Discovering computer science : interdisciplinary problems, principles and python programming / Jessen Havill
Material type:
- 9781482254143
- QA 76 .H38 2016

Item type | Current library | Home library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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National University - Manila | LRC - Graduate Studies General Circulation | Gen. Ed. - CCIT | GC QA 76 .H38 2016 (Browse shelf(Opens below)) | c.1 | Available | NULIB000014072 |
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GC QA 267 .S57 2013 Introduction to the theory of computation / | GC QA 297 .B88 2014 Numerical methods and optimization : an introduction / | GC QA 76 .C57 2014 Computing handbook / | GC QA 76 .H38 2016 Discovering computer science : interdisciplinary problems, principles and python programming / | GC Q 181 .L39 2015 Data science in higher education / | GC Q 335 .H43 2013 Artificial intelligence for humans : volume 1 fundamental algorithms / | GC Q 335 .S78 2015 Artificial intelligence : A modern approach / |
Includes bibliographical references and index.
What is computation? -- Elementary computations -- Visualizing abstraction -- Growth and decay -- Forks in the road -- Text, documents, and DNA -- Designing programs -- Data analysis -- Flatland -- Self-similarity and recursion -- Organizing data -- Networks -- Abstract data types.
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.
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