Developing Analytic Talent: Becoming a Data Scientist

Details Author Reviews Description The book discusses the following topics: what is data science and why it is different (from computer science, statistics) and here to stay, why is big data different and require new techniques (and its not hype although the word is abused by fake data scientists), how to extract value from data, how to become a data scientist (independently or through a University program The book discusses the following topics: what is data science and why it is different (from computer science, statistics) and here to stay, why is big data different and require new techniques (and its not hype although the word is abused by fake data scientists), how to extract value from data, how to become a data scientist (independently or through a University program or certification) and the skills needed. Important topics: Analytical recipes and data science tricks and rules of thumb - including the curse of big data, causation vs. correlationData science job interview questions, horizontal vs. vertical data scientistCase studies - Wall Street, Botnet detection, online advertisingWhat companies are looking forSample resumes, salary surveys, sample job adsSource code, data sets, dictionary, software / companies and other resources The book discusses the following topics: what is data science and why it is different (from computer science, statistics) and here to stay, why is big data different and require new techniques (and its not hype although the word is abused by fake data scientists), how to extract value from data, how to become a data scientist (independently or through a University program The book discusses the following topics: what is data science and why it is different (from computer science, statistics) and here to stay, why is big data different and require new techniques (and its not hype although... Read More

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