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# Preface {.unnumbered}

This notebook covers many aspects of data science: soft skills, technical skills, backend to frontend. The notebook is in an outline format, so some of the information may seem a bit fragmented. The bullets are bits of information that I've pulled from various articles, papers, books, etc.

Most of the code is written in R, but there is a substantial portion in Python. There are also sections devoted to SQL and Javascript.

Initially, I had no intent of publicly releasing these notes, so I haven't attributed all the authors of the content inside this notebook. If you see your work and want credit, please let me know.

This is a live document that's frequently updated.

Also, if you see any mistakes or have any questions, please open an issue at the github [repository](https://github.com/ercbk/Data-Science-Notebook).

Cover designed using Google Imagen 3