Discovering Computer Science

Discovering Computer Science PDF

Author: Jessen Havill

Publisher: CRC Press

Published: 2020-10-12

Total Pages: 522

ISBN-13: 1000218481

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"Havill's problem-driven approach introduces algorithmic concepts in context and motivates students with a wide range of interests and backgrounds." -- Janet Davis, Associate Professor and Microsoft Chair of Computer Science, Whitman College "This book looks really great and takes exactly the approach I think should be used for a CS 1 course. I think it really fills a need in the textbook landscape." -- Marie desJardins, Dean of the College of Organizational, Computational, and Information Sciences, Simmons University "Discovering Computer Science is a refreshing departure from introductory programming texts, offering students a much more sincere introduction to the breadth and complexity of this ever-growing field." -- James Deverick, Senior Lecturer, The College of William and Mary "This unique introduction to the science of computing guides students through broad and universal approaches to problem solving in a variety of contexts and their ultimate implementation as computer programs." -- Daniel Kaplan, DeWitt Wallace Professor, Macalester College Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming is a problem-oriented introduction to computational problem solving and programming in Python, appropriate for a first course for computer science majors, a more targeted disciplinary computing course or, at a slower pace, any introductory computer science course for a general audience. Realizing that an organization around language features only resonates with a narrow audience, this textbook instead connects programming to students’ prior interests using a range of authentic problems from the natural and social sciences and the digital humanities. The presentation begins with an introduction to the problem-solving process, contextualizing programming as an essential component. Then, as the book progresses, each chapter guides students through solutions to increasingly complex problems, using a spiral approach to introduce Python language features. The text also places programming in the context of fundamental computer science principles, such as abstraction, efficiency, testing, and algorithmic techniques, offering glimpses of topics that are traditionally put off until later courses. This book contains 30 well-developed independent projects that encourage students to explore questions across disciplinary boundaries, over 750 homework exercises, and 300 integrated reflection questions engage students in problem solving and active reading. The accompanying website — https://www.discoveringcs.net — includes more advanced content, solutions to selected exercises, sample code and data files, and pointers for further exploration.

Discovering Computer Science

Discovering Computer Science PDF

Author: Jessen Havill

Publisher: CRC Press

Published: 2020-10-27

Total Pages: 543

ISBN-13: 1000218465

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"Havill's problem-driven approach introduces algorithmic concepts in context and motivates students with a wide range of interests and backgrounds." -- Janet Davis , Associate Professor and Microsoft Chair of Computer Science, Whitman College "This book looks really great and takes exactly the approach I think should be used for a CS 1 course. I think it really fills a need in the textbook landscape." -- Marie desJardins, Dean of the College of Organizational, Computational, and Information Sciences, Simmons University "Discovering Computer Science is a refreshing departure from introductory programming texts, offering students a much more sincere introduction to the breadth and complexity of this ever-growing field." -- James Deverick, Senior Lecturer, The College of William and Mary "This unique introduction to the science of computing guides students through broad and universal approaches to problem solving in a variety of contexts and their ultimate implementation as computer programs." -- Daniel Kaplan, DeWitt Wallace Professor, Macalester College Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming is a problem-oriented introduction to computational problem solving and programming in Python, appropriate for a first course for computer science majors, a more targeted disciplinary computing course or, at a slower pace, any introductory computer science course for a general audience. Realizing that an organization around language features only resonates with a narrow audience, this textbook instead connects programming to students’ prior interests using a range of authentic problems from the natural and social sciences and the digital humanities. The presentation begins with an introduction to the problem-solving process, contextualizing programming as an essential component. Then, as the book progresses, each chapter guides students through solutions to increasingly complex problems, using a spiral approach to introduce Python language features. The text also places programming in the context of fundamental computer science principles, such as abstraction, efficiency, testing, and algorithmic techniques, offering glimpses of topics that are traditionally put off until later courses. This book contains 30 well-developed independent projects that encourage students to explore questions across disciplinary boundaries, over 750 homework exercises, and 300 integrated reflection questions engage students in problem solving and active reading. The accompanying website — https://www.discoveringcs.net — includes more advanced content, solutions to selected exercises, sample code and data files, and pointers for further exploration.

Discovering Computer Science

Discovering Computer Science PDF

Author: Jessen Havill

Publisher: CRC Press

Published: 2016-07-06

Total Pages: 800

ISBN-13: 149878674X

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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.

Computer Science: Discovering God's Glory in Ones and Zeros

Computer Science: Discovering God's Glory in Ones and Zeros PDF

Author: Jonathan R. Stoddard

Publisher: P & R Publishing

Published: 2015-03-16

Total Pages: 32

ISBN-13: 9781596389908

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What does computer programming have to do with God? Discover how writing code gives programmers a unique insight into Gods all-powerful word, and how constructing software can glorify him.

Discovering Computers

Discovering Computers PDF

Author: Gary B. Shelly

Publisher:

Published: 2004

Total Pages: 0

ISBN-13: 9780619202224

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We are excited to announce the publication of the ground-breaking Discovering Computers: Fundamentals Edition. This book is the Shelly Cashman Series answer to the many requests we have received from instructors and students for a textbook that provides a succinct, yet thorough, introduction to computers. Discovering Computers: Fundamentals Edition covers the same breadth of topics as our well-known Discovering Computers 2005: Complete, but the depth of coverage focuses on the basic knowledge required to be computer literate in today's digital world. This text is perfect for a short course on computer concepts, or a full semester course that also teaches applications or programming.

Discovering Computers 2005

Discovering Computers 2005 PDF

Author: Gary B. Shelly

Publisher:

Published: 2004

Total Pages: 308

ISBN-13: 9780619255251

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For the past three decades, the Shelly Cashman Series has effectively introduced computers to millions of students - consistently providing the highest quality, most up-to-date, and innovative materials in computer education. This new edition employs the proven Shelly Cashman approach to learning, presents fundamental computer concepts in a clear writing style, and includes extensive end-of-chapter exercises. The book's visually appealing layout keeps students interested and allows them to receive the most interactive learning experience on computer concepts.

Feature Selection for Knowledge Discovery and Data Mining

Feature Selection for Knowledge Discovery and Data Mining PDF

Author: Huan Liu

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 225

ISBN-13: 1461556899

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As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.