Learn the basics of computer science through coding with Scratch, App Inventor, Alice, and HTML.

Computer Science: A Concise Introduction covers the fundamentals of computer science. The book describes micro-, mini-, and mainframe computers and their uses; the ranges and types of computers and peripherals currently available; applications to numerical computation; and commercial data processing and industrial control processes. The functions of data preparation, data control, computer operations, applications programming, systems analysis and design, database administration, and network control are also encompassed. The book then discusses batch, on-line, and real-time systems; the basic concepts of computer architecture; and the characteristics of main memory and backing storage. The main characteristics of common types of input, output, and input/output devices used in commercial computer applications and data transmission system are also considered. The book tackles the organization and accessing of serial, sequential, and indexed sequential file; file processing and management; and the concepts and functions of operating systems. The text describes on-line and off-line programming methods as well. Computer science students will find the book useful.

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.

This text strikes a good balance between rigor and an intuitive approach to computer theory. Covers all the topics needed by computer scientists with a sometimes humorous approach that reviewers found "refreshing". It is easy to read and the coverage of mathematics is fairly simple so readers do not have to worry about proving theorems.

Classroom-tested by tens of thousands of students, this new edition of the bestselling intro to programming book is for anyone who wants to understand computer science. Learn about design, algorithms, testing, and debugging. Discover the fundamentals of programming with Python 3.6--a language that's used in millions of devices. Write programs to solve real-world problems, and come away with everything you need to produce quality code. This edition has been updated to use the new language features in Python 3.6.

An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to

Discusses most ideas behind a computer in a simple and straightforward manner. The book is also useful to computer enthusiasts who wish to gain fundamental knowledge of computers.

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.

The modern computer is so powerful that a casual knowledge of programming suffices for most of its users. However, a variety of circumstances can abruptly require a much deeper understanding: the need to structure a program carefully to avoid being overwhelmed by its complexity, the need to insure reliability beyond what can be achieved by debugging, or the need to utilize computing resources efficiently. Beyond such practical considerations is an inherent intellectual satisfaction in mastering the fundamental concepts of programming. The aim of this book is to provide such mastery concept by concept.