Discovering Computer Science: Interdisciplinary Problems, Principles, and Python

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Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming
Author: Jessen Havill
Pub Date: 2015
ISBN: 978-1482254143
Pages: 750
Language: English
Format: PDF
Size: 62 Mb

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 sophis
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 ― 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.

Table of Contents
1: What is computation?
2: Elementary computations
3: Visualizing abstraction
4: Growth and decay
5: Forks in the road
6: Text, documents, and DNA
7: Designing programs
8: Data analysis
9: Flatland
10: Self-similarity and recursion
11: Organizing data
12: Networks
13: Abstract data types
A: Installing Python
B: Python library reference

                                                                       

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