This is a textbook for a one quarter introductory present concerns essays cs lewis in theoretical computer science. It includes topics from propositional and predicate logic, proof techniques, set theory and the theory of computation, along with practical applications to CS.

Using examples from the publishing industry, Whitington introduces the fascinating discipline of Computer Science to the uninitiated. A draft of text book for Computer Science I, covering CS1 topics in a generic manner using psuedocode with supplemental parts for specific languages. Programming is a necessary skill, but it is only the beginning. This book will familiarize you with the Scratch visual programming environment, focusing on using Scratch to learn computer science. Each concept is introduced in order to solve a specific task such as animating dancing images or building a game. Data Science is about drawing useful conclusions from large and diverse data sets through exploration, prediction, and inference. The objective of this book is to provide the reader with all the necessary elements to get him or her started in the modern field of informatics and to allow him or her to become aware of the relationship between key areas of computer science.

Our objective is to provide an introduction to computer science as an intellectually vibrant field rather than focusing exclusively on computer programming. We emphasize concepts and problem-solving over syntax and programming language features. The book covers material on logic, sets, and functions that would often be taught in a course in discrete mathematics. The second part covers automata, formal languages, and grammar that would ordinarily be encountered in an upper level course. This book provides a survey of basic mathematical objects, notation, and techniques useful in later computer science courses. It gives a brief introduction to some key topics: algorithm analysis and complexity, automata theory, and computability. This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.