Introduction To Programming Concepts With Case Studies In Python

The current text provides a clear introduction to Computer Science concepts in a programming environment. It is designed as suitable use in freshman- or introductory level coursework in CS and provides the fundamental concepts as well as abstract theorems for solving computational problems. The Python language serves as a medium for illustrating and demonstrating the concepts.

Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it. Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasizes important and engaging applications, not toy problems. The authors supply the tools needed for students to learn that programming is a natural, satisfying, and creative experience. This example-driven guide focuses on Python’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science. Coverage includes Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound Functions, modules, and libraries: organizing programs into components that can be independently debugged, maintained, and reused Object-oriented programming and data abstraction: objects, modularity, encapsulation, and more Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables Examples from applied math, physics, chemistry, biology, and computer science—all compatible with Python 2 and 3 Drawing on their extensive classroom experience, the authors provide Q&As, exercises, and opportunities for creative practice throughout. An extensive amount of supplementary information is available at introcs.cs.princeton.edu/python. With source code, I/O libraries, solutions to selected exercises, and much more, this companion website empowers people to use their own computers to teach and learn the material.

*Exclusive: Now get your $4 Google Play Books code to get this book for only $0,01!* Embark on an exciting journey into the world of programming with "Learn Coding with Python: Introduction to Programming with Python." This comprehensive guide is designed specifically for those with little or no programming experience, providing a gentle introduction to the Python programming language, one of the most versatile and popular languages in the world. Whether you're aspiring to become a developer, looking to automate tasks, or simply curious about programming, this book is your ideal starting point. With straightforward explanations, engaging examples, and practical exercises, you'll quickly grasp the fundamentals of programming and gain the confidence to create your own Python projects. By purchasing this book, you'll gain access to: A step-by-step introduction to Python programming, making it easy to follow even for complete beginners. Real-world examples and case studies, providing context and relevance to the concepts you learn. Interactive exercises to test your knowledge and reinforce your understanding. Don't miss this opportunity to kickstart your programming journey with Python! Get your copy today and unlock the countless possibilities that coding has to offer.

Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.

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 book describes the life cycle process of IP cores, from specification to production, including IP modeling, verification, optimization, and protection. Various trade-offs in the design process are discussed, including those associated with many of the most common memory cores, controller IPs and system-on-chip (SoC) buses. Readers will also benefit from the author’s practical coverage of new verification methodologies. such as bug localization, UVM, and scan-chain. A SoC case study is presented to compare traditional verification with the new verification methodologies. Discusses the entire life cycle process of IP cores, from specification to production, including IP modeling, verification, optimization, and protection; Introduce a deep introduction for Verilog for both implementation and verification point of view. Demonstrates how to use IP in applications such as memory controllers and SoC buses. Describes a new verification methodology called bug localization; Presents a novel scan-chain methodology for RTL debugging; Enables readers to employ UVM methodology in straightforward, practical terms.

This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts. The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester. Topics and features: Assumes no prior knowledge, and makes the transition from Python to Java a smooth process Features numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFX Explains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.