Five Books that Aspiring Data Scientists Should Read

Five Books that Aspiring Data Scientists Should Read

Five Books that Aspiring Data Scientists Should Read:Data science is not just about mathematics, statistics, and coding. It is about telling a great story.

Data science is not just about mathematics, statistics, and coding. It is about using these tools to generate new insights, and about_ telling a great story_. When data analysis and great storytelling come together, they can help us understand how the world works, challenge our (mis)conceptions of reality, and inspire us to do better. Here is a quick overview of five accessible books that do precisely that.

Factfulness: Ten Reasons We’re Wrong About the World — and Why Things Are Better Than You Think (2018)

By Hans Rosling, Anna Rosling Rönnlund, and Ola Rosling | 352 pages.

Known for a series of influential Ted Talks, Hans Rosling (1948–2017) and his co-authors are on a mission to challenge our misconceptions about the state of the world. The authors begin their book with the startling observation that our ideas about progress in the world are wrong across the board, whether it be poverty, education, or global health. We consistently over-estimate the levels of misery in the world, and under-estimate the progress that we’ve made over the past decades.

Our lives would become unmanageable if we were to approach every problem rationally and base every single decision on data

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