Introduction To Programming Concepts With Case Studies In Python
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| Author | : Göktürk Üçoluk |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 227 |
| Release | : 2012-10-29 |
| Genre | : Computers |
| ISBN | : 3709113431 |
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.
| Author | : Springer |
| Publisher | : |
| Total Pages | : 232 |
| Release | : 2012-10-30 |
| Genre | : |
| ISBN | : 9783709113448 |
| Author | : John M. Zelle |
| Publisher | : Franklin, Beedle & Associates, Inc. |
| Total Pages | : 533 |
| Release | : 2004 |
| Genre | : Computers |
| ISBN | : 1887902996 |
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.
| Author | : Jason R. Briggs |
| Publisher | : No Starch Press |
| Total Pages | : 365 |
| Release | : 2022-11-15 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 1718503032 |
The second edition of the best-selling Python for Kids—which brings you (and your parents) into the world of programming—has been completely updated to use the latest version of Python, along with tons of new projects! Python is a powerful programming language that’s easy to learn and fun to use! But books about programming in Python can be dull and that’s no fun for anyone. Python for Kids brings kids (and their parents) into the wonderful world of programming. Jason R. Briggs guides you through the basics, experimenting with unique (and hilarious) example programs featuring ravenous monsters, secret agents, thieving ravens, and more. New terms are defined; code is colored and explained; puzzles stretch the brain and strengthen understanding; and full-color illustrations keep you engaged throughout. By the end of the book, you’ll have programmed two games: a clone of the famous Pong, and “Mr. Stick Man Races for the Exit”—a platform game with jumps and animation. This second edition is revised and updated to reflect Python 3 programming practices. There are new puzzles to inspire you and two new appendices to guide you through Python’s built-in modules and troubleshooting your code. As you strike out on your programming adventure, you’ll learn how to: Use fundamental data structures like lists, tuples, and dictionaries Organize and reuse your code with functions and modules Use control structures like loops and conditional statements Draw shapes and patterns with Python’s turtle module Create games, animations, and other graphical wonders with tkinter Why should serious adults have all the fun? Python for Kids is your ticket into the amazing world of computer programming. Covers Python 3.x which runs on Windows, macOS, Linux, even Raspberry Pi
| Author | : Mark A. Kramer |
| Publisher | : MIT Press |
| Total Pages | : 385 |
| Release | : 2016-11-04 |
| Genre | : Science |
| ISBN | : 0262529378 |
A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data. As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis. The book begins with an introduction to MATLAB, the most common programming platform in neuroscience, which is used in the book. (Readers familiar with MATLAB can skip this chapter and might decide to focus on data type or method type.) The book goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each chapter offers a stand-alone case study that can be used separately as part of a targeted investigation. The book includes some mathematical discussion but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying MATLAB code are freely available on the authors' website. The book can be used for upper-level undergraduate or graduate courses or as a professional reference. A version of this textbook with all of the examples in Python is available on the MIT Press website.
| Author | : Joakim Sundnes |
| Publisher | : |
| Total Pages | : 157 |
| Release | : 2020 |
| Genre | : Computer programming |
| ISBN | : 3030503569 |
This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.
| Author | : Allen B. Downey |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 309 |
| Release | : 2015-12-02 |
| Genre | : Computers |
| ISBN | : 1491939419 |
If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, youâ??ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand objects, methods, and object-oriented programming Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design, data structures, and GUI-based programs through case studies
| Author | : Laura Igual |
| Publisher | : Springer |
| Total Pages | : 227 |
| Release | : 2017-02-22 |
| Genre | : Computers |
| ISBN | : 3319500171 |
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
| Author | : Arvind Kumar Bansal |
| Publisher | : CRC Press |
| Total Pages | : 628 |
| Release | : 2013-12-14 |
| Genre | : Computers |
| ISBN | : 1466565144 |
In programming courses, using the different syntax of multiple languages, such as C++, Java, PHP, and Python, for the same abstraction often confuses students new to computer science. Introduction to Programming Languages separates programming language concepts from the restraints of multiple language syntax by discussing the concepts at an abstract level. Designed for a one-semester undergraduate course, this classroom-tested book teaches the principles of programming language design and implementation. It presents: Common features of programming languages at an abstract level rather than a comparative level The implementation model and behavior of programming paradigms at abstract levels so that students understand the power and limitations of programming paradigms Language constructs at a paradigm level A holistic view of programming language design and behavior To make the book self-contained, the author introduces the necessary concepts of data structures and discrete structures from the perspective of programming language theory. The text covers classical topics, such as syntax and semantics, imperative programming, program structures, information exchange between subprograms, object-oriented programming, logic programming, and functional programming. It also explores newer topics, including dependency analysis, communicating sequential processes, concurrent programming constructs, web and multimedia programming, event-based programming, agent-based programming, synchronous languages, high-productivity programming on massive parallel computers, models for mobile computing, and much more. Along with problems and further reading in each chapter, the book includes in-depth examples and case studies using various languages that help students understand syntax in practical contexts.
| Author | : Robert Sedgewick |
| Publisher | : Addison-Wesley Professional |
| Total Pages | : 1487 |
| Release | : 2015-05-27 |
| Genre | : Computers |
| ISBN | : 0134076524 |
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.
