Computer Science: An Overview uses broad coverage and clear exposition to present a complete picture of the dynamic computer science field. Accessible to students from all backgrounds, Glenn Brookshear uses a language-independent context to encourage the development of a practical, realistic understanding of the field. An overview of each of the important areas of Computer Science (e.g. Networking, OS, Computer Architecture, Algorithms) provides students with a general level of proficiency for future courses. The Eleventh Edition features two new contributing authors (David Smith -- Indiana University of PA; Dennis Brylow -- Marquette University), new, modern examples, and updated coverage based on current technology.
Note: You are purchasing a standalone product; MyProgrammingLab does not come packaged with this content. If you would like to purchase both the physical text and MyProgrammingLab search for ISBN-10: 0133862119/ISBN-13: 9780133862119. That package includes ISBN-10: 0133766268/ISBN-13: 9780133766264 and ISBN-10: 0133841030 /ISBN-13: 9780133841039. MyProgrammingLab is not a self-paced technology and should only be purchased when required by an instructor. Java: An Introduction to Problem Solving and Programming, 7e, is ideal for introductory Computer Science courses using Java, and other introductory programming courses in departments of Computer Science, Computer Engineering, CIS, MIS, IT, and Business. It also serves as a useful Java fundamentals reference for programmers. Students are introduced to object-oriented programming and important concepts such as design, testing and debugging, programming style, interfaces inheritance, and exception handling. The Java coverage is a concise, accessible introduction that covers key language features. Objects are covered thoroughly and early in the text, with an emphasis on application programs over applets. MyProgrammingLab for Java is a total learning package. MyProgrammingLab is an online homework, tutorial, and assessment program that truly engages students in learning. It helps students better prepare for class, quizzes, and exams–resulting in better performance in the course–and provides educators a dynamic set of tools for gauging individual and class progress. Teaching and Learning Experience This program presents a better teaching and learning experience—for you and your students. Personalized Learning with MyProgrammingLab: Through the power of practice and immediate personalized feedback, MyProgrammingLab helps students fully grasp the logic, semantics, and syntax of programming. A Concise, Accessible Introduction to Java: Key Java language features are covered in an accessible manner that resonates with introductory programmers. Tried-and-true Pedagogy: Numerous case studies, programming examples, and programming tips are used to help teach problem-solving and programming techniques. Flexible Coverage that Fits your Course: Flexibility charts and optional graphics sections allow instructors to order chapters and sections based on their course needs. Instructor and Student Resources that Enhance Learning: Resources are available to expand on the topics presented in the text.
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic.
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.
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.
In just 21 days, you can acquire the knowledge and skills necessary to develop applications on your computer, web servers, and mobile devices. With this complete tutorial you’ll quickly master the basics and then move on to more advanced features and concepts. Completely updated for Java 11 and 12, this book teaches you about the Java language and how to use it to create applications for any computing environment. By the time you have finished the book, you’ll have well-rounded knowledge of Java and the Java class libraries. No previous programming experience required. By following the 21 carefully organized lessons in this book, anyone can learn the basics of Java programming. Learn at your own pace. You can work through each chapter sequentially to make sure you thoroughly understand all the concepts and methodologies, or you can focus on specific lessons to learn the techniques that interest you most. Test your knowledge. Each chapter ends with a Workshop section filled with questions, answers, and exercises for further study. There are even certification practice questions. Completely revised, updated, and expanded to cover the latest features of Java 11 and 12 Learn to develop Java applications using NetBeans–an excellent programming platform Easy-to-understand, practical examples clearly illustrate the fundamentals of Java programming Discover how to quickly develop programs with a graphical user interface Find out about JDBC programming with the Derby database Learn how to use Inner Classes and Lambda Expressions Learn rapid application development with Apache NetBeans Create a game using Java
Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Contents Tutorial • Applications • Further Reading
This book contains high-quality refereed research papers presented at the Fifth International Conference on Computer Science, Engineering, and Education Applications (ICCSEEA2022), which took place in Kyiv, Ukraine, on February 21–22, 2022, and was organized by the National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute," National Aviation University, and the International Research Association of Modern Education and Computer Science. State-of-the-art studies in computer science, artificial intelligence, engineering methodologies, genetic coding systems, deep learning with medical applications, and knowledge representation with educational applications are among the topics covered in the book. For academics, graduate students, engineers, management practitioners, and undergraduate students interested in computer science and its applications in engineering and education, this book is a valuable resource.
