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Titlebook: Data Science Careers, Training, and Hiring; A Comprehensive Guid Renata Rawlings-Goss Book 2019 The Author(s), under exclusive license to S

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發(fā)表于 2025-3-21 16:28:04 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Data Science Careers, Training, and Hiring
副標(biāo)題A Comprehensive Guid
編輯Renata Rawlings-Goss
視頻videohttp://file.papertrans.cn/264/263062/263062.mp4
概述Broad introduction to what is needed to be successful as a new entrant to the field of data science either as an individual, institution, or business.Offering a 360-degree view of the data science lan
叢書名稱SpringerBriefs in Computer Science
圖書封面Titlebook: Data Science Careers, Training, and Hiring; A Comprehensive Guid Renata Rawlings-Goss Book 2019 The Author(s), under exclusive license to S
描述.This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce.?..Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data.??..The book is divided into three sections, the first “Building Data Careers”,?is from the perspective of a potential career seeker interested in a career in data, the second
出版日期Book 2019
關(guān)鍵詞Self-Learning; careers; bootcamps; video learning; data science
版次1
doihttps://doi.org/10.1007/978-3-030-22407-3
isbn_softcover978-3-030-22409-7
isbn_ebook978-3-030-22407-3Series ISSN 2191-5768 Series E-ISSN 2191-5776
issn_series 2191-5768
copyrightThe Author(s), under exclusive license to Springer Nature Switzerland AG 2019
The information of publication is updating

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Liudmila A. Vasilenko,Olga I. MolchanovaTo lay the foundation for success in forming a data career, degree program or business team we must return to a point from the introduction. Data is not where the true power is; it is in people. Not just the people who code but the people who use data to make decisions and those whose lives data effects.
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Conclusion,To lay the foundation for success in forming a data career, degree program or business team we must return to a point from the introduction. Data is not where the true power is; it is in people. Not just the people who code but the people who use data to make decisions and those whose lives data effects.
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SpringerBriefs in Computer Sciencehttp://image.papertrans.cn/d/image/263062.jpg
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Tim Schoof,Simon Groth,Michael Bonitzrson needs food, shelter, clean water, health care, security, and education [1]. This need for transformation in global society shows that the relevance of Data Science is not only its unparalleled ubiquity and enormous scope, but its potential to improve lives and decision-making across a wide vari
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Chris Woolley,Joel P. Castellanosr, is as much a practice as it is a discipline, raising the questions of whether and how Data Science should be treated in academia. Should it be its own major, department, or division at a university? And what are the foundational elements that comprise a degree in Data Science? Here, we discuss th
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