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First Steps to Learning Data Science or ML after the Roadmap
Pre-requisites and pre-work before diving deep into data science and ML
At the start of this year, I published a mind map on the Data Science learning roadmap (shown below). The roadmap was widely accepted, that article got translated into different languages, and a large number of folks thanked me for publishing it.
Everything was good until a few aspirants pointed out that there are too many resources and many of them are expensive. Python programming was the only branch that had a number of really good courses but it ends right there for beginners.
A few important questions on foundational data science struck me:
- What should one do after learning how to code? Are there topics that help you strengthen your foundations for data science?
- I hate math and there are either very basic tutorials or too deep for me. Can you recommend a compact yet comprehensive course on Math and Statistics?
- How much Math is enough to start learning how ML algorithms work?
- What are some essential statistics topics to get started with data analysis or data science?