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You will find here an unusual perspective and opinions about data science. These articles may resonate well with senior data scientists and decision makers who manage the data science budget in their companies, but not so well with junior data scientists (assuming it is possible to be both junior and data scientist.) Professionals in fields such as operations research, physics, engineering, FinTech, econometrics, biostatistics might find this content refreshing, even if they don't call themselves data scientists. Eventually, most of us, at some time, graduate to become a real data scientist, even if we started as a pure tech geek.

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- Why do people with no experience want to become data scientists?
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- Statistical Significance and p-Values Take Another Blow
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- 5 Myths About PhD Data Scientists
- 22 Differences Between Junior and Senior Data Scientists
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- Data Science and Machine Learning Without Mathematics
- Advanced Machine Learning with Basic Excel
- The Death of the Statistical Tests of Hypotheses
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- IBM acquires MyInvenio to build its automation portfolio
- Structured vs. unstructured data: The key differences

Posted 12 April 2021

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