How to be a modern scientist (Ediție în Limba Română)
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How to be a modern scientist (Ediție în Limba Română)

Despre carte

Fața academiei se schimbă. Nu mai este suficient doar să publici sau să dispari. Suntem acum într-o eră în care Twitter, Github, Figshare și Alt Metrics fac parte regulată din fluxul de lucru științific. Aici ofer sfaturi de nivel înalt despre ce unelte să folosești, cum să le folosești și la ce să fii atent. Această carte este potrivită pentru oamenii de știință la toate nivelurile care vor să rămână la curent cu dezvoltările tehnologice actuale care afectează carierele științifice moderne. Cartea se bazează în parte pe ghidurile populare ale autorului, inclusiv ghiduri pentru

Cartea este probabil cel mai potrivită pentru studenții la doctorat și post-doctoranzi în științe, dar poate fi de interes și pentru alții care doresc să-și adapteze procesul științific pentru a utiliza unelte moderne.

Despre autor: Jeff Leek este Profesor Asociat de Biostatistică la Johns Hopkins Bloomberg School of Public Health. Este cofondator și codirector al Specializării în Știința Datelor Johns Hopkins pe Coursera, care a înscris peste 3 milioane de aspiranți la știința datelor. Cercetările sale au contribuit la înțelegerea noastră despre baza genomică a dezvoltării creierului, trauma prin forță bluntă și cancer. Blogurile lui se găsesc la Simply Statistics și poate fi găsit pe twitter la @jtleek și @simplystats

This book is a translation into Română of How to be a modern scientist which was originally written in Engleză.

Despre autori

Jeffrey Leek
Jeffrey Leek

Jeff is Chief Data Officer, Vice President, and J Orin Edson Foundation Chair of Biostatistics at the Fred Hutchinson Cancer Center. Previously, he was a professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health and co-director of the Johns Hopkins Data Science Lab. His group develops statistical methods, software, data resources, and data analyses that help people make sense of massive-scale genomic and biomedical data. As the co-director of the Johns Hopkins Data Science Lab he helped to develop massive online open programs that have enrolled more than 8 million individuals and partnered with community-based non-profits to use data science education for economic and public health development. He is a Fellow of the American Statistical Association and a recipient of the Mortimer Spiegelman Award and Committee of Presidents of Statistical Societies Presidential Award.

TranslateAI
TranslateAI

TranslateAI: GPT-4 Powered AI Translations!

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Can I See An Example of TranslateAI Translations?

To see the output of TranslateAI right now, you can check out these two books: How To Be a Modern Scientist and The Elements of Data Analytic Style by bestselling Leanpub author Jeffrey Leek.

Both of these books have been translated into 31 languages using our innovative TranslateAI service for non-fiction authors! Scroll down on the books' landing pages to see the translations. (Both these books and all their translations have a free minimum price, so feel free to buy it for free in both the English language version and in one or more translations if you want to see what TranslateAI can do.)

(The languages that these books have been translated into are the 31 languages in the GlobalAuthor Max bundle. The GlobalAuthor bundle comes in 3, 8 and 31 language versions.)

We’ve been working hard on our TranslateAI service for a long time now, and it’s an amazing opportunity to get self-published books in the hands of new audiences all around the world. Learn more here.

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Leanpub exists to serve our authors. We want to help you reach as many readers as possible, and we want to help you make as much money as possible. We also want to help you save time, so you can spend more time writing and less time doing other things.

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For our authors who write in English: just because many people in the world can read English as a second language to some extent doesn't mean they should have to read your book that way. Furthermore, billions of people cannot read English, even as a second language. If you want to reach these people, you need to translate your book into their language. First and foremost, this is a question of accessibility: if your readers cannot read your book, it does not matter how good it is.

For our authors who write in a language other than English: TranslateAI is even more valuable for you, especially if you're writing a computer programming book or business book. English is the largest market for these books, and you're really missing out by not having an English version of your book!

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  5. Your translation is put into read-only mode.
  6. Leanpub will use the OpenAI API to use GPT-4 to translate your book.
  7. Leanpub will automatically validate the output, including ensuring that code samples are handled appropriately.
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Cuprins

    • Introducere
    • Scrierea lucrărilor
      • Scrierea - ce ar trebui să fac și de ce?
      • Scrierea - ce unelte ar trebui să folosesc?
      • Scrierea - sfaturi suplimentare și probleme
    • Publicare
      • Publicare - ce ar trebui să fac și de ce?
      • Publicare - ce instrumente ar trebui să folosesc?
      • Publicarea - sfaturi suplimentare și probleme
    • Recenzare între colegi
      • Recenzare între colegi - ce ar trebui să fac și de ce?
      • Evaluare între colegi - ce unelte ar trebui să folosesc?
      • Evaluare inter pares - sfaturi și probleme suplimentare
    • Partajarea datelor
      • Partajarea datelor - ce ar trebui să fac și de ce?
      • Partajarea datelor - ce instrumente ar trebui să utilizez?
      • Partajarea datelor - sfaturi și probleme suplimentare
    • Blogare științifică
      • Blogarea - ce ar trebui să fac și de ce?
      • Blogging - ce unelte ar trebui să folosesc?
      • Blogging - sfaturi și probleme suplimentare
    • Cod științific
      • Cod științific - ce ar trebui să fac și de ce?
      • Cod științific - ce unelte ar trebui să folosesc?
      • Cod științific - sfaturi suplimentare și probleme
    • Social media în știință
      • Social media - ce ar trebui să fac și de ce?
      • Social media - ce unelte ar trebui să folosesc?
      • Rețele de socializare - sfaturi suplimentare și probleme
    • Predarea în știință
      • Predarea - ce ar trebui să fac și de ce?
      • Predarea - ce instrumente ar trebui să folosesc?
      • Predarea - sfaturi și probleme suplimentare
    • Cărți
      • Cărți - ce ar trebui să fac și de ce?
      • Cărți - ce unelte ar trebui să folosesc?
      • Cărți - sfaturi suplimentare și probleme
    • Comunicare științifică internă
      • Comunicarea internă - ce ar trebui să fac și de ce?
      • Comunicare internă - ce unelte ar trebui să folosesc?
      • Comunicare internă - sfaturi și probleme suplimentare
    • Prezentări științifice
      • Prezentări științifice - ce ar trebui să fac și de ce?
      • Prezentări științifice - ce unelte ar trebui să folosesc?
      • Prezentări științifice - sfaturi suplimentare și probleme
    • Citirea lucrărilor științifice
      • Citirea lucrărilor științifice - ce ar trebui să fac și de ce?
      • Citirea articolelor științifice - ce instrumente ar trebui să folosesc?
      • Citirea articolelor științifice - sfaturi și trucuri suplimentare
    • Credit
      • Credit - ce ar trebui să fac și de ce?
      • Credit - ce unelte ar trebui să folosesc?
      • Credit - sfaturi suplimentare și probleme
    • Planificarea carierei
      • Planificarea carierei - ce ar trebui să fac și de ce?
      • Planificarea carierei - ce instrumente ar trebui să folosesc?
    • Identitatea ta online
      • Identitatea ta online - ce ar trebui să fac și de ce?
      • Identitatea ta online - ce instrumente ar trebui să folosești?
      • Identitatea dumneavoastră online - sfaturi și trucuri suplimentare
    • Despre autor
      • Ar trebui să îmi urmezi exemplul?

Cauze susținute

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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