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Introduction to Computer Science provides a comprehensive foundation in core Computer Science concepts and principles, aligning with the scope and sequence of most introductory Computer Science courses. The offering serves as an engaging entry point for students pursuing diverse fields of study and employment, including Computer Science, business, engineering, Data Science, social sciences, and related disciplines. By addressing a broad learner audience—ranging from Computer Science majors to non-majors—the book offers a thorough introduction to computational thinking and its applications across multiple domains.
This book will introduce the computational thinking aspects of problem-solving and analytical thinking that enable the study of algorithms, which are step-by-step instructions for solving specific problems or carrying out computations. Therefore, this book also covers algorithms and their realization via programming languages, computer systems architectures, networks, and operating systems. The book subsequently delves into Computer Science areas that enable the design and development of software solutions using high-level programming languages (i.e., coding languages designed to be more intuitive for humans), architectural styles and related models, data management systems, and software engineering. Finally, the book demonstrates how to leverage computer science realizations and areas to build modern end-to-end solutions to business and social problems. In particular, the book focuses on modern web applications development, cloud-native applications development, and hybrid Cloud/on-premise digital solutions. The various chapters emphasize how to achieve software solution qualities such as performance and scalability. The last chapter explains how to secure software applications and their applications in the context of various cyber threats. It also explains how to make the right decisions about using computers and information in society to navigate social, ethical, economic, and political issues that could result from the misuse of technology. To conclude this textbook, we’ll introduce you to cybersecurity and help you understand why responsible computing is essential to promote ethical behavior in computer science. The book is designed to help students grasp the full meaning of computer science as a tool that can help them think, build meaningful solutions to complex problems, and motivate their careers in information technology (IT).
An algorithm is a sequence of precise instructions that operate on data. We can think of recipes, plans, or instructions from our daily lives as examples of algorithms. Computers can only execute a finite pre-defined set of instructions exactly as instructed, which is why programming can feel like such a different way of communicating as compared to our natural human languages. A program is an implementation (realization) of an algorithm written in a formal programming language. Although each programming language is different from all the others, there are still common ideas across all of them. Knowing just a few of these common ideas enables computer scientists to address a wide variety of problems without having to start from scratch every single time. The study of data structures and algorithms focuses on identifying what is known as a canonical algorithm: a well-known algorithm that showcases design principles helpful across a wide variety of problems.
Computer scientists have created programming languages which are designed specifically for programmers to develop practical applications. These languages are usually classified into high-level (Java, Python) and low-level languages (assembly language). A high-level programming language operates at a high level of abstraction, meaning that low-level details such as the management of memory are automated. In contrast, a low-level programming language operates at a low level of abstraction. Languages like C and C   can perform both high-level and low-level tasks