Applied Computational Thinking with Python

420 Pages·2020·4.671 MB·English

by  Sofía De Jesús, Dayrene Martinez

Applied
Computational
Thinking with
Python
Design algorithmic solutions for complex and
challenging real-world problems
Sofía De Jesús
Dayrene Martinez
BIRMINGHAM—MUMBAI
Applied Computational Thinking with Python
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To my parents, Elia and Miguel, and to my siblings, Rebeca, Graciela, and
Miguelito, without whom I wouldn't be who I am or have been able to have
the experiences that got me here. I love you all. And to Kristen McKeen,
Will Murchison, Teresa Caro, and Joel Socarrás, friends without whom
I couldn't survive this life.
- Sofía De Jesús
To my loving mother, Xiomara Garcia, for the everlasting support and
love, and to my siblings, Karlyn and Junior Martinez, for being great role
models—you guys inspire me every day. And to Samantha Tolentino
Benitez, Noemi Reyes, Rosemary Vergara, Pedro Peralta, Charles Ozuna,
and Gabriel Alatorre for being the best listeners when I needed it most.
I am grateful for all of you.
- Dayrene Martinez
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Contributors
About the authors
Sofía De Jesús is a computational thinking teacher with a degree from the University
of Puerto Rico with a focus on math. She has a master's degree from the University of
Dayton. Her experience in education and development spans two decades. She has worked
with clients to develop solutions in multiple programming languages. As a teacher, Sofía
helps students incorporate the philosophy of computational thinking in courses such as
game design, circuits, Python, web design, and robotics. She likes to play video games and
spend time with her 11 year-old Yorkie, King Kong. Sofía also enjoys creating materials,
small furniture, and jewelry using CNC machines and laser cutters. She enjoys spending
as much time in Puerto Rico as work and life permits.
I started this book before the world changed in 2020. If it wasn't for
my family, my co-author, Dayrene, Gregg Moses, Emily Joyce, Princess
Harrison, Brooke Marcy, and so many others who stepped up and held me
up, this book would not have been possible. Thank you.
Dayrene Martinez is a systems engineer in the defense industry where she develops
neural networks embedded in real-time software to aid in decision making for aerospace
vehicles. She received a B.S. in electrical engineering from the New Jersey Institute of
Technology (NJIT). Dayrene is passionate about STEM education and spends her free
time in a voluntary capacity inspiring the next generation of engineers. She is an active
supporter and keynote speaker for the non-profit organization Latinas in STEM. She
teaches circuitry, robotic design, and software engineering to middle and high school
students.
I would like to thank my co-author, Sofía, for helping me accomplish one
of my lifetime goals—publishing a book. I would also like to thank Colin
Pouchet and Scott Terhorst for your encouragement and guidance at work.
I would also like to thank Greg Wagner, my boss, for stimulating my interest
in machine learning by giving me challenging work, and Jaz Carvajal,
without whom I would not even be an engineer. Thank you for being the
best and most supportive mentor.
About the reviewer
Dr. Gowrishankar S. is currently working as associate professor in the department
of computer science and engineering at the Dr. Ambedkar Institute of Technology,
Bengaluru, Karnataka, India. His current research interests are mainly focused on data
science, including its technical aspects, as well as its applications and implications.
Specifically, he is interested in the applications of machine learning, data mining, and big
data analytics in healthcare.
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Table of Contents
Preface
Section 1:
Introduction to Computational Thinking
1
Fundamentals of Computer Science
Technical requirements 4 Computational number theory 17
Introduction to computer science 4
Learning about a system's
Learning about computers and the software 18
binary system 4
Operating systems 19
Understanding theoretical Application software 19
computer science 8
Understanding computing 20
Algorithms 8
Architecture 20
Coding theory 10
Programming languages 22
Computational biology 13
Data structures 13 Learning about data types and
Information theory 14 structures 24
Automata theory 16 Data types 24
Formal language theory 16 Data structures 25
Symbolic computation 16
Summary 26
Computational geometry 17
2
Elements of Computational Thinking
Technical requirements 28 Problem 2 - Mathematical algorithms
and generalization 34
Understanding computational
thinking 28
Generalizing patterns 34
Problem 1 - Conditions 30
Designing algorithms 35
Decomposing problems 33 Additional problems 38
Recognizing patterns 33 Problem 2 - Children's soccer party 39
Problem 3 - Savings and interest 40
Summary 43
3
Understanding Algorithms and Algorithmic Thinking
Technical requirements 46 Designing algorithms 50
Defining algorithms in depth 46 Problem 1 – An office lunch 51
Algorithms should be clear and Problem 2 – A catering company 54
unambiguous 47
Analyzing algorithms 56
Algorithms should have inputs and
Algorithm analysis 1 – States and capitals 57
outputs that are well defined 47
Algorithm analysis 2 – Terminating or
Algorithms should have finiteness 48
not terminating? 60
Algorithms have to be feasible 50
Algorithms are language-independent 50 Summary 61
4
Understanding Logical Reasoning
Technical requirements 64 The and operator 78
Understanding the importance The or operator 79
of logical reasoning 64 The not operator 80
Applying inductive reasoning 65 Identifying logic errors 81
Applying deductive reasoning 69
Summary 85
Using Boolean logic and
operators 76