Introduction to Data Science Using Python

by Afrand Agah, Ph.D.

Keywords: Data Science, Machine Learning, Python
ePub
PDF

Agah's book cover

About the Book

This book contains two parts, the first is designed to be used in an introductory programming course for students looking to learn Python, without having any prior experience with programming. Basic programming concepts are discussed, explained, and illustrated with a Python program. Ample programming questions are provided for practice. The second part of the book utilizes machine-learning concepts and statistics to accomplish data-driven resolutions. Python programs are provided to apply scientific computing to conclude statistically driven results.

Chapters

  1. Installing Python
  2. Introduction to Pragramming
  3. Decision Structures
  4. Repetitions
  5. Functions
  6. Recursion
  7. File Access
  8. Lists
  9. Arrays
  10. Plotting Graphs
  11. Object Oriented Programming
  12. Using Python Packages
  13. Python and Graph Theory
  14. Python and Machine Learning
  15. Python and Statistics

General Information

  • Publication Year: 2024
  • Edition: First
  • Subject: Computer Programming

License

cc by-nc

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0) as a part of PA-ADOPT, except where otherwise noted.

Usage

Readers

The eTextbooks created as a part of this program are provided in two formats: ePub and PDF. Please refer to our Reader Support section for guidance on which format may be best for you and the device(s) you use.

Instructors

If you are an instructor seeking to use this eTextbook in your own course(s) please feel free to download the ePub and/or PDF file(s) for your use, but make sure to complete our eTextbook Usage Survey (this information is used for program evaluation purposes).

If you are interested in making revisions and edits to this eTextbook please note that this is possible since the book is under a Creative Commons License, which allows you to remix, reuse, revise, and redistribute the eTextbook. Please refer to the Faculty Support Page, specifically looking at Remixing. You can download Introduction to Data Science using Python Apple Pages File in order to use the original document to revise and remix the eTextbook for your purposes.

Citations

MLA: Agah, Afrand. Introduction to Data Science Using Python. First, The Pennsylvania Alliance for Design of Open Textbooks (PA-ADOPT), 2024.

APA: Agah, A. (2024). Introduction to Data Science Using Python. (First). The Pennsylvania Alliance for Design of Open Textbooks (PA-ADOPT).

Chicago: Agah, A. Introduction to Data Science Using Python. First. The Pennsylvania Alliance for Design of Open Textbooks (PA-ADOPT), 2024. 

Peer Review

This eTextbook went through an Open Peer Review process. The peer review process used the Open SUNY Textbook Peer Review Guidelines, allowing peer reviewers to read the text carefully and evaluate the following:

  • Educational Significance of Content including accuracy, appropriate and useful materials, valid and significant concepts, models, and skills, and key  elements; 
  • Effectiveness as a Teaching Resource including a clear explanation of the  concepts, alignment of materials to the learning process of the target audience, and alignment of the learning objectives with course goals; and 
  • Readability and Ease of Use including clarity and comprehensiveness, consistent writing style, readability and ease of use (logic, sequence, and flow), appropriateness for target readership level, and quality of Interactivity and  multimedia learning objects.

As a part of the open peer review process, the public review conducted by Dr. Mehran Asadi is made available: Peer Review Document (PDF).