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Data Science Careers, Training, and Hiring: A Comprehensive Guide to the Data Ecosystem: How to Build a Successful Data Science Career, Program, or Un

. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs;

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Robinson:Build A Career in Data S_p

expectations make data science a challenging field for the unprepared to break into and navigate. Alongside their technical skills, the successful data;

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Practical Data Science with Hadoop and Spark

essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data;

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Data Science Strategy For Dummies

big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability;

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Java

Java developers who are comfortable developing applications in Java, and now want to enter the world of data science or wish to build;

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Julia for Data Science

is aimed at data analysts and aspiring data scientists who have a basic knowledge of Julia or are completely new to it. The book also appeals to;

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Managing Data Science

will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage;

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Productive and Efficient Data Science with Python

how to measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a;

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Practical Data Science with Python

, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science. The book starts with an;

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Data Science

Learn how to build a data science team within your organization rather than hiring from the outside. Teach your team to ask the right;

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Data Science Programming All-in-One For Dummies

clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the;

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Data Science for Mathematicians

opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field;

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Productive and Efficient Data Science with Python

efficiency with the help of advanced libraries and packages that already exist in the Python ecosystem. The book focuses on topics such as how to;

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Getting Data Science Done

Getting Data Science Done outlines the essential stages in running successful data science projects-providing comprehensive guidelines to;

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Practical Statistics for Data Scientists

can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to;

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Mastering Java for Data Science

Learning to Deep Learning and Big Data frameworks. * Easy-to-follow illustrations and the running example of building a search engine. Who This;

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Introducing Data Science

. Introducing Data Science teaches readers how to accomplish the fundamental tasks that occupy data scientists. They'll use the Python language and;

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Practical Data Science

in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable;

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Building an Information Security Awareness Program

Awareness Program is the first book that shows you how to build a successful security awareness training program from the ground up.

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Data Science For Dummies 3e

science field or already a decade in, you're sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to;

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Data Science Solutions on Azure

different Azure services work together using real life scenarios and how-to-build solutions in a single comprehensive cloud ecosystem. What You'll;

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Jumpstart Your Career in Data Centers (Color Edition)

: a detailed explanation of what the industry is, the jobs within it, and how the entire ecosystem ties together. This first-of-its-kind, peer;

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Smarter Data Science Succeeding with

Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast;

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Hands-On Data Science with R

the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity. What you;

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Spark for Data Science

to understand how algorithms are implemented in Spark, or a newbie with minimal development experience who wants to learn about Big Data;

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The The Data Science Workshop

Cut through the noise and get real results with a step-by-step approach to data science Key Features Ideal for the data science beginner;

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Scala for Data Science

data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and;

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