Introduction to Data Science, with Introduction to R (Jeffrey Stanton)

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Introduction to Data Science, with Introduction to R (Jeffrey Stanton)

The key ideas and procedures of data science are gently introduced to non-technical audiences in this book. The book offers code explanations and explanations for a variety of intriguing applications that use the free and open-source R language for statistical computing and graphics for more technical readers.

It also discusses the numerous talents needed, the crucial processes in the Data Science process, the software technology necessary for efficient Data Science practise, and the top university programmes that are emerging for training in the area.

The competencies required of data scientists are demonstrated in this book via a series of data challenges of escalating complexity. In order to demonstrate both the difficulties of data science and some of the approaches taken to overcome those difficulties, actual data examples are utilised in conjunction with the open source data analysis programme "R" and its graphical user interface companion "R-Studio." The talks are, to the best degree possible, based on real datasets that reflect significant contemporary topics.

Ebook Details

About the Authors
The School of Information Studies at Syracuse University currently employs Jeffrey S. Saltz as an Associate Professor. His work focuses on helping businesses use data and information technologies to gain a competitive edge. The socio-technical elements of data science projects, such as how to coordinate and manage data science teams, are the focus of Jeff's current study. Jeff consults with customers ranging from Fortune 500 companies to professional football teams in order to stay in touch with the "real world."
Published Date / Year
(October 6, 2017); eBook (Creative Commons, Syracuse University, 2013)
288 pages
eBook Format
PDF, ePub, Kindle, etc.

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