{"product_id":"python-data-science-hardcover","title":"Python Data Science - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eChaolemen Borjigin\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eRather 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.\u003c\/p\u003e \u003cp\u003eUnlike 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\u0026amp;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. \u003c\/p\u003e \u003cp\u003eThis 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).\u003c\/p\u003e\u003cp\u003eMore teaching materials including Codes, Datasets, Slides, Syllabus can be found at https: \/\/github.com\/LemenChao\/PythonDataScience\u003cbr\u003e\u003c\/p\u003e\u003ch3\u003eBack Jacket\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eRather than presenting Python as Java or C, this book focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts.\u003c\/p\u003e\u003cp\u003eUnlike 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\u0026amp;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. \u003c\/p\u003e\u003cp\u003eThis 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).\u003c\/p\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eChaolemen Borjigin is an associate professor at Renmin University of China, and one of the top 50 data science influencers in China. He is a member of the Information System Special Committee of the Chinese Computer Federation, deputy director of the Expert Committee of the National University Artificial Intelligence and Big Data Innovation Alliance of China, executive editorial board member of the academic journal \u003ci\u003eComputer Science\u003c\/i\u003e, and deputy editor-in-chief of the international journal \u003ci\u003eData Science and Informatics\u003c\/i\u003e.\u003c\/p\u003e \u003cp\u003eHe is the author of \u003ci\u003eData Science\u003c\/i\u003e (Tsinghua University Press, 2016), the first monograph in China that systematically introduced data science principles, theories, methods, technologies, and tools. His textbook \u003ci\u003eData Science Theory and Practice \u003c\/i\u003e(Second Edition) was recognized as a high-quality textbook by the Beijing Municipal Education Commission in 2019. His course Introduction to Data Science is one of the China National First-Class Undergraduate Courses.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 345\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.02 x 11.1 x 8.27 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 01, 2023\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47213272498425,"sku":"9789811977015","price":145.78,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/R73kY_nayW9789811977015.webp?v=1768104457","url":"https:\/\/bookscloud.io\/products\/python-data-science-hardcover","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}