You're reading from Applied Computational Thinking with Python Design algorithmic solutions for complex and challenging real-world problems

Product type Paperback

Published in Nov 2020

Publisher Packt

ISBN-13 9781839219436

Length 420 pages

Edition 1st Edition

Languages

Python

Concepts

Design

Authors (2):

Dayrene Martinez

Sofía De Jesús

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Table of Contents (21) Chapters

Preface

1. Section 1: Introduction to Computational Thinking

2. Chapter 1: Fundamentals of Computer Science FREE CHAPTER

3. Chapter 2: Elements of Computational Thinking

4. Chapter 3: Understanding Algorithms and Algorithmic Thinking

5. Chapter 4: Understanding Logical Reasoning

6. Chapter 5: Exploring Problem Analysis

7. Chapter 6: Designing Solutions and Solution Processes

8. Chapter 7: Identifying Challenges within Solutions

9. Section 2:Applying Python and Computational Thinking

10. Chapter 8: Introduction to Python

11. Chapter 9: Understanding Input and Output to Design a Solution Algorithm

12. Chapter 10: Control Flow

13. Chapter 11: Using Computational Thinking and Python in Simple Challenges

14. Section 3:Data Processing, Analysis, and Applications Using Computational Thinking and Python

15. Chapter 12: Using Python in Experimental and Data Analysis Problems

16. Chapter 13: Using Classification and Clusters

17. Chapter 14: Using Computational Thinking and Python in Statistical Analysis

18. Chapter 15: Applied Computational Thinking Problems

19. Chapter 16: Advanced Applied Computational Thinking Problems

20. Other Books You May Enjoy

To get the most out of this book

You will need to have Python 3.9 installed on your computer in order to run the codes. All code examples have been tested on a Windows operating system using Python 3.9 and should run in subsequent releases. All code has also been tested using the Anaconda virtual environment.

Additional libraries and packages used in this book include the following:

NumPy
Scikit-Learn
TensorFlow/Keras
Matplotlib
Seaborn
Cairos
NLTK
Pandas

If you would like to run the code using a Spyder environment or Jupyter notebook, you can install Anaconda, an environment manager for Python and R programming languages.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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Table of Contents (21) Chapters

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