Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domains Key FeaturesDevelop logical reasoning and problem-solving skills that will help you tackle complex problemsExplore core computer science concepts and important computational thinking elements using practical examplesFind out how to identify the best-suited algorithmic solution for your problemBook Description Computational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence. This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You’ll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions. By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development. What you will learnFind out how to use decomposition to solve problems through visual representationEmploy pattern generalization and abstraction to design solutionsBuild analytical skills required to assess algorithmic solutionsUse computational thinking with Python for statistical analysisUnderstand the input and output needs for designing algorithmic solutionsUse computational thinking to solve data processing problemsIdentify errors in logical processing to refine your solution designApply computational thinking in various domains, such as cryptography, economics, and machine learningWho this book is for This book is for students, developers, and professionals looking to develop problem-solving skills and tactics involved in writing or debugging software programs and applications. Familiarity with Python programming is required.

Write popular DeFi and NFT smart contracts with Vyper, a Pythonic programming language, and integrate blockchain with real-world applications using Python Key Features Use the world's easiest programming language to build web3 applications Write common smart contracts like decentralized exchanges, NFT marketplaces, and lending applications Unlock deeper levels of insights with technologies relating to blockchain, such as IPFS and Layer 2 Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWe are living in the age of decentralized fi nance and NFTs. People swap tokens on Uniswap, borrow assets from Aave, send payments with stablecoins, trade art NFTs on OpenSea, and more. To build applications of this kind, you need to know how to write smart contracts. This comprehensive guide will help you explore all the features of Vyper, a programming language designed to write smart contracts. You’ll also explore the web3.py library. As you progress, you’ll learn how to connect to smart contracts, read values, and create transactions. To make sure your foundational knowledge is strong enough, the book guides you through Ape Framework, which can help you create decentralized exchanges, NFT marketplaces, voting applications, and more. Each project provides invaluable insights and hands-on experience, equipping you with the skills you need to build real-world blockchain solutions. By the end of this book, you’ll be well versed with writing common Web3 applications such as a decentralized exchange, an NFT marketplace, a voting application, and more.What you will learn Understand blockchain and smart contracts Learn how to write smart contracts with Vyper Explore how to use the web3.py library and Ape Framework Discover related technologies such as Layer 2 and IPFS Gain a step-by-step guide to writing an automated market maker (AMM) decentralized exchange (DEX) smart contract Build innovative, interactive, and token-gated Web3 NFT applications Who this book is for This blockchain book is for developers interested in understanding blockchain and smart contracts. It is suitable for both technology enthusiasts looking to explore blockchain technology and programmers who aspire to become smart contract engineers. Basic knowledge of GNU/Linux and Python programming is mandatory to get started with this book.

A guide for educators to incorporate computational thinking—a set of cognitive skills applied to problem solving—into a broad range of subjects. Computational thinking—a set of mental and cognitive tools applied to problem solving—is a fundamental skill that all of us (and not just computer scientists) draw on. Educators have found that computational thinking enhances learning across a range of subjects and reinforces students’ abilities in reading, writing, and arithmetic. This book offers a guide for incorporating computational thinking into middle school and high school classrooms, presenting a series of activities, projects, and tasks that employ a range of pedagogical practices and cross a variety of content areas. As students problem solve, communicate, persevere, work as a team, and learn from mistakes, they develop a concrete understanding of the abstract principles used in computer science to create code and other digital artifacts. The book guides students and teachers to integrate computer programming with visual art and geometry, generating abstract expressionist–style images; construct topological graphs that represent the relationships between characters in such literary works as Harry Potter and the Sorcerer’s Stone and Romeo and Juliet; apply Newtonian physics to the creation of computer games; and locate, analyze, and present empirical data relevant to social and political issues. Finally, the book lists a variety of classroom resources, including the programming languages Scratch (free to all) and Codesters (free to teachers). An accompanying website contains the executable programs used in the book’s activities.

This is a guide to the teaching of computing and coding in primary schools, and an exploration of how children develop their computational thinking. It covers all areas of the National Curriculum for primary computing and offers insight into effective teaching. The text considers three strands of computer science, digital literacy and information technology. The teaching of coding is especially challenging for primary teachers, so it highlights learning on this, giving practical examples of how this can be taught. For all areas of the computing curriculum the text also provides guidance on planning age-appropriate activities with step-by-step guides and details of educationally appropriate software and hardware. This book helps you to connect what you need to teach with how it can be taught, and opens up opportunities in the new curriculum for creative and imaginative teaching. It also includes the full National Curriculum Programme of Study for Computing, key stages 1 and 2 as a useful reference for trainee teachers.

Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy m

While the growth of computational thinking has brought new awareness to the importance of computing education, it has also created new challenges. Many educational initiatives focus solely on the programming aspects, such as variables, loops, conditionals, parallelism, operators, and data handling, divorcing computing from real-world contexts and applications. This decontextualization threatens to make learners believe that they do not need to learn computing, as they cannot envision a future in which they will need to use it, just as many see math and physics education as unnecessary. The Handbook of Research on Tools for Teaching Computational Thinking in P-12 Education is a cutting-edge research publication that examines the implementation of computational thinking into school curriculum in order to develop creative problem-solving skills and to build a computational identity which will allow for future STEM growth. Moreover, the book advocates for a new approach to computing education that argues that while learning about computing, young people should also have opportunities to create with computing, which will have a direct impact on their lives and their communities. Featuring a wide range of topics such as assessment, digital teaching, and educational robotics, this book is ideal for academicians, instructional designers, teachers, education professionals, administrators, researchers, and students.

Computational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and 'code explained' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy required for any modern biologist to adopt computational approaches in their research with confidence.

The education system is constantly growing and developing as more ways to teach and learn are implemented into the classroom. Recently, there has been a growing interest in teaching computational thinking with schools all over the world introducing it to the curriculum due to its ability to allow students to become proficient at problem solving using logic, an essential life skill. In order to provide the best education possible, it is imperative that computational thinking strategies, along with programming skills and the use of robotics in the classroom, be implemented in order for students to achieve maximum thought processing skills and computer competencies. The Research Anthology on Computational Thinking, Programming, and Robotics in the Classroom is an all-encompassing reference book that discusses how computational thinking, programming, and robotics can be used in education as well as the benefits and difficulties of implementing these elements into the classroom. The book includes strategies for preparing educators to teach computational thinking in the classroom as well as design techniques for incorporating these practices into various levels of school curriculum and within a variety of subjects. Covering topics ranging from decomposition to robot learning, this book is ideal for educators, computer scientists, administrators, academicians, students, and anyone interested in learning more about how computational thinking, programming, and robotics can change the current education system.

This This book is open access under a CC BY 4.0 license.This book offers a comprehensive guide, covering every important aspect of computational thinking education. It provides an in-depth discussion of computational thinking, including the notion of perceiving computational thinking practices as ways of mapping models from the abstraction of data and process structures to natural phenomena. Further, it explores how computational thinking education is implemented in different regions, and how computational thinking is being integrated into subject learning in K-12 education. In closing, it discusses computational thinking from the perspective of STEM education, the use of video games to teach computational thinking, and how computational thinking is helping to transform the quality of the workforce in the textile and apparel industry.

From coding languages and hardware to cyberbullying and gaming, this comprehensive homework helper for kids and parents covers the essentials of computer science. This unique visual study guide examines the technical aspects of computers, such as how they function, the latest digital devices and software, and how the Internet works. It also builds the confidence of parents and kids when facing challenges such as staying safe online, digital etiquette, and how to navigate the potential pitfalls of social media. Jargon-free language helps to explain difficult and potentially dread-inducing homework such as hacking, "big data" and malware, while colorful graphics help makes learning about the world of computer science exciting. Whether at home or school, this clear and helpful guide to computer science is the tool you need to be able to support students with confidence. Series Overview: DK's bestselling Help Your Kids With series contains crystal-clear visual breakdowns of important subjects. Simple graphics and jargon-free text are key to making this series a user-friendly resource for frustrated parents who want to help their children get the most out of school.