game or find the best way to translate a book Dijkstra's algorithm to determine how many mice can exit a maze or the number of fastest routes between two locations The union-find data structure to answer questions about connections in a social network or determine who are friends or enemies The heap data structure to determine the amount of money given away in a promotion The hash-table data structure to determine whether snowflakes are unique or identify compound words in a dictionary NOTE: Each problem in this book is available on a programming-judge website. You'll find the site's URL and problem ID in the description. What's better than a free correctness check?
Author |
: Aristides Bouras |
Publisher |
: Packt Publishing Ltd |
Total Pages |
: 908 |
Release |
: 2024-06-14 |
ISBN-10 |
: 9781836209263 |
ISBN-13 |
: 1836209266 |
Rating |
: 4/5 (63 Downloads) |
Synopsis Python and Algorithmic Thinking for the Complete Beginner by : Aristides Bouras
Unlock the power of Python with this comprehensive guide, “Python and Algorithmic Thinking for the Complete Beginner.” It covers everything from computer basics to advanced decision and loop control structures. Key Features Comprehensive coverage from basic computer operations to advanced programming concepts Step-by-step progression of each topic, along with tips and tricks to enhance coding efficiency In-depth exploration of Python and algorithmic thinking with exercises and practical examples Book DescriptionThis course is meticulously designed to take beginners on a journey through the fascinating world of Python programming and algorithmic thinking. The initial chapters lay a strong foundation, starting with the basics of how computers operate, moving into Python programming, and familiarizing learners with integrated development environments like IDLE and Visual Studio Code. Further, the course delves into essential programming constructs such as variables, constants, input/output handling, and operators. You'll gain practical experience with trace tables, sequence control structures, and decision control structures through comprehensive exercises and examples. The curriculum emphasizes hands-on learning with chapters dedicated to manipulating numbers, strings, and understanding complex mathematical expressions. By mastering these concepts, you'll be well-prepared to tackle more advanced topics. The final chapters introduce you to object-oriented programming and file manipulation, rounding out your skill set. Throughout the course, practical tips and tricks are provided to enhance your coding efficiency and problem-solving skills. By the end of this course, you will have a robust understanding of Python programming and the ability to apply algorithmic thinking to solve real-world problems.What you will learn Understand how computers work and the basics of Python programming Install and use integrated development environments (IDEs) Develop skills in decision and loop control structures Manipulate data using lists, dictionaries, and strings Apply algorithmic thinking to solve complex problems Gain proficiency in object-oriented programming & file manipulation Who this book is for This course is ideal for absolute beginners with no prior programming experience. Basic computer literacy is required, but no specific knowledge of programming or algorithms is necessary. It is also suitable for individuals looking to refresh their Python skills and enhance their understanding of algorithmic thinking. High school and college students interested in programming, professionals seeking to upskill, and hobbyists eager to learn a new programming language will all find value in this course.
Author |
: Jeff Edmonds |
Publisher |
: Cambridge University Press |
Total Pages |
: 409 |
Release |
: 2008-05-19 |
ISBN-10 |
: 9781139471756 |
ISBN-13 |
: 1139471759 |
Rating |
: 4/5 (56 Downloads) |
Synopsis How to Think About Algorithms by : Jeff Edmonds
This textbook, for second- or third-year students of computer science, presents insights, notations, and analogies to help them describe and think about algorithms like an expert, without grinding through lots of formal proof. Solutions to many problems are provided to let students check their progress, while class-tested PowerPoint slides are on the web for anyone running the course. By looking at both the big picture and easy step-by-step methods for developing algorithms, the author guides students around the common pitfalls. He stresses paradigms such as loop invariants and recursion to unify a huge range of algorithms into a few meta-algorithms. The book fosters a deeper understanding of how and why each algorithm works. These insights are presented in a careful and clear way, helping students to think abstractly and preparing them for creating their own innovative ways to solve problems.
Author |
: Daniel Zingaro |
Publisher |
: No Starch Press |
Total Pages |
: 481 |
Release |
: 2024-01-23 |
ISBN-10 |
: 9781718503229 |
ISBN-13 |
: 1718503229 |
Rating |
: 4/5 (29 Downloads) |
Synopsis Algorithmic Thinking, 2nd Edition by : Daniel Zingaro
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.
Author |
: Daniel Zingaro |
Publisher |
: No Starch Press |
Total Pages |
: 392 |
Release |
: 2021-06-29 |
ISBN-10 |
: 9781718501331 |
ISBN-13 |
: 1718501331 |
Rating |
: 4/5 (31 Downloads) |
Synopsis Learn to Code by Solving Problems by : Daniel Zingaro
Learn to Code by Solving Problems is a practical introduction to programming using Python. It uses coding-competition challenges to teach you the mechanics of coding and how to think like a savvy programmer. Computers are capable of solving almost any problem when given the right instructions. That’s where programming comes in. This beginner’s book will have you writing Python programs right away. You’ll solve interesting problems drawn from real coding competitions and build your programming skills as you go. Every chapter presents problems from coding challenge websites, where online judges test your solutions and provide targeted feedback. As you practice using core Python features, functions, and techniques, you’ll develop a clear understanding of data structures, algorithms, and other programming basics. Bonus exercises invite you to explore new concepts on your own, and multiple-choice questions encourage you to think about how each piece of code works. You’ll learn how to: Run Python code, work with strings, and use variables Write programs that make decisions Make code more efficient with while and for loops Use Python sets, lists, and dictionaries to organize, sort, and search data Design programs using functions and top-down design Create complete-search algorithms and use Big O notation to design more efficient code By the end of the book, you’ll not only be proficient in Python, but you’ll also understand how to think through problems and tackle them with code. Programming languages come and go, but this book gives you the lasting foundation you need to start thinking like a programmer.
Author |
: Aristides S. Bouras |
Publisher |
: |
Total Pages |
: 746 |
Release |
: 2019-12-17 |
ISBN-10 |
: 1671594363 |
ISBN-13 |
: 9781671594364 |
Rating |
: 4/5 (63 Downloads) |
Synopsis C# and Algorithmic Thinking for the Complete Beginner (2nd Edition) by : Aristides S. Bouras
Thoroughly revised for the latest version of C#, this book explains basic concepts in a clear and explicit way that takes very seriously one thing for granted-that the reader knows nothing about computer programming. Addressed to anyone who has no prior programming knowledge or experience, but a desire to learn programming with C#, it teaches the first thing that every novice programmer needs to learn, which is Algorithmic Thinking. Algorithmic Thinking involves more than just learning code. It is a problem-solving process that involves learning how to code. This edition contains all the popular features of the previous edition and adds a significant number of exercises, as well as extensive revisions and updates. Apart from C# 's arrays, it now also covers dictionaries, while a brand new section provides an effective introduction to the next field that a programmer needs to work with, which is Object Oriented Programming (OOP). This book has a class course structure with questions and exercises at the end of each chapter so you can test what you have learned right away and improve your comprehension. With 250 solved and 450 unsolved exercises, 475 true/false, about 150 multiple choice, and 200 review questions and crosswords (the solutions and the answers to which can be found on the Internet), this book is ideal for novices or average programmers, for self-study high school students first-year college or university students teachers professors anyone who wants to start learning or teaching computer programming using the proper conventions and techniques
Author |
: Daniel Zingaro |
Publisher |
: No Starch Press |
Total Pages |
: 481 |
Release |
: 2024-01-23 |
ISBN-10 |
: 9781718503236 |
ISBN-13 |
: 1718503237 |
Rating |
: 4/5 (36 Downloads) |
Synopsis Algorithmic Thinking, 2nd Edition by : Daniel Zingaro
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.
Author |
: Steven S Skiena |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 742 |
Release |
: 2009-04-05 |
ISBN-10 |
: 9781848000704 |
ISBN-13 |
: 1848000707 |
Rating |
: 4/5 (04 Downloads) |
Synopsis The Algorithm Design Manual by : Steven S Skiena
This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java
Author |
: Roland Backhouse |
Publisher |
: John Wiley & Sons |
Total Pages |
: 434 |
Release |
: 2011-10-24 |
ISBN-10 |
: 9780470684535 |
ISBN-13 |
: 0470684534 |
Rating |
: 4/5 (35 Downloads) |
Synopsis Algorithmic Problem Solving by : Roland Backhouse
An entertaining and captivating way to learn the fundamentals of using algorithms to solve problems The algorithmic approach to solving problems in computer technology is an essential tool. With this unique book, algorithm guru Roland Backhouse shares his four decades of experience to teach the fundamental principles of using algorithms to solve problems. Using fun and well-known puzzles to gradually introduce different aspects of algorithms in mathematics and computing. Backhouse presents you with a readable, entertaining, and energetic book that will motivate and challenge you to open your mind to the algorithmic nature of problem solving. Provides a novel approach to the mathematics of problem solving focusing on the algorithmic nature of problem solving Uses popular and entertaining puzzles to teach you different aspects of using algorithms to solve mathematical and computing challenges Features a theory section that supports each of the puzzles presented throughout the book Assumes only an elementary understanding of mathematics Let Roland Backhouse and his four decades of experience show you how you can solve challenging problems with algorithms!
Author |
: Paolo Ferragina |
Publisher |
: Springer Nature |
Total Pages |
: 204 |
Release |
: 2024 |
ISBN-10 |
: 9783031599224 |
ISBN-13 |
: 3031599225 |
Rating |
: 4/5 (24 Downloads) |
Synopsis Computational Thinking by : Paolo Ferragina
A topic important to pre-university as well as to university curricula for computing and various other disciplines, computational thinking examines processes in the mind engaged in addressing problems such that answers/solutions can be formulated as computational increments and then, algorithms. This revised and updated textbook/guide offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical real problems from domains such as finance, cryptography, web search, data compression and bioinformatics. Although the work assumes only basic mathematical knowledge, it still upholds the scientific rigor indispensable for transforming general ideas into executable algorithms, giving several solutions to common tasks, taken from topics of our everyday world. Topics and features: Provides a readily accessible introduction, suitable for undergraduate and high-school students, as well as for self-study Organizes content neatly and conveniently by application or problem area Offers a helpful supporting website with Python code that implements the algorithms in the book Anchors the content practically, examining an excellent variety of modern topics in a concise volume Assumes knowledge of only basic computing skills as a prerequisite Written by highly experienced lecturers, as well as researchers of world renown A unique and reader-friendly textbook/reference, the title is eminently suitable for undergraduate students in computer science, engineering, and applied mathematics, university students in other fields, high-school students with an interest in STEM subjects, and professionals who want an insight into algorithmic solutions and the related mindset. Paolo Ferragina is professor of computer science at the Sant’Anna School of Advanced Studies, Italy, and Fabrizio Luccio is an emeritus professor of computer science at the University of Pisa, Italy.