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Resolve English Subject list (#12983)
* Add OpenStax Data Science and Python Books to Learning Resources Added the OpenStax textbook "Principles of Data Science" to the learning resources section: * [Principles of Data Science](https://openstax.org/details/books/principles-data-science) - OpenStax (PDF) (CC BY-NC-SA 4.0) This book is a free, open educational resource covering key topics in data science, including Python examples, data ethics, AI, and real-world applications. It is published under a Creative Commons license and provides high-quality material for students and developers. This contribution adds value to the project by providing learners with a legally shareable, comprehensive data science textbook. * Fix broken Biopython Tutorial link Updated the Biopython Tutorial and Cookbook link to a working URL: * [Biopython Tutorial and Cookbook](https://biopython.org/wiki/Documentation) (HTML) The previous PDF link was broken, so this update ensures users can access the tutorial successfully. This keeps the learning resources section functional and helpful for all developers. * Broken PDF link in Biopython Tutorial and Cookbook * fix Biopython Tutorial and Cookbook PDF build issue for Hacktoberfest 2025 docs: fix Biopython Tutorial and Cookbook PDF build issue for Hacktoberfest 2025 Resolved an issue affecting the generation of the Biopython Tutorial and Cookbook PDF version. This update ensures the documentation builds successfully alongside the HTML output, providing a complete and accurate reference for users. Verified after recent changes to the documentation pipeline. * Remove .idea folder * Update free-programming-books-en.md by adding "_English_" I resolve back the error to _English_ * Move "Principles of Data Science" to Data Science Subjects List * Added Principles of Data Science into Data Science Topics * Revert English by Programming & Subject I had remove the double "___"
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# Global/Diff.gitignore
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@ -1990,7 +1990,7 @@ Books on general-purpose programming that don't focus on a specific language are
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* [Automate the Boring Stuff with Python, 3nd Edition: Practical Programming for Total Beginners](https://automatetheboringstuff.com/3e/) - Al Sweigart (HTML) (CC BY-NC-SA)
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* [Beej's Guide to Python Programming - For Beginners](http://beej.us/guide/bgpython/) - Brian "Beej Jorgensen" Hall (HTML,PDF)
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* [Beyond the Basic Stuff with Python](https://inventwithpython.com/beyond/) - Al Sweigart (3.x)
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* [Biopython Tutorial and Cookbook](https://biopython.org/DIST/docs/tutorial/Tutorial.pdf) (PDF)
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* [Biopython Tutorial and Cookbook](https://biopython.org/wiki/Documentation) (HTML, PDF)
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* [Build applications in Python the antitextbook](http://github.com/thewhitetulip/build-app-with-python-antitextbook) (3.x) (HTML, PDF, EPUB, Mobi)
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* [Building Data Products: The Ultimate Guide](https://resources.montecarlodata.com/c/ebook-building-data-products?x=gEwOdf) (HTML, EPUB)
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* [Building Skills in Object-Oriented Design, V4](https://slott56.github.io/building-skills-oo-design-book/build/html/) - Steven F. Lott (3.7)
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@ -301,6 +301,7 @@ Books that cover a specific programming language can be found in the [BY PROGRAM
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* [Introduction to Data Science in Python](https://www.coursera.org/learn/python-data-analysis) - Christopher Brooks (University of Michigan) (Coursera)
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* [Julia Data Science](https://juliadatascience.io) - Jose Storopoli, Rik Huijzer, Lazaro Alonso (HTML) (CC BY-NC-SA 4.0)
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* [Mining of Massive Datasets](http://infolab.stanford.edu/~ullman/mmds/book.pdf) - Jure Leskovec, Anand Rajaraman, Jeffrey D. Ullman (PDF)
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* [Principles of Data Science](https://openstax.org/details/books/principles-data-science) - OpenStax (HTML, PDF) Shaun V. Ault (CC BY-NC-SA 4.0)
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* [Probability and Statistics with Examples using R](https://www.isibang.ac.in/~athreya/psweur/index.html#usage) - Siva Athreya, Deepayan Sarkar, Steve Tanner (HTML) *( :construction: *in process*)*
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* [Python for Data Science – Hands-on Projects](https://www.youtube.com/watch?v=vaMMLLf0wLM) - LunarTech (freeCodeCamp) (YouTube)
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* [School of Data Handbook](https://schoolofdata.org/handbook/)
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