30-Second Data Science

Thanks to NetGalley, authors, and publishers, for the opportunity to read an advanced copy of "30-Second Data Science".
This book is an excellent introduction to the subject of data and data science, with mesmerizing visual material, related facts to each topic, related brief biographies, highlighted main ideas, and very accessible explanations of topics. Do not expect deep dive into topics, this book does what it says: within a couple of minutes and a couple of pages we get an idea of certain use of data and its characteristics.
This is a great tool for students interested in AI, data science, statistics, just to understand what are the uses and main research fields of data usage. It is perfectly visualized and great learning material and introductory tool.

The book touches and elaborates the main uses of data and characteristics of uses in each of the below fields:
-daily use of data
-business use of data
-social/ethical use of data
-medical data & biostatistics
-predictive analytics
-decision making in uncertainty ( my personal favorite and research topic)
-logistics and business process optimization
-shopping, surveillance, and other uses.

Needless to say, this is a definitely 5-star read for me. The amount of research and accessibility for the researches in all academical fields, language, and logical reasoning and transitions, made this book an exceptional material for both students.
I am going to use this in my classes of the theory of psychological research as a mandatory, introductory read, as well as my small research group.

If possible, please share a copy of this book upon printing, I'd definitely treasure it in my library.

I really love the 30-Second series, because you can cover a lot of information in a short period of time. It's just enough information to grow an interest and decide if you'd like to further pursue a topic. It would even bee a great idea to pick up before starting a course on the topic so you're a little familiar before starting. I'm not super intrigued by data science, but I checked this one out to trial read before adding to my classroom library. Some of my students who are interested in pursing careers like engineering and software development would definitely be interested in reading. It covers a variety of topics such as: ethical use of data, business use of data, and even daily use of data! Definitely a good place to start for some basics on the topic.

I have read other books in the 30-second series, so I am familiar with the format. As a novice to the field of data science, this does give a decent overview of theories from a variety of fields such as computing, mathematics, economics and even philosophy. This multi-disciplinary approach is really engaging and you can come away from the book feeling relatively well informed! And you can take it to the bare minimum or go further. If you are in a scientific/mathematical field, or just looking to enhance your knowledge, this is the book for you.

A comprehensive introduction to the foundational principles of Data Science, this book serves to act as a enjoyable guide to getting your data vocab right. Data Science is driving major technological changes and innovations today. So it has become imperative to have a working knowledge of what it is and exactly what all those terms to often used in association with it mean.( And yes, Statistical association is one of those terms).

A well-organized, accessible reference for curious readers which presents the information in digestible bits. It covers major application areas where Data Science is being used as well as the principles that drive it. The biographies of major figures and quotes related to the topic being presented add a human touch to the experience.

As is mentioned in the introduction, this book aims to bring together humanism and dataism while making the later accessible. A fantastic guide for anybody curious about today's world and how data drives it.

Enjoyable, heavily illustrated guide to an important topic. Easy-to-understand snippets on foundational topics like regression, clustering, and sampling will not make you a data scientist, but will increase your comfort with this field and provide pragmatic, everyday examples.

Many thanks to NetGalley for the ARC in exchange for an honest review.

This book is a great read if you are looking to some concise introductions of the principles and main concepts used in the complex field of data science. With data management and evaluation a driving force between a large range of industries and fields - from AI, sports, dating and medicine, to mention only a few - it is important to realize, through simple everyday life examples - what is the relevance of the data models and patterns. In addition, the readers are also introduced to important historical names that pioneered the use of data science.
I was particularly impressed by the graphic part with inspiring illustrations pertinent to the topics explained.

Gorgeously illustrated, this slim volume is a nice primer for those with little to no exposure to data science. It covers some major basic concepts in a readable way as well as modern and bleeding edge applications of data science. I also liked how it situated data science firmly in the statistical tradition and gave some good introductions to some major historical figures. On the whole, while I didn't learn a lot, I love the art and would recommend this to anyone who wants a quick overview. And I absolutely would love to frame some of the illustrations on my office wall!

This book gives a fun, easy to read breakdown of what data science is, what it is commonly used for currently, and what the future might hold. It does a good job showing the depth at which data science can be used. It also gave some quick bios of some of the most important people in the field. Definitely would recommend for people to get an easy look into what data science actually is.