Introduction to Computer Security is a new Computer Security textbook for a new generation of IT professionals. It is ideal for computer-security courses that are taught at the undergraduate level and that have as their sole prerequisites an introductory computer science sequence (e.g., CS 1/CS 2).
This book is for anyone who wants to understand computer programming. You'll learn to program in a language that' s used in millions of smartphones, tablets, and PCs. You'll code along with the book, writing programs to solve real-world problems as you learn the fundamentals of programming using Python 3. You'll learn about design, algorithms, testing, and debugging, and come away with all the tools you need to produce quality code. In this second edition, we've updated almost all the material, incorporating the lessons we've learned over the past five years of teaching Python to people new to programming.You don't need any programming experience to get started. First, you'll get a detailed introduction to Python and to programming. You'll find out exactly what happens when your programs are executed. Through real-world examples, you'll learn how to work with numbers, text, big data sets, and files. Then you'll see how to create and use your own data types.The incremental examples show you the steps and missteps that happen while developing programs, so you know what to expect when you tackle a problem on your own. Inspired by "How to Design Programs" (HtDP), you'll learn a six-step recipe for designing functions, which helps you as you start to learn the concepts--and becomes an integral part of writing programs by the end.As you learn to use the fundamental programming tools in the first half of the book, you'll see how to document and organize your code so that you and other programmers can more easily read and understand it. Beyond the basics, you'll learn how to ensure that your programs are reliable, and how to work with databases, download data from the web automatically, and build user interfaces. Most importantly, you'll learn how to think like a professional programmer.You'll need to download Python 3, available from "python.org". With that download comes IDLE, the editor we use for writing and running Python programs. (If you use Linux, you may need to installPython 3 and IDLE separately.)
The Raspberry Pi is a credit card-sized computer that plugs into your TV and a keyboard. It is a capable little computer which can be used in electronics projects, and for many of the things that your desktop PC does, like spreadsheets, word processing, browsing the internet, and playing games. It also plays high-definition video. This book takes you step-by-step through many fun and educational possibilities. Take advantage of several preloaded programming languages. Use the Raspberry Pi with Arduino. Create Internet-connected projects. Play with multimedia. With Raspberry Pi, you can do all of this and more.
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 a massive open online course (or MOOC) offered by the pioneering MIT-Harvard collaboration edX.
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. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. 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. Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.
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