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3 points by jdbt97 3796 days ago | link | parent

I'd say it really depends on what 0 really means for you. "0" for me was a physics degree and handful of years in industry doing physics-y things. "0" for somebody else might be a stats background, a programming background, maybe even a humanities background. The advice is going to vary vastly depending on the context - and it's going to vary a lot based on location too.

Here in the Bay Area, the demand for data science people is a lot higher, so there are a wider variety of paths into the field. Try to break in on the East coast, and it might be much harder.



2 points by astanway 3796 days ago | link

I dunno, I feel like New York is a genuine powerhouse for data science. We're saturated with ad-tech and finance, for starters...

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1 point by jdbt97 3793 days ago | link

True, but I feel like NY is harder to break into without already knowing somebody. I could be mistaken, though, since most of my data is anecdotal.

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2 points by rohit 3796 days ago | link

I agree. 0 to me was a Master's degree in Math.

To answer OP's question: I would say Kaggle is a great place to start getting your hands dirty.

Coursera would go very well to give a better understanding of theory with Kaggle's practical learning style.

There was another link to the Open Source Data Science Masters in the front page. You might want to check that.

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2 points by amogh10 3796 days ago | link

Given this criteria seems I am at -2.

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