How to be a modern… by Jeffrey Leek [Leanpub PDF/iPad/Kindle]
How to be a modern scientist
How to be a modern scientist
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How to be a modern scientist

Last updated on 2016-04-08

About the Book

The face of academia is changing. It is no longer sufficient to just publish or perish. We are now in an era where Twitter, Github, Figshare, and Alt Metrics are regular parts of the scientific workflow. Here I give high level advice about which tools to use, how to use them, and what to look out for. This book is appropriate for scientists at all levels who want to stay on top of the current technological developments affecting modern scientific careers. The book is based in part on the author's popular guides including guides for

The book is probably most suited to graduate students and postdocs in the sciences, but may be of interest to others who want to adapt their scientific process to use modern tools. 

About the author: Jeff Leek is an Associate Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. He is a co-founder and co-director of the Johns Hopkins Data Science Specialization on Coursera that has enrolled over 3 million aspiring data scientists. His research has helped contributed to our understanding of the genomic basis of brain development, blunt force trauma, and cancer. He is blogs at Simply Statistics and can be found on twitter at @jtleek and @simplystats

About the Author

Jeffrey Leek
Jeffrey Leek

Jeff Leek is Associate Professor of Biostatistics and Oncology at Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. He writes for the blog Simply Statistics and can be found on Twitter @jtleek@simplystats.

Causes Supported

Data Carpentry

http://www.datacarpentry.org

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Our goal is to provide researchers high-quality, domain-specific training covering the full lifecycle of data-driven research.

From astronomy to molecular biology and digital text, our increasing capacity to collect data is changing research. It allows us to ask questions that previously could not have been answered, and it changes the impact that research has on society. Although petabytes of data are now available, most disciplines are struggling to translate this sea of data into knowledge. The missing step between data collection and research progress is a lack of training for scientists in crucial skills for effectively managing and analyzing large amounts of data. Data Carpentry addresses this gap by teaching researchers the fundamental data skills they need to conduct their research. Our goal is to provide researchers high-quality, domain-specific training covering the full lifecycle of data-driven research. We teach hands-on workshops in data organization, management, and analysis to increase data literacy and improve research efficiency and reproducibility.

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