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Jessen Havill - Discovering Computer Science : Interdisciplinary Problems, Principles, and Python Programming

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Jessen Havill Discovering Computer Science : Interdisciplinary Problems, Principles, and Python Programming
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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 books 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. Read more...
Abstract: 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 books 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

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DISCOVERING COMPUTER SCIENCE Interdisciplinary Problems Principles and - photo 1

DISCOVERING
COMPUTER
SCIENCE

Interdisciplinary Problems,
Principles, and Python
Programming

CHAPMAN & HALL/CRC
TEXTBOOKS IN COMPUTING

Series Editors

John Impagliazzo

Andrew McGettrick

Professor Emeritus, Hofstra University

Department of Computer and Information Sciences University of Strathclyde

Aims and Scope

This series covers traditional areas of computing, as well as related technical areas, such as software engineering, artificial intelligence, computer engineering, information systems, and information technology. The series will accommodate textbooks for undergraduate and graduate students, generally adhering to worldwide curriculum standards from professional societies. The editors wish to encourage new and imaginative ideas and proposals, and are keen to help and encourage new authors. The editors welcome proposals that: provide groundbreaking and imaginative perspectives on aspects of computing; present topics in a new and exciting context; open up opportunities for emerging areas, such as multi-media, security, and mobile systems; capture new developments and applications in emerging fields of computing; and address topics that provide support for computing, such as mathematics, statistics, life and physical sciences, and business.

Published Titles

Paul Anderson, Web 2.0 and Beyond: Principles and Technologies

Henrik Brbak Christensen, Flexible, Reliable Software: Using Patterns and Agile Development

John S. Conery, Explorations in Computing: An Introduction to Computer Science

John S. Conery, Explorations in Computing: An Introduction to Computer Science and Python Programming

Jessen Havill, Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming

Ted Herman, A Functional Start to Computing with Python

Pascal Hitzler, Markus Krtzsch, and Sebastian Rudolph, Foundations of Semantic Web Technologies

Mark J. Johnson, A Concise Introduction to Data Structures using Java

Mark J. Johnson, A Concise Introduction to Programming in Python

Lisa C. Kaczmarczyk, Computers and Society: Computing for Good

Mark C. Lewis, Introduction to the Art of Programming Using Scala

Bill Manaris and Andrew R. Brown, Making Music with Computers: Creative Programming in Python

Uvais Qidwai and C.H. Chen, Digital Image Processing: An Algorithmic Approach with MATLAB

David D. Riley and Kenny A. Hunt, Computational Thinking for the Modern Problem Solver

Henry M. Walker, The Tao of Computing, Second Edition

CHAPMAN & Hall/CRC
TEXTBOOKS IN COMPUTING

DISCOVERING
COMPUTER
SCIENCE

Interdisciplinary Problems,
Principles, and Python
Programming

Jessen Havill

Denison University

Granville, Ohio, USA

CRC Press Taylor Francis Group 6000 Broken Sound Parkway NW Suite 300 Boca - photo 2

CRC Press
Taylor & Francis Group
6000 Broken Sound Parkway NW, Suite 300
Boca Raton, FL 33487-2742

2016 by Taylor & Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business

No claim to original U.S. Government works

Version Date: 20150318

International Standard Book Number-13: 978-1-4987-8674-4 (eBook - EPUB3)

This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint.

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I N my view, an introductory computer science course should strive to accomplish three things. First, it should demonstrate to students how computing has become a powerful mode of inquiry, and a vehicle of discovery, in a wide variety of disciplines. This orientation is also inviting to students of the natural and social sciences, who increasingly benefit from an introduction to computational thinking, beyond the limited black box recipes often found in manuals. Second, the course should engage students in computational problem solving, and lead them to discover the power of abstraction, efficiency, and data organization in the design of their solutions. Third, the course should teach students how to implement their solutions as computer programs. In learning how to program, students more deeply learn the core principles, and experience the thrill of seeing their solutions come to life.

Unlike most introductory computer science textbooks, which are organized around programming language constructs, I deliberately lead with interdisciplinary problems and techniques. This orientation is more interesting to a more diverse audience, and more accurately reflects the role of programming in problem solving and discovery. A computational discovery does not, of course, originate in a programming language feature in search of an application. Rather, it starts with a compelling problem which is modeled and solved algorithmically, by leveraging abstraction and prior experience with similar problems. Only then is the solution implemented as a program.

Like most introductory computer science textbooks, I introduce programming skills in an incremental fashion, and include many opportunities for students to practice them. The topics in this book are arranged to ease students into computational thinking, and encourage them to incrementally build on prior knowledge. Each chapter focuses on a general class of problems that is tackled by new algorithmic techniques and programming language features. My hope is that students will leave the course, not only with strong programming skills, but with a set of problem solving strategies and simulation techniques that they can apply in their future work, whether or not they take another computer science course.

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