Data Scientist: The Definitive Guide to Becoming a Data Scientist

by Zacharias Voulgaris

Each chapter is filled with practical information that will help you reap the fruits of big data and become a successful Data Scientist: - Learn what big data is and how it differs from traditional data through its main characteristics: volume, variety, velocity, and veracity.

- Explore the different types of Data Scientists and the skillset each one has.

- Dig into what the role of the Data Scientist requires in terms of the relevant mindset, technical skills, experience, and how the Data Scientist connects with other people.

- Be a Data Scientist for a day, examining the problems you may encounter and how you tackle them, what programs you use, and how you expand your knowledge and know-how.

- See how you can become a Data Scientist, based on where you are starting from: a programming, machine learning, or data-related background.

Genres: Nonfiction, Academia

278 pages, Paperback

First published June 1, 2014

Reviews

[Peter A. · Rating 5 out of 5]

Very good book, particularly for newcomers like myself. I enjoyed the easy-to-follow style, the large number of examples, and the well structured format. It would be nice if there were a newer version of it containing all the latest developments in data science.

[Giorgio R. · Rating 5 out of 5]

Great book. Very practical and entertaining. Would recommend to others interested in the subject.

[Samuel R. · Rating 5 out of 5]

Excellent book! Easy-to-follow style, rather entertaining at times, and lots of relatable examples.

[Thomaz Philippe · Rating 4 out of 5]

This is a very good book. The author really deliver enough content to help you start your data science journey. This book is divided in three main parts. In the first one the author focus on the explanation of what is this new field in the data related industry called "Data science", explaining what is the mindset required by the professionals who performs this activity. Second, the author focus on what skill-set, techniques, frameworks, theory, statistics and machine learning knowledge that is mandatory a professional to have before he can call himself a data scientist. In the last part, the author presents a series of advices to help the readers to be accepted in a data science job position. I would recommend this book to any person who have a real intention to evolve in the big data, machine learning and eventually data science career. The book would help you to learn your weaknesses and create a plan to acquire the necessary knowledge to pursuit your goals.

[Lesley Looper · Rating 4 out of 5]

I learned about the job title "data scientist" from my niece a couple of years ago, and I've been curious since then about the growing field of data science, and how it might apply to libraries, as well as other (more obvious) job markets. I learned a good bit from this book, and wish I'd honed my math skills earlier! Still, it's given me a lot to think about, and I've looked into courses and certificates at the local community college.