Algorithmic Thinking
Download Algorithmic Thinking full books in PDF, epub, and Kindle. Read online free Algorithmic Thinking ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Daniel Zingaro |
| Publisher | : No Starch Press |
| Total Pages | : 409 |
| Release | : 2020-12-15 |
| Genre | : Computers |
| ISBN | : 1718500807 |
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 | : Anany Levitin |
| Publisher | : OUP USA |
| Total Pages | : 280 |
| Release | : 2011-10-14 |
| Genre | : Computers |
| ISBN | : 0199740445 |
Algorithmic puzzles are puzzles involving well-defined procedures for solving problems. This book will provide an enjoyable and accessible introduction to algorithmic puzzles that will develop the reader's algorithmic thinking. The first part of this book is a tutorial on algorithm design strategies and analysis techniques. Algorithm design strategies — exhaustive search, backtracking, divide-and-conquer and a few others — are general approaches to designing step-by-step instructions for solving problems. Analysis techniques are methods for investigating such procedures to answer questions about the ultimate result of the procedure or how many steps are executed before the procedure stops. The discussion is an elementary level, with puzzle examples, and requires neither programming nor mathematics beyond a secondary school level. Thus, the tutorial provides a gentle and entertaining introduction to main ideas in high-level algorithmic problem solving. The second and main part of the book contains 150 puzzles, from centuries-old classics to newcomers often asked during job interviews at computing, engineering, and financial companies. The puzzles are divided into three groups by their difficulty levels. The first fifty puzzles in the Easier Puzzles section require only middle school mathematics. The sixty puzzle of average difficulty and forty harder puzzles require just high school mathematics plus a few topics such as binary numbers and simple recurrences, which are reviewed in the tutorial. All the puzzles are provided with hints, detailed solutions, and brief comments. The comments deal with the puzzle origins and design or analysis techniques used in the solution. The book should be of interest to puzzle lovers, students and teachers of algorithm courses, and persons expecting to be given puzzles during job interviews.
| Author | : Aristides Bouras |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 908 |
| Release | : 2024-06-14 |
| Genre | : Computers |
| ISBN | : 1836209266 |
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 | : Peter J. Denning |
| Publisher | : MIT Press |
| Total Pages | : 266 |
| Release | : 2019-05-14 |
| Genre | : Computers |
| ISBN | : 0262353423 |
This pocket-sized introduction to computational thinking and problem-solving traces its genealogy centuries before the digital computer. A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation. Eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, “computational thinking” has become part of the K–12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview—tracing a genealogy that begins centuries before digital computers and portraying computational thinking as the pioneers of computing have described it. The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as “computers”) who performed complex calculations as teams engaged in CT long before electronic computers. In each chapter, the author identify different dimensions of today's highly developed CT: • Computational Methods • Computing Machines • Computing Education • Software Engineering • Computational Science • Design Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.
| Author | : Paolo Ferragina |
| Publisher | : Springer |
| Total Pages | : 176 |
| Release | : 2018-08-21 |
| Genre | : Computers |
| ISBN | : 331997940X |
This book offers a gentle motivation and introduction to computational thinking, in particular to algorithms and how they can be coded to solve significant, topical problems from domains such as finance, cryptography, Web search, and data compression. The book is 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. While the authors assume only basic mathematical knowledge, they uphold the scientific rigor that is indispensable for transforming general ideas into executable algorithms. A supporting website contains examples and Python code for implementing the algorithms in the book.
| Author | : Aristides S. Bouras |
| Publisher | : |
| Total Pages | : 746 |
| Release | : 2019-12-17 |
| Genre | : |
| ISBN | : 9781671594364 |
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 | : Zhiwei Xu |
| Publisher | : Springer Nature |
| Total Pages | : 338 |
| Release | : 2022-01-01 |
| Genre | : Computers |
| ISBN | : 9811638489 |
This textbook is intended as a textbook for one-semester, introductory computer science courses aimed at undergraduate students from all disciplines. Self-contained and with no prerequisites, it focuses on elementary knowledge and thinking models. The content has been tested in university classrooms for over six years, and has been used in summer schools to train university and high-school teachers on teaching introductory computer science courses using computational thinking. This book introduces computer science from a computational thinking perspective. In computer science the way of thinking is characterized by three external and eight internal features, including automatic execution, bit-accuracy and abstraction. The book is divided into chapters on logic thinking, algorithmic thinking, systems thinking, and network thinking. It also covers societal impact and responsible computing material – from ICT industry to digital economy, from the wonder of exponentiation to wonder of cyberspace, and from code of conduct to best practices for independent work. The book’s structure encourages active, hands-on learning using the pedagogic tool Bloom's taxonomy to create computational solutions to over 200 problems of varying difficulty. Students solve problems using a combination of thought experiment, programming, and written methods. Only 300 lines of code in total are required to solve most programming problems in this book.
| Author | : Daniel Zingaro |
| Publisher | : No Starch Press |
| Total Pages | : 392 |
| Release | : 2021-06-29 |
| Genre | : Computers |
| ISBN | : 1718501331 |
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 | : John Maeda |
| Publisher | : Penguin |
| Total Pages | : 242 |
| Release | : 2019-11-12 |
| Genre | : Technology & Engineering |
| ISBN | : 0399564438 |
Visionary designer and technologist John Maeda defines the fundamental laws of how computers think, and why you should care even if you aren't a programmer. "Maeda is to design what Warren Buffett is to finance." --Wired John Maeda is one of the world's preeminent interdisciplinary thinkers on technology and design. In How to Speak Machine, he offers a set of simple laws that govern not only the computers of today, but the unimaginable machines of the future. Technology is already more powerful than we can comprehend, and getting more powerful at an exponential pace. Once set in motion, algorithms never tire. And when a program's size, speed, and tirelessness combine with its ability to learn and transform itself, the outcome can be unpredictable and dangerous. Take the seemingly instant transformation of Microsoft's chatbot Tay into a hate-spewing racist, or how crime-predicting algorithms reinforce racial bias. How to Speak Machine provides a coherent framework for today's product designers, business leaders, and policymakers to grasp this brave new world. Drawing on his wide-ranging experience from engineering to computer science to design, Maeda shows how businesses and individuals can identify opportunities afforded by technology to make world-changing and inclusive products--while avoiding the pitfalls inherent to the medium.
| Author | : Jeff Edmonds |
| Publisher | : Cambridge University Press |
| Total Pages | : 409 |
| Release | : 2008-05-19 |
| Genre | : Computers |
| ISBN | : 1139471759 |
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.
