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| can you teach yourself computer science: Mathematics for Computer Science Eric Lehman, F. Thomson Leighton, Albert R. Meyer, 2017-03-08 This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions. |
| can you teach yourself computer science: Classic Computer Science Problems in Java David Kopec, 2020-12-21 Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms. Summary Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms. You’ll work through a series of exercises based in computer science fundamentals that are designed to improve your software development abilities, improve your understanding of artificial intelligence, and even prepare you to ace an interview. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your new problems! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Whatever software development problem you’re facing, odds are someone has already uncovered a solution. This book collects the most useful solutions devised, guiding you through a variety of challenges and tried-and-true problem-solving techniques. The principles and algorithms presented here are guaranteed to save you countless hours in project after project. About the book Classic Computer Science Problems in Java is a master class in computer programming designed around 55 exercises that have been used in computer science classrooms for years. You’ll work through hands-on examples as you explore core algorithms, constraint problems, AI applications, and much more. What's inside Recursion, memoization, and bit manipulation Search, graph, and genetic algorithms Constraint-satisfaction problems K-means clustering, neural networks, and adversarial search About the reader For intermediate Java programmers. About the author David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. Table of Contents 1 Small problems 2 Search problems 3 Constraint-satisfaction problems 4 Graph problems 5 Genetic algorithms 6 K-means clustering 7 Fairly simple neural networks 8 Adversarial search 9 Miscellaneous problems 10 Interview with Brian Goetz |
| can you teach yourself computer science: Structure and Interpretation of Computer Programs Harold Abelson, Gerald Jay Sussman, 2022-05-03 A new version of the classic and widely used text adapted for the JavaScript programming language. Since the publication of its first edition in 1984 and its second edition in 1996, Structure and Interpretation of Computer Programs (SICP) has influenced computer science curricula around the world. Widely adopted as a textbook, the book has its origins in a popular entry-level computer science course taught by Harold Abelson and Gerald Jay Sussman at MIT. SICP introduces the reader to central ideas of computation by establishing a series of mental models for computation. Earlier editions used the programming language Scheme in their program examples. This new version of the second edition has been adapted for JavaScript. The first three chapters of SICP cover programming concepts that are common to all modern high-level programming languages. Chapters four and five, which used Scheme to formulate language processors for Scheme, required significant revision. Chapter four offers new material, in particular an introduction to the notion of program parsing. The evaluator and compiler in chapter five introduce a subtle stack discipline to support return statements (a prominent feature of statement-oriented languages) without sacrificing tail recursion. The JavaScript programs included in the book run in any implementation of the language that complies with the ECMAScript 2020 specification, using the JavaScript package sicp provided by the MIT Press website. |
| can you teach yourself computer science: Ultralearning Scott H. Young, 2019-08-06 Now a Wall Street Journal bestseller. Learn a new talent, stay relevant, reinvent yourself, and adapt to whatever the workplace throws your way. Ultralearning offers nine principles to master hard skills quickly. This is the essential guide to future-proof your career and maximize your competitive advantage through self-education. In these tumultuous times of economic and technological change, staying ahead depends on continual self-education—a lifelong mastery of fresh ideas, subjects, and skills. If you want to accomplish more and stand apart from everyone else, you need to become an ultralearner. The challenge of learning new skills is that you think you already know how best to learn, as you did as a student, so you rerun old routines and old ways of solving problems. To counter that, Ultralearning offers powerful strategies to break you out of those mental ruts and introduces new training methods to help you push through to higher levels of retention. Scott H. Young incorporates the latest research about the most effective learning methods and the stories of other ultralearners like himself—among them Benjamin Franklin, chess grandmaster Judit Polgár, and Nobel laureate physicist Richard Feynman, as well as a host of others, such as little-known modern polymath Nigel Richards, who won the French World Scrabble Championship—without knowing French. Young documents the methods he and others have used to acquire knowledge and shows that, far from being an obscure skill limited to aggressive autodidacts, ultralearning is a powerful tool anyone can use to improve their career, studies, and life. Ultralearning explores this fascinating subculture, shares a proven framework for a successful ultralearning project, and offers insights into how you can organize and exe - cute a plan to learn anything deeply and quickly, without teachers or budget-busting tuition costs. Whether the goal is to be fluent in a language (or ten languages), earn the equivalent of a college degree in a fraction of the time, or master multiple tools to build a product or business from the ground up, the principles in Ultralearning will guide you to success. |
| can you teach yourself computer science: The Elements of Computing Systems Noam Nisan, Shimon Schocken, 2008 This title gives students an integrated and rigorous picture of applied computer science, as it comes to play in the construction of a simple yet powerful computer system. |
| can you teach yourself computer science: Everything You Need to Ace Computer Science and Coding in One Big Fat Notebook Workman Publishing, 2020-04-28 From the editors of Brain Quest, America’s #1 educational bestseller! This Big Fat Notebook makes it all “sink in” with key concepts, mnemonic devices, definitions, diagrams, and doodles to help you understand computer science. Including: Computing systems Binary code Algorithms Computational thinking Loops, events, and procedures Programming in Scratch and Python Boolean Expressions Web development Cybersecurity HTML CSS …and more! The Big Fat Notebook series is built on a simple and irresistible conceit—borrowing the notes from the smartest kid in class. Each book in the series meets Common Core State Standards, Next Generation Science Standards, and state history standards, and are vetted by National and State Teacher of the Year Award–winning teachers. They make learning fun and are the perfect next step for every kid who grew up on Brain Quest. |
| can you teach yourself computer science: Computer Science in K-12 Shuchi Grover, 2020-04 Coding teaches our students the essence of logical thinking and problem solving while also preparing them for a world in which computing is becoming increasingly pervasive. While there's excitement and enthusiasm about programming becoming an intrinsic part of K-12 curricula the world over, there's also growing anxiety about preparing teachers to teach effectively at all grade levels.This book strives to be an essential, enduring, practical guide for every K-12 teacher anywhere who is either teaching or planning to teach computer science and programming at any grade level. To this end, readers will discover:? An A-to-Z organization that affords comprehensive insight into teaching introductory programming.? 26 chapters that cover foundational concepts, practices and well-researched pedagogies related to teaching introductory programming as an integral part of K-12 computer science. Cumulatively these chapters address the two salient building blocks of effective teaching of introductory programming-what content to teach (concepts and practices) and how to teach (pedagogy).? Concrete ideas and rich grade-appropriate examples inspired by practice and research for classroom use.? Perspectives and experiences shared by educators and scholars who are actively practicing and/or examiningthe teaching of computer science and programming in K-12 classrooms. |
| can you teach yourself computer science: Beginning Programming with Python For Dummies John Paul Mueller, 2018-02-13 The easy way to learn programming fundamentals with Python Python is a remarkably powerful and dynamic programming language that's used in a wide variety of application domains. Some of its key distinguishing features include a very clear, readable syntax, strong introspection capabilities, intuitive object orientation, and natural expression of procedural code. Plus, Python features full modularity, supporting hierarchical packages, exception-based error handling, and modules easily written in C, C++, Java, R, or .NET languages, such as C#. In addition, Python supports a number of coding styles that include: functional, imperative, object-oriented, and procedural. Due to its ease of use and flexibility, Python is constantly growing in popularity—and now you can wear your programming hat with pride and join the ranks of the pros with the help of this guide. Inside, expert author John Paul Mueller gives a complete step-by-step overview of all there is to know about Python. From performing common and advanced tasks, to collecting data, to interacting with package—this book covers it all! Use Python to create and run your first application Find out how to troubleshoot and fix errors Learn to work with Anaconda and use Magic Functions Benefit from completely updated and revised information since the last edition If you've never used Python or are new to programming in general, Beginning Programming with Python For Dummies is a helpful resource that will set you up for success. |
| can you teach yourself computer science: Computer Science Education Sue Sentance, Erik Barendsen, Nicol R. Howard, Carsten Schulte, 2023-02-23 Drawing together the most up-to-date research from experts all across the world, the second edition of Computer Science Education offers the most up-to-date coverage available on this developing subject, ideal for building confidence of new pre-service and in-service educators teaching a new discipline. It provides an international overview of key concepts, pedagogical approaches and assessment practices. Highlights of the second edition include: - New sections on machine learning and data-driven (epistemic) programming - A new focus on equity and inclusion in computer science education - Chapters updated throughout, including a revised chapter on relating ethical and societal aspects to knowledge-rich aspects of computer science education - A new set of chapters on the learning of programming, including design, pedagogy and misconceptions - A chapter on the way we use language in the computer science classroom. The book is structured to support the reader with chapter outlines, synopses and key points. Explanations of key concepts, real-life examples and reflective points keep the theory grounded in classroom practice. The book is accompanied by a companion website, including online summaries for each chapter, 3-minute video summaries by each author and an archived chapter on taxonomies and competencies from the first edition. |
| can you teach yourself computer science: Guide to Teaching Computer Science Orit Hazzan, Tami Lapidot, Noa Ragonis, 2015-01-07 This textbook presents both a conceptual framework and detailed implementation guidelines for computer science (CS) teaching. Updated with the latest teaching approaches and trends, and expanded with new learning activities, the content of this new edition is clearly written and structured to be applicable to all levels of CS education and for any teaching organization. Features: provides 110 detailed learning activities; reviews curriculum and cross-curriculum topics in CS; explores the benefits of CS education research; describes strategies for cultivating problem-solving skills, for assessing learning processes, and for dealing with pupils’ misunderstandings; proposes active-learning-based classroom teaching methods, including lab-based teaching; discusses various types of questions that a CS instructor or trainer can use for a range of teaching situations; investigates thoroughly issues of lesson planning and course design; examines the first field teaching experiences gained by CS teachers. |
| can you teach yourself computer science: Sams Teach Yourself COBOL in 24 Hours Thane Hubbell, 1998-11-28 Sams Teach Yourself COBOL in 24 Hours teaches the basics of COBOL programming in 24 step-by-step lessons. Each lesson builds on the previous one providing a solid foundation in COBOL programming concepts and techniques. This hands-on guide is the easiest, fastest way to begin creating standard COBOL compliant code. Business professionals and programmers from other languages will find this hands-on, task-oriented tutorial extremely useful for learning the essential features and concepts of COBOL programming. Writing a program can be a complex task. Concentrating on one development tool guides you to good results every time. There will be no programs that will not compile! |
| can you teach yourself computer science: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| can you teach yourself computer science: How to Design Programs, second edition Matthias Felleisen, Robert Bruce Findler, Matthew Flatt, Shriram Krishnamurthi, 2018-05-25 A completely revised edition, offering new design recipes for interactive programs and support for images as plain values, testing, event-driven programming, and even distributed programming. This introduction to programming places computer science at the core of a liberal arts education. Unlike other introductory books, it focuses on the program design process, presenting program design guidelines that show the reader how to analyze a problem statement, how to formulate concise goals, how to make up examples, how to develop an outline of the solution, how to finish the program, and how to test it. Because learning to design programs is about the study of principles and the acquisition of transferable skills, the text does not use an off-the-shelf industrial language but presents a tailor-made teaching language. For the same reason, it offers DrRacket, a programming environment for novices that supports playful, feedback-oriented learning. The environment grows with readers as they master the material in the book until it supports a full-fledged language for the whole spectrum of programming tasks. This second edition has been completely revised. While the book continues to teach a systematic approach to program design, the second edition introduces different design recipes for interactive programs with graphical interfaces and batch programs. It also enriches its design recipes for functions with numerous new hints. Finally, the teaching languages and their IDE now come with support for images as plain values, testing, event-driven programming, and even distributed programming. |
| can you teach yourself computer science: The Self-Taught Computer Scientist Cory Althoff, 2021-09-16 The follow-up to Cory Althoff's bestselling The Self-Taught Programmer, which inspired hundreds of thousands of professionals to learn to program outside of school! Fresh out of college and with just a year of self-study behind him, Cory Althoff was offered a dream first job as a software engineer for a well-known tech company, but he quickly found himself overwhelmed by the amount of things he needed to know, but hadn’t learned yet. This experience combined with his personal journey learning to program inspired his widely praised guide, The Self-Taught Programmer. Now Cory's back with another guide for the self-taught community of learners focusing on the foundations of computer science. The Self-Taught Computer Scientist introduces beginner and self-taught programmers to computer science fundamentals that are essential for success in programming and software engineering fields. Computer science is a massive subject that could cover an entire lifetime of learning. This book does not aim to cover everything you would learn about if you went to school to get a computer science degree. Instead, Cory's goal is to give you an introduction to some of the most important concepts in computer science that apply to a programming career. With a focus on data structures and algorithms, The Self-Taught Computer Scientist helps you fill gaps in your knowledge, prepare for a technical interview, feel knowledgeable and confident on the job, and ultimately, become a better programmer. Learn different algorithms including linear and binary search and test your knowledge with feedback loops Understand what a data structure is and study arrays, linked lists, stacks, queues, hash tables, binary trees, binary heaps, and graphs Prepare for technical interviews and feel comfortable working with more experienced colleagues Discover additional resources and tools to expand your skillset and continue your learning journey It's as simple as this: You have to study computer science if you want to become a successful programmer, and if you don't understand computer science, you won't get hired. Ready for a career in programming, coding, or software engineering and willing to embrace an always be learning mindset? The Self-Taught Computer Scientist is for you. |
| can you teach yourself computer science: Getting Smart Tom Vander Ark, 2011-09-20 A comprehensive look at the promise and potential of online learning In our digital age, students have dramatically new learning needs and must be prepared for the idea economy of the future. In Getting Smart, well-known global education expert Tom Vander Ark examines the facets of educational innovation in the United States and abroad. Vander Ark makes a convincing case for a blend of online and onsite learning, shares inspiring stories of schools and programs that effectively offer personal digital learning opportunities, and discusses what we need to do to remake our schools into smart schools. Examines the innovation-driven world, discusses how to combine online and onsite learning, and reviews smart tools for learning Investigates the lives of learning professionals, outlines the new employment bargain, examines online universities and smart schools Makes the case for smart capital, advocates for policies that create better learning, studies smart cultures |
| can you teach yourself computer science: Learning to Program Steven Foote, 2014 Learning to Program will help students build a solid foundation in programming that can prepare them to achieve just about any programming goal. Whether they want to become a professional software programmer, learn how to more effectively communicate with programmers, or are just curious about how programming works, this book is a great first step in helping to get there. |
| can you teach yourself computer science: Computer Architecture John L. Hennessy, David A. Patterson, Krste Asanović, 2012 The computing world is in the middle of a revolution: mobile clients and cloud computing have emerged as the dominant paradigms driving programming and hardware innovation. This book focuses on the shift, exploring the ways in which software and technology in the 'cloud' are accessed by cell phones, tablets, laptops, and more |
| can you teach yourself computer science: Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Policy and Global Affairs, Board on Higher Education and Workforce, Committee on the Growth of Computer Science Undergraduate Enrollments, 2018-04-28 The field of computer science (CS) is currently experiencing a surge in undergraduate degree production and course enrollments, which is straining program resources at many institutions and causing concern among faculty and administrators about how best to respond to the rapidly growing demand. There is also significant interest about what this growth will mean for the future of CS programs, the role of computer science in academic institutions, the field as a whole, and U.S. society more broadly. Assessing and Responding to the Growth of Computer Science Undergraduate Enrollments seeks to provide a better understanding of the current trends in computing enrollments in the context of past trends. It examines drivers of the current enrollment surge, relationships between the surge and current and potential gains in diversity in the field, and the potential impacts of responses to the increased demand for computing in higher education, and it considers the likely effects of those responses on students, faculty, and institutions. This report provides recommendations for what institutions of higher education, government agencies, and the private sector can do to respond to the surge and plan for a strong and sustainable future for the field of CS in general, the health of the institutions of higher education, and the prosperity of the nation. |
| can you teach yourself computer science: Your First Year Teaching Computer Science Chris Gregg, 2021-01-15 Your First Year Teaching Computer Science is a comprehensive guide to teaching computer science geared to new instructors in the field. It can be used as a guide and a reference, and it provides multiple examples of how to construct teaching materials, how to prepare lectures, how to write assignments, how to train TAs, and how to advise students, among many other topics. It is both motivational and instructive, and it provides a foundation on which to become a great CS instructor. Teaching computer science involves more than just teaching the material, and this book details all of the other parts of teaching that you will need to know to do the job. If you are wondering where to begin as a computer science teacher, this is the book for you.Features-Serves as a comprehensive guide to teaching introductory computer science for new teachers, and experienced teachers can refer to it on specific points. -Provides examples of teaching materials, grading guides, multiple lists, and other valuable resource for helping new teachers to launch their first computer science courses. -Includes information about training TAs, holding office hours, advising students, and many other practical information that is not specifically about the technical part of teaching computer science. -Written in a conversational tone and is premised on the belief that teaching should be rewarding, fun, and engaging. |
| can you teach yourself computer science: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| can you teach yourself computer science: Sams Teach Yourself Samba in 24 Hours Gerald Carter, 2002 Author and Samba Team Member Gerald Carter dedicates most of this book to the processes of installing and configuring Samba, distinguishing between both Linux/Windows, and Unix/Windows-based systems. He discusses the mechanics of file sharing across the dual platforms and expertly outlines the means necessary to remedy common problems, including helping to identify which version of Samba you are running and where to look for the patch or bug fix you will need to resolve it. He also assists in locating utilities like autoconf that automatically compiles a system configuration file with common default settings. Finally, he discusses security and password issues, as well as peripheral support for server printers. |
| can you teach yourself computer science: Computation Structures Stephen A. Ward, Robert H. Halstead, 1990 Computer Systems Organization -- general. |
| can you teach yourself computer science: A to Z Computer Science Activity Book Sakina Fakhruddin, 2020-05-25 An awesome and fascinating introduction to computer science concepts, one letter at a time!The Computer Science A to Z Activity Book introduces kids (and adults) to coding and computer science vocabulary, from letter A to Z. Explore the collection of fun, engaging and innovative activities in this book and learn the basics of programming and computer science! On every page, you will find a brief description of the word mentioned and a fun activity with it. You will learn about how the Internet works, algorithms, and also learn about people like Grace Hopper, Tim Berners-Lee and more. This book has places for you to draw and color, word searches, and a ton of other awesome stuff! Draw a flowchart for baking a cookie, learn sorting using playing cards, debug some code, and HAVE FUN! |
| can you teach yourself computer science: Sams Teach Yourself the C# Language in 21 Days Bradley Jones, 2004 In 21 days readers learn how to use the key features of the C♯ programming language - not only the commands, but how to create entire programs using them after a few introductory chapters. |
| can you teach yourself computer science: Sams Teach Yourself PHP in 10 Minutes Chris Newman, 2005 Presents lessons on using PHP, covering such topics as processing HTML forms, filtering database data, creating HTML pages, authenticating users at a Web site, and using cookies and sessions. |
| can you teach yourself computer science: Computer Science Illuminated Nell B. Dale, John Lewis, 2013 Revised and updated with the latest information in the field, the Fifth Edition of best-selling Computer Science Illuminated continues to provide students with an engaging breadth-first overview of computer science principles and provides a solid foundation for those continuing their study in this dynamic and exciting discipline. Authored by two of today's most respected computer science educators, Nell Dale and John Lewis, the text carefully unfolds the many layers of computing from a language-neutral perspective, beginning with the information layer, progressing through the hardware, programming, operating systems, application, and communication layers, and ending with a discussion on the limitations of computing. Separate program language chapters are available as bundle items for instructors who would like to explore a particular programming language with their students. Ideal for introductory computing and computer science courses, the fifth edition's thorough presentation of computing systems provides computer science majors with a solid foundation for further study, and offers non-majors a comprehensive and complete introduction to computing. New Features of the Fifth Edition: - Includes a NEW chapter on computer security (chapter 17) to provide readers with the latest information, including discussions on preventing unauthorized access and guidelines for creating effective passwords, types of malware anti-virus software, problems created by poor programming, protecting your online information including data collection issues with Facebook, Google, etc., and security issues with mobile and portable devices. - A NEW section on cloud computing (chapter 15) offers readers an overview of the latest way in which businesses and users interact with computers and mobile devices. - The section on social networks (moved to chapter 16) has been rewritten to include up-to-date information, including new data on Google+ and Facebook. - The sections covering HTML have been updated to include HTML5. - Includes revised and updated Did You Know callouts in the chapter margins. - The updated Ethical Issues at the end of each chapter have been revised to tie the content to the recently introduced tenth strand recommended by the ACM stressing the importance of computer ethics. Instructor Resources: -Answers to the end of chapter exercises -Answers to the lab exercises -PowerPoint Lecture Outlines -PowerPoint Image Bank -Test Bank Every new copy is packaged with a free access code to the robust Student Companion Website featuring: Animated Flashcards; Relevant Web Links; Crossword Puzzles; Interactive Glossary; Step by step tutorial on web page development; Digital Lab Manual; R. Mark Meyer's labs, Explorations in Computer Science; Additional programming chapters, including Alice, C++, Java, JavaScript, Pascal, Perl, Python, Ruby, SQL, and VB.NET; C++ Language Essentials labs; Java Language Essentials labs; Link to Download Pep/8 |
| can you teach yourself computer science: Touch of Class Bertrand Meyer, 2009-08-28 This text combines a practical, hands-on approach to programming with the introduction of sound theoretical support focused on teaching the construction of high-quality software. A major feature of the book is the use of Design by Contract. |
| can you teach yourself computer science: Readings in Database Systems Joseph M. Hellerstein, Michael Stonebraker, 2005 The latest edition of a popular text and reference on database research, with substantial new material and revision; covers classical literature and recent hot topics. Lessons from database research have been applied in academic fields ranging from bioinformatics to next-generation Internet architecture and in industrial uses including Web-based e-commerce and search engines. The core ideas in the field have become increasingly influential. This text provides both students and professionals with a grounding in database research and a technical context for understanding recent innovations in the field. The readings included treat the most important issues in the database area--the basic material for any DBMS professional. This fourth edition has been substantially updated and revised, with 21 of the 48 papers new to the edition, four of them published for the first time. Many of the sections have been newly organized, and each section includes a new or substantially revised introduction that discusses the context, motivation, and controversies in a particular area, placing it in the broader perspective of database research. Two introductory articles, never before published, provide an organized, current introduction to basic knowledge of the field; one discusses the history of data models and query languages and the other offers an architectural overview of a database system. The remaining articles range from the classical literature on database research to treatments of current hot topics, including a paper on search engine architecture and a paper on application servers, both written expressly for this edition. The result is a collection of papers that are seminal and also accessible to a reader who has a basic familiarity with database systems. |
| can you teach yourself computer science: Rev Up Robotics Jorge Valenzuela, 2022-08-18 Author Jorge Valenzuela lays out the foundational skills of computational thinking required for programming with robotics. Unlike other robotics books and curriculum, Rev Up Robotics takes a cross-curricular approach, showing educators how to begin incorporating robotics into their content area lessons and in conjunction with other subjects. You’ll get an overview of standards-based skills that can be covered in English language arts, math, science, social studies and robotics electives. Teachers also get tips for selecting the robot that works for them and for students, and details on the functions of gears, motors and sensors. Also included is a deep dive into more advanced topics like the intersections of computer science, mechanical engineering and electrical engineering with robotics. Finally, you’ll find advice for getting students involved with competitive robotics, and case studies that offer empirical evidence for using robotics successfully in instruction. The book: • Shows how to help students recognize and apply the four elements of computational thinking to familiar situations. • Provides a pathway from working with visual blocks to programming in C++. • Discusses building and programming robots, with tips for adding your own code and troubleshooting. • Demonstrates how to manipulate basic movement to better understand the functions of gears, motors and sensors. With activities and examples for grade levels K-8, teachers come away with easy-to-implement cross-curricular ideas to engage students in computer science and engineering activities. |
| can you teach yourself computer science: Computer Science Distilled Wladston Ferreira Filho, 2017-01-17 A walkthrough of computer science concepts you must know. Designed for readers who don't care for academic formalities, it's a fast and easy computer science guide. It teaches the foundations you need to program computers effectively. After a simple introduction to discrete math, it presents common algorithms and data structures. It also outlines the principles that make computers and programming languages work. |
| can you teach yourself computer science: Preparing Pre-Service Teachers to Teach Computer Science Chrystalla Mouza, Aman Yadav, Anne Ottenbreit-Leftwich, 2021 Computer science has emerged as a key driver of innovation in the 21st century. Preparing teachers to teach computer science, however, remains an enormous challenge as there are few highly qualified teachers who can teach computer science or integrate computer science content into K-12 curricula. To address this challenge, NSF established the CS10K program with the aim of preparing 10,000 teachers in 10,000 high schools teaching computer science curricula. While this effort is still under-way, there has not been a systematic attempt to capture the work done in this area. In order to prepare a generation of teachers who are capable of delivering computer science content to students, we must identify research-based examples, pedagogical strategies and policies that can facilitate changes in teacher knowledge and practices. The purpose of this project is to provide examples that could help guide the design and delivery of effective teacher preparation on the teaching of computer science concepts. This book identifies promising pathways, pedagogical strategies and policies that help pre-service and in-service teachers infuse computing ideas in their curricula as well as teach stand-alone computing courses. The book focuses on pedagogical practices for developing and assessing pre-service teacher knowledge of computer science, course design models for pre-service teachers, and discussion of policies that can support the teaching of computer science. The primary audience of the book will be students and faculty in educational technology, educational or cognitive psychology, learning theory, curriculum and instruction, computer science, instructional systems and learning sciences-- |
| can you teach yourself computer science: Picturing Programs Stephen Bloch, 2010 A first programming course should not be directed towards learning a particular programming language, but rather at learning to program well; the programming language should get out of the way and serve this goal. The simple, powerful Racket language (related to Scheme) allows us to concentrate on the fundamental concepts and techniques of computer programming, without being distracted by complex syntax. As a result, this book can be used at the high school (and perhaps middle school) level, while providing enough advanced concepts not usually found in a first course to challenge a college student. Those who have already done some programming (e.g. in Java, Python, or C++) will enhance their understanding of the fundamentals, un-learn some bad habits, and change the way they think about programming. We take a graphics-early approach: you'll start manipulating and combining graphic images from Chapter 1 and writing event-driven GUI programs from Chapter 6, even before seeing arithmetic. We continue using graphics, GUI and game programming throughout to motivate fundamental concepts. At the same time, we emphasize data types, testing, and a concrete, step-by-step process of problem-solving. After working through this book, you'll be prepared to learn other programming languages and program well in them. Or, if this is the last programming course you ever take, you'll understand many of the issues that affect the programs you use every day. I have been using Picturing Programs with my daughter, and there's no doubt that it's gentler than Htdp. It does exactly what Stephen claims, which is to move gradually from copy-and-change exercises to think-on-your-own exercises within each section. I also think it's nice that the worked exercises are clearly labeled as such. There's something psychologically appealing about the fact that you first see an example in the text of the book, and then a similar example is presented as if it were an exercise but they just happen to be giving away the answer. It is practically shouting out Here's a model of how you go about solving this class of problems, pay close attention . Mark Engelberg 1. Matthias & team have done exceptional, highly impressive work with HtDP. The concepts are close to genius. (perhaps yes, genius quality work) They are a MUST for any high school offering serious introductory CS curriculum. 2. Without Dr. Blochs book Picturing Programs, I would not have successfully implemented these concepts (Dr. Scheme, Racket, Design Recipe etc) into an ordinary High School Classroom. Any high school instructor who struggles to find ways to bring these great HtDP ideas to the typical high schooler, should immediately investigate the Bloch book. Think of it as coating the castor oil with chocolate. Brett Penza |
| can you teach yourself computer science: Logic for Computer Science Steve Reeves, Michael Clarke, 1990 An understanding of logic is essential to computer science. This book provides a highly accessible account of the logical basis required for reasoning about computer programs and applying logic in fields like artificial intelligence. The text contains extended examples, algorithms, and programs written in Standard ML and Prolog. No prior knowledge of either language is required. The book contains a clear account of classical first-order logic, one of the basic tools for program verification, as well as an introductory survey of modal and temporal logics and possible world semantics. An introduction to intuitionistic logic as a basis for an important style of program specification is also featured in the book. |
| can you teach yourself computer science: Crafting Interpreters Robert Nystrom, 2021-07-27 Despite using them every day, most software engineers know little about how programming languages are designed and implemented. For many, their only experience with that corner of computer science was a terrifying compilers class that they suffered through in undergrad and tried to blot from their memory as soon as they had scribbled their last NFA to DFA conversion on the final exam. That fearsome reputation belies a field that is rich with useful techniques and not so difficult as some of its practitioners might have you believe. A better understanding of how programming languages are built will make you a stronger software engineer and teach you concepts and data structures you'll use the rest of your coding days. You might even have fun. This book teaches you everything you need to know to implement a full-featured, efficient scripting language. You'll learn both high-level concepts around parsing and semantics and gritty details like bytecode representation and garbage collection. Your brain will light up with new ideas, and your hands will get dirty and calloused. Starting from main(), you will build a language that features rich syntax, dynamic typing, garbage collection, lexical scope, first-class functions, closures, classes, and inheritance. All packed into a few thousand lines of clean, fast code that you thoroughly understand because you wrote each one yourself. |
| can you teach yourself computer science: Feynman Lectures On Computation Richard P. Feynman, 2018-07-03 When, in 1984?86, Richard P. Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a ?Feynmanesque? overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers. |
| can you teach yourself computer science: Architecture of a Database System Joseph M. Hellerstein, Michael Stonebraker, James Hamilton, 2007 Architecture of a Database System presents an architectural discussion of DBMS design principles, including process models, parallel architecture, storage system design, transaction system implementation, query processor and optimizer architectures, and typical shared components and utilities. |
| can you teach yourself computer science: Essentials of Programming Languages Daniel P. Friedman, Mitchell Wand, Christopher Thomas Haynes, 2001 This textbook offers an understanding of the essential concepts of programming languages. The text uses interpreters, written in Scheme, to express the semantics of many essential language elements in a way that is both clear and directly executable. |
| can you teach yourself computer science: Digital Logic Design Brian Holdsworth, Clive Woods, 2002-11-01 New, updated and expanded topics in the fourth edition include: EBCDIC, Grey code, practical applications of flip-flops, linear and shaft encoders, memory elements and FPGAs. The section on fault-finding has been expanded. A new chapter is dedicated to the interface between digital components and analog voltages. - A highly accessible, comprehensive and fully up to date digital systems text - A well known and respected text now revamped for current courses - Part of the Newnes suite of texts for HND/1st year modules |
| can you teach yourself computer science: Stuck in the Shallow End, updated edition Jane Margolis, 2017-03-03 Why so few African American and Latino/a students study computer science: updated edition of a book that reveals the dynamics of inequality in American schools. The number of African Americans and Latino/as receiving undergraduate and advanced degrees in computer science is disproportionately low. And relatively few African American and Latino/a high school students receive the kind of institutional encouragement, educational opportunities, and preparation needed for them to choose computer science as a field of study and profession. In Stuck in the Shallow End, Jane Margolis and coauthors look at the daily experiences of students and teachers in three Los Angeles public high schools: an overcrowded urban high school, a math and science magnet school, and a well-funded school in an affluent neighborhood. They find an insidious “virtual segregation” that maintains inequality. The race gap in computer science, Margolis discovers, is one example of the way students of color are denied a wide range of occupational and educational futures. Stuck in the Shallow End is a story of how inequality is reproduced in America—and how students and teachers, given the necessary tools, can change the system. Since the 2008 publication of Stuck in the Shallow End, the book has found an eager audience among teachers, school administrators, and academics. This updated edition offers a new preface detailing the progress in making computer science accessible to all, a new postscript, and discussion questions (coauthored by Jane Margolis and Joanna Goode). |
| can you teach yourself computer science: The Self-Taught Programmer Cory Althoff, 2022-01-13 |
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