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Python Data Science
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Python Data Science

2023 ed.

Book Details

Format Hardback or Cased Book
ISBN-10 9811977011
ISBN-13 9789811977015
Edition 2023 ed.
Publisher Springer Verlag, Singapore
Imprint Springer Verlag, Singapore
Country of Manufacture GB
Country of Publication GB
Publication Date Jul 1st, 2023
Print length 345 Pages
Weight 1,106 grams
Dimensions 21.50 x 28.80 x 2.80 cms
Product Classification: Databases
Ksh 11,700.00
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Rather than presenting Python as Java or C, this textbook focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts.

Unlike conventional textbooks, it is based on Markdown and uses full-color printing and a code-centric approach to highlight the 3C principles in data science: creative design of data solutions, curiosity about the data lifecycle, and critical thinking regarding data insights. Q&A-based knowledge maps, tips and suggestions, notes, as well as warnings and cautions are employed to explain the key points, difficulties, and common mistakes in Python programming for data science. In addition, it includes suggestions for further reading. 

This textbook provides an open-source community via GitHub, and the course materials are licensed for free use under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).

Rather than presenting Python as Java or C, this textbook focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts. Unlike conventional textbooks, it is based on Markdown and uses full-color printing and a code-centric approach to highlight the 3C principles in data science: creative design of data solutions, curiosity about the data lifecycle, and critical thinking regarding data insights. Q&A-based knowledge maps, tips and suggestions, notes, as well as warnings and cautions are employed to explain the key points, difficulties, and common mistakes in Python programming for data science. In addition, it includes suggestions for further reading. This textbook provides an open-source community via GitHub, and the course materials are licensed for free use under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). More teaching materials including Codes, Datasets, Slides, Syllabus can be found at https://github.com/LemenChao/PythonDataScience

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