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Data Science For Dummies

       The power of big data and data science are revolutionizing the world. From
the modern business enterprise to the lifestyle choices of today’s digital
citizen, data science insights are driving changes and improvements in every
arena. Although data science may be a new topic to many, it’s a skill that any
individual who wants to stay relevant in her career field and industry needs to
know.

         This book is a reference manual to guide you through the vast and expansive
areas encompassed by big data and data science. If you’re looking to learn a
little about a lot of what’s happening across the entire space, this book is for
you. If you’re an organizational manager who seeks to understand how data
science and big data implementations could improve your business, this book
is for you. If you’re a technical analyst, or even a developer, who wants a
reference book for a quick catch-up on how machine learning and
programming methods work in the data science space, this book is for you.

          But, if you are looking for hands-on training in deep and very specific areas
that are involved in actually implementing data science and big data
initiatives, this is not the book for you. Look elsewhere because this book
focuses on providing a brief and broad primer on all the areas encompassed
by data science and big data. To keep the book at the For Dummies level, I do
not go too deeply or specifically into any one area. Plenty of online courses
are available to support people who want to spend the time and energy
exploring these narrow crevices. I suggest that people follow up this book by
taking courses in areas that are of specific interest to them.

        Although other books dealing with data science tend to focus heavily on
using Microsoft Excel to learn basic data science techniques, Data Science
For Dummies goes deeper by introducing the R statistical programming
language, Python, D3.js, SQL, Excel, and a whole plethora of open-source
applications that you can use to get started in practicing data science. Some
books on data science are needlessly wordy, with their authors going in
circles trying to get to the point. Not so here. Unlike books authored by
stuffy-toned, academic types, I’ve written this book in friendly, approachable
language — because data science is a friendly and approachable subject!

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