Glencoe?'s Introduction to Computer Science Using Java provides students with a highly visual way of learning Java programming. This colorful text provides the information needed for students enrolled in Computer Science I courses, and for students planning to take the AP Computer Science A exam (which has recently switched from C++ to Java). An AP correlation chart is provided in the student edition to help readers locate information that is relevant to the A exam, and ?AP Exam Prep? exercises throughout the book help students prepare for the AP test. The availableÂ Teacher Resource Manual also provides AP information and resources for teachers, and links to important AP sites can be found on the book?'s Web site.
The textbook immediately introduces students to concepts that are essential to object-oriented programming and develops these concepts throughout various code programs and examples. Programs are examined line-by-line through in-text code blocks. Complete programs are then provided for students to compile and run. The output for every program is also provided either in the book or on the teacher CD so students can see what happens when the code is run.
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.
This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. Â The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional.
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