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Data Science For Dummies, 2nd Edition 2nd Edition

by Lillian Pierson (Author), Jake Porway (Foreword)

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Data Science For Dummies (For Dummies (Computer/Tech))
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Discover how data science can help you gain in-depth insight into your business - the easy way!

Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect:

Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value
Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL
Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things
Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate

It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

ISBN-10

9781119327639
ISBN-13

978-1119327639
Edition

2nd
Publisher

For Dummies
Publication date

March 6, 2017
Language

English
Dimensions

7.3 x 1 x 9 inches
Print length

384 pages
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Editorial Reviews

From the Inside Flap

Learn how data science is applied to generate value
Use data visualization to communicate insights
Covers big data frameworks and applications

A guide book for your journey towards an exciting new data science career

Think you'd like to pursue a career in data science? Let this book be your guide. Data Science For Dummies is for working professionals and students interested in transforming an organization's sea of structured, semi-structured, and unstructured data into actionable business insights. It gets you up-to-speed on what's happening across this broad industry, giving you a head start in turning messy data into meaningful stories that all people in an organization can use.

Inside…

Data science basics
Big data and its infrastructure
Learn Python^®, R, SQL and GIS
Data visualization
Real-time analytics and the Internet of Things
Using MapReduce, Hadoop^® and other big data tools
Real-world applications

From the Back Cover

Learn how data science is applied to generate value
Use data visualization to communicate insights
Covers big data frameworks and applications

A guide book for your journey towards an exciting new data science career

Think you'd like to pursue a career in data science? Let this book be your guide. Data Science For Dummies is for working professionals and students interested in transforming an organization's sea of structured, semi-structured, and unstructured data into actionable business insights. It gets you up-to-speed on what's happening across this broad industry, giving you a head start in turning messy data into meaningful stories that all people in an organization can use.

Inside…

Data science basics
Big data and its infrastructure
Learn Python^®, R, SQL and GIS
Data visualization
Real-time analytics and the Internet of Things
Using MapReduce, Hadoop^® and other big data tools
Real-world applications

Product details

ASIN ‏ : ‎ 1119327636
Publisher ‏ : ‎ For Dummies; 2nd edition (March 6, 2017)
Language ‏ : ‎ English
Paperback ‏ : ‎ 384 pages
ISBN-10 ‏ : ‎ 9781119327639
ISBN-13 ‏ : ‎ 978-1119327639
Item Weight ‏ : ‎ 1.13 pounds
Dimensions ‏ : ‎ 7.3 x 1 x 9 inches

Best Sellers Rank: #1,025,852 in Books (See Top 100 in Books)
- #628 in Data Processing
- #2,804 in Computer Science (Books)
- #35,613 in Unknown

Customer Reviews:
224

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About the author

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Lillian Pierson

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Lillian Pierson is a CEO & data leader that supports data professionals to evolve into world-class leaders & entrepreneurs. To date, she’s helped educate over 1.3 million data professionals on AI and data science.

Lillian has authored 6 data books with Wiley & Sons Publishers as well as 8 data courses with LinkedIn Learning. She’s supported a wide variety of organizations across the globe, from the United Nations and National Geographic, to Ericsson and Saudi Aramco, and everything in between.

She is a licensed Professional Engineer, in good standing. She’s been a technical consultant since 2007 and a data business mentor since 2018. She occasionally volunteers her expertise in global summits and forums on data privacy and ethics.

Title: CEO

Email: lillian@data-mania.com

Website Link: www.data-mania.com

Business HQ Location: Houston, Texas - USA

LinkedIn Profile: https://www.linkedin.com/in/lillianpierson/

Customer reviews

4.4 out of 5

224 global ratings

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Kindle Customer

Broadly inclusive, practical examples and good introduction for topics

Reviewed in the United States on August 19, 2017

Verified Purchase

Broad scope and current. This is the book for anyone looking to see the range of available tools (from machine learning to d3.js) for data science. She is better than most authors at the intro stage of every topic -- for example, why do I care about reducing dimensionality? How to predict groupings within a dataset? One reviewer said that this book does not get much into implementation of the concepts. That is true, but then how could you in less than 400 pages? Entire books are written on just one topic, such as time series prediction models. The key for beginners and intermediate data science practitioners is to fully understand options before spending weeks or months going down a rabbit hole (wrong model). I can say this with some regret because I wasted a lot of my own time in a steel demand prediction project a few years back. Had I been better acquainted with options, I probably would have completed it in half the time. Unless you are already a guru, this book is well worth the money.

18 people found this helpful

Helpful

Stephen Seth Keesee

Great for beginners!

Reviewed in the United States on January 5, 2018

Verified Purchase

If you’re curious what data science is and isn’t, this book is perfect. It gives information in a little bit of everything. It also has a LOT of great references to come back to if you need data sets or specific program needs. This book is more of an overview which I’d highly recommend if you’re just beginning your data science journey. It isn’t a walkthrough of the in depth programming. It’s more of a intro to data science class which is still very involved.

3 people found this helpful

Helpful

Naksh

Gives nice introduction to data science!

Reviewed in the United States on March 17, 2020

Verified Purchase

This book is a geat start for anyone who is curious to know about data, In today's world every aspect of the business and its future relies on the historical data and this is a great book which covers-
1. Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value
2. Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL
3. Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things
4. Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate

Helpful

B. Allen

Not Feeling the Data Love

Reviewed in the United States on January 24, 2019

Verified Purchase

I am a complete novice when it comes to data science. Most of the material left me more or less confused. The worst part of the book was the author's discussion on Python. As someone who is a Python expert she didn't do justice to her chapter on that subject as far as I am concerned. Lots of definitions and then the snippets of coding examples were too confusing. What would have worked better is to give a introduction to Python and then work through simple examples that were fully annotated.

2 people found this helpful

Helpful

Paula

Great overview as expected from the Dummies series

Reviewed in the United States on January 19, 2020

Verified Purchase

Sorts out the high level topics and allows understanding to decide if you want to jump into this field.

Package was open on one end when delivered; contents could have easily fallen out. Looks like the end of the padded envelope was intentionally torn open and someone decided the 'nerd' books were a disappointment . . .

14 people found this helpful

Helpful

Butterfly

Great book for beginners and beyond

Reviewed in the United States on February 1, 2022

Verified Purchase

Nicely made. Easy to follow

Reviewed in the United States on April 5, 2021

Verified Purchase

Good source of basic knoweldge.

Reviewed in the United States on January 7, 2021

Verified Purchase

I like the way the author explains complex concepts in simple words, using relevant examples.

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Diego Rodrigues

Boa leitura sobre o assunto!

Reviewed in Brazil on May 22, 2021

Verified Purchase

Boa leitura sobre o assunto!

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Noe Mosqueda Valadez

El mejor libro para iniciar en Data Science

Reviewed in Mexico on August 26, 2020

Verified Purchase

Considero que es la mejor opcion para iniciar en Data Science, tambien recomiendo seguir a la autora en Linkedin.

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Jennifer

Glossary with not enough overview for a beginner. Too many unexplained topics thrown at you.

Reviewed in Canada on January 28, 2020

Verified Purchase

If this was intended to be written for a beginner to data science, it is the most difficult book I have ever read and I have a technical education. It is a glossary with very brief definitions. Definitely not in depth enough. I couldn't finish it and I will be looking for another book as recommended by another low star reviewer.

2 people found this helpful

msmartinas

Great book for subject overview

Reviewed in the United Kingdom on May 6, 2020

Verified Purchase

Great book, well presented throughout, not unnecessarily flooded with words for the sake of it. Basic concepts of data science explained clearly to give an overview of the subject. Don't buy if you expect hand-holding 'how-to' guide as this is meant to explain the realm of the subject. It's very easy to read and I would definitely buy again!

2 people found this helpful

Cliente Amazon

Buon contenuto

Reviewed in Italy on November 13, 2017

Verified Purchase

Il libro, ricevuto nei tempi, contiene contenuti validi espressi in modo coerente con il target che si pone di coprire. Tutto espresso in modo molto pratico e fruibile

3 people found this helpful

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