A collection of (mostly) technical things every data scientist should know - `s/programmer/data-scientist/g` of every-programmer-should-know by @mtdvio
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README.md

every-data-scientist-should-know 🤔

A collection of (mostly) technical things every data scientist should know 📈 📉

☝️ These are resources I can recommend to every data scientist regardless of their skill level or tech stack

This is a s/programmer/data-scientist/g of every-programmer-should-know by @mtdvio. That meas two things: 1. I take no credit for the idea of creating this page, I just wanted one for data-science and 2. things that are purely related to software development will not be the focus of this page, though there may be limited duplication.

What do YOU think every data scientist should know?

What do YOU think every data scientist should know

This list is far from complete/correct. Add/remove as you wish...

(see Contributions)

As in the original, all of the following applies:

Highly opinionated 💣. Not backed by science.
Comes in no particular order ♻️

U like it? ⭐️ it and share with a friendly data scientis! U don't like it? Watch the doggo 🐶

P.S. You don't need to know all of that by heart to be a data scientist.
But knowing the stuff will help you become better! 💪

P.P.S. Contributions are welcome!*

📜 - paper
📖 - book
📄 - blog
- checklist
📂 - github/lab repo
🔗 - website (other)
🎥 - video

Ethics

Base Math for Data Science

Statistics

Open Source / Open Data

Machine Learning

Artificial Intelligence / Neural Networks / Deep Learning

Visualisation

"Data Constructs" - Data Structures & Relational Databases

"Big Data" Processing/Managment Technologies & Operalization

Programming Languages/Software Developement

Career

Meta-Lists

Blogs/Tweeps you should follow

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.