Essential Computer Science

Understand essential computer science concepts and skills. This book focuses on the foundational and fundamental concepts upon which expertise in specific areas can be developed, including computer architecture, programming language, algorithm and data structure, operating systems, computer networks, distributed systems, security, and more. According to code.org, there are 500,000 open programming positions available in the US— compared to an annual crop of just 50,000 graduating computer science majors. The US Department of Labor predicted that there will be almost a million and a half computer science jobs in the very near future, but only enough programmers to fill roughly one third of these jobs. To bridge the gap, many people not formally trained in computer science are employed in programming jobs. Although they are able to start programming and coding quickly, it often takes them time to acquire the necessary understanding to gain the requisite skills to become an efficient computer engineer or advanced developer. What You Will Learn The fundamentals of how a computer works The basics of computer programming and programming paradigms How to write efficient programs How the hardware and software work together to provide a good user experience and enhance the usability of the system How computers can talk to each other How to ensure the security of the system The fundamentals of cloud offerings, implications/trade-offs, and deployment/adoption configurations The fundamentals of machine learning Who This Book Is For Computer programmers lacking a formal education in computer science, and anyone with a formal education in computer science, looking to develop a general understanding of computer science fundamentals

An introduction to applying predicate logic to testing and verification of software and digital circuits that focuses on applications rather than theory. Computer scientists use logic for testing and verification of software and digital circuits, but many computer science students study logic only in the context of traditional mathematics, encountering the subject in a few lectures and a handful of problem sets in a discrete math course. This book offers a more substantive and rigorous approach to logic that focuses on applications in computer science. Topics covered include predicate logic, equation-based software, automated testing and theorem proving, and large-scale computation. Formalism is emphasized, and the book employs three formal notations: traditional algebraic formulas of propositional and predicate logic; digital circuit diagrams; and the widely used partially automated theorem prover, ACL2, which provides an accessible introduction to mechanized formalism. For readers who want to see formalization in action, the text presents examples using Proof Pad, a lightweight ACL2 environment. Readers will not become ALC2 experts, but will learn how mechanized logic can benefit software and hardware engineers. In addition, 180 exercises, some of them extremely challenging, offer opportunities for problem solving. There are no prerequisites beyond high school algebra. Programming experience is not required to understand the book's equation-based approach. The book can be used in undergraduate courses in logic for computer science and introduction to computer science and in math courses for computer science students.

Get to grips with the building blocks of programming languages and get started on your programming journey without a computer science degree Key FeaturesUnderstand the fundamentals of a computer program and apply the concepts you learn to different programming languagesGain the confidence to write your first computer programExplore tips, techniques, and best practices to start coding like a professional programmerBook Description Learning how to code has many advantages, and gaining the right programming skills can have a massive impact on what you can do with your current skill set and the way you advance in your career. This book will be your guide to learning computer programming easily, helping you overcome the difficulties in understanding the major constructs in any mainstream programming language. Computer Programming for Absolute Beginners starts by taking you through the building blocks of any programming language with thorough explanations and relevant examples in pseudocode. You'll understand the relationship between computer programs and programming languages and how code is executed on the computer. The book then focuses on the different types of applications that you can create with your programming knowledge. You'll delve into programming constructs, learning all about statements, operators, variables, and data types. As you advance, you'll see how to control the flow of your programs using control structures and reuse your code using functions. Finally, you'll explore best practices that will help you write code like a pro. By the end of this book, you'll be prepared to learn any programming language and take control of your career by adding coding to your skill set. What you will learnGet to grips with basic programming language concepts such as variables, loops, selection and functionsUnderstand what a program is and how the computer executes itExplore different programming languages and learn about the relationship between source code and executable codeSolve problems using various paradigms such as procedural programming, object oriented programming, and functional programmingWrite high-quality code using several coding conventions and best practicesBecome well-versed with how to track and fix bugs in your programsWho this book is for This book is for beginners who have never programmed before and are looking to enter the world of programming. This includes anyone who is about to start studying programming and wants a head start, or simply wants to learn how to program on their own.

Discrete mathematics is the basis of much of computer science, from algorithms and automata theory to combinatorics and graph theory. Essential Discrete Mathematics for Computer Science aims to teach mathematical reasoning as well as concepts and skills by stressing the art of proof. It is fully illustrated in color, and each chapter includes a concise summary as well as a set of exercises.

Algorithms might sound like a complicated tech term, but don't be intimidated, people actually use them every day. Using accessible language and full-color photographs, this book simplifies algorithms in an easy-to-understand way. Readers will be amazed to learn that an algorithm is just a set of steps for computers to follow to get things done. STEM topics from the Next Generation Science Standards are emphasized throughout the text. Sidebars featuring key terms help readers grow their tech vocabulary, and fact boxes provide additional opportunities to learn.

Essential Computational Thinking: Computer Science from Scratch helps students build a theoretical and practical foundation for learning computer science. Rooted in fundamental science, this text defines elementary ideas including data and information, quantifies these ideas mathematically, and, through key concepts in physics and computation, demonstrates the relationship between computer science and the universe itself. In Part I, students explore the theoretical underpinnings of computer science in a wide-ranging manner. Readers receive a robust overview of essential computational theories and programming ideas, as well as topics that examine the mathematical and physical foundations of computer science. Part 2 presents the basics of computation and underscores programming as an invaluable tool in the discipline. Students can apply their newfound knowledge and begin writing substantial programs immediately. Finally, Part 3 explores more sophisticated computational ideas, including object-oriented programing, databases, data science, and some of the underlying principles of machine learning. Essential Computational Thinking is an ideal text for a firmly technical CS0 course in computer science. It is also a valuable resource for highly-motivated non-computer science majors at the undergraduate or graduate level who are interested in learning more about the discipline for either professional or personal development.

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

Perfect for anyone who needs a basic understanding of how computers work, this introductory guide gives friendly, accessible, up-to-date explanations of computer hardware, software, networks, and the Internet. Coverage also includes micro-processors, operating systems, programming languages, applications, and e-commerce.