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Introduction To Programming In Python

Author: Robert Sedgewick
Publisher: Addison-Wesley Professional
ISBN: 0134076524
Size: 73.49 MB
Format: PDF
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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.

New Directions For Computing Education

Author: Samuel B. Fee
Publisher: Springer
ISBN: 3319542265
Size: 21.47 MB
Format: PDF, Kindle
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Why should every student take a computing course? What should be the content of these courses? How should they be taught, and by whom? This book addresses these questions by identifying the broader reaches of computing education, problem-solving and critical thinking as a general approach to learning. The book discusses new approaches to computing education, and considers whether the modern ubiquity of computing requires an educational approach that is inherently interdisciplinary and distinct from the traditional computer science perspective. The alternative approach that the authors advocate derives its mission from an intent to embed itself within an interdisciplinary arts and science context. An interdisciplinary approach to computing is compellingly valuable for students and educational institutions alike. Its goal is to support the educational and intellectual needs of students with interests in the entire range of academic disciplines. It capitalizes on students’ focus on career development and employers’ demand for technical, while also engaging a diverse student body that may not possess a pre-existing interest in computing for computing’s sake. This approach makes directly evident the applicability of computer science topics to real-world interdisciplinary problems beyond computing and recognizes that technical and computational abilities are essential within every discipline. The book offers a valuable resource for computer science and computing education instructors who are presently re-thinking their curricula and pedagogical approaches and are actively trying new methods in the classroom. It will also benefit graduate students considering a future of teaching in the field, as well as administrators (in both higher education and high schools) interested in becoming conversant in the discourse surrounding the future of computing education.

A Concise Introduction To Programming In Python

Author: Mark J. Johnson
Publisher: CRC Press
ISBN: 1351621998
Size: 46.84 MB
Format: PDF, ePub, Docs
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A Concise Introduction to Programming in Python, Second Edition provides a hands-on and accessible introduction to writing software in Python, with no prior programming experience required. The Second Edition was thoroughly reorganized and rewritten based on classroom experience to incorporate: A spiral approach, starting with turtle graphics, and then revisiting concepts in greater depth using numeric, textual, and image data Clear, concise explanations written for beginning students, emphasizing core principles A variety of accessible examples, focusing on key concepts Diagrams to help visualize new concepts New sections on recursion and exception handling, as well as an earlier introduction of lists, based on instructor feedback The text offers sections designed for approximately one class period each, and proceeds gradually from procedural to object-oriented design. Examples, exercises, and projects are included from diverse application domains, including finance, biology, image processing, and textual analysis. It also includes a brief "How-To" sections that introduce optional topics students may be interested in exploring. The text is written to be read, making it a good fit in flipped classrooms. Designed for either classroom use or self-study, all example programs and solutions to odd-numbered exercises (except for projects) are available at: http://www.central.edu/go/conciseintro/.

Discovering Computer Science

Author: Jessen Havill
Publisher: CRC Press
ISBN: 1482254166
Size: 40.69 MB
Format: PDF, Kindle
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Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines. With a principles-oriented introduction to computational thinking, the text provides a broader and deeper introduction to computer science than typical introductory programming books. Organized around interdisciplinary problem domains, rather than programming language features, each chapter guides students through increasingly sophisticated algorithmic and programming techniques. The author uses a spiral approach to introduce Python language features in increasingly complex contexts as the book progresses. The text places programming in the context of fundamental computer science principles, such as abstraction, efficiency, and algorithmic techniques, and offers overviews of fundamental topics that are traditionally put off until later courses. The book includes thirty well-developed independent projects that encourage students to explore questions across disciplinary boundaries. Each is motivated by a problem that students can investigate by developing algorithms and implementing them as Python programs. The book's accompanying website — http://discoverCS.denison.edu — includes sample code and data files, pointers for further exploration, errata, and links to Python language references. Containing over 600 homework exercises and over 300 integrated reflection questions, this textbook is appropriate for a first computer science course for computer science majors, an introductory scientific computing course or, at a slower pace, any introductory computer science course.

Introduction To Data Science

Author: Laura Igual
Publisher: Springer
ISBN: 3319500171
Size: 80.55 MB
Format: PDF
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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.

Learning Scipy For Numerical And Scientific Computing

Author: Francisco J. Blanco-Silva
Publisher: Packt Publishing Ltd
ISBN: 1782161635
Size: 78.48 MB
Format: PDF, Docs
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A step-by-step practical tutorial with plenty of examples on research-based problems from various areas of science, that prove how simple, yet effective, it is to provide solutions based on SciPy.This book is targeted at anyone with basic knowledge of Python, a somewhat advanced command of mathematics/physics, and an interest in engineering or scientific applications---this is broadly what we refer to as scientific computing.This book will be of critical importance to programmers and scientists who have basic Python knowledge and would like to be able to do scientific and numerical computations with SciPy.

Wiser 2004

Author: ACM Sigsoft
Publisher: Association for Computing Machinery (ACM)
ISBN:
Size: 57.41 MB
Format: PDF, Docs
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