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Calculus recommendations?

Hi everyone! I was doing MIT’s Calculus 1A (Differentiation) course on EdX and I really loved it (it’s one of the best mooc courses I ever taken!) and I wanted to continue my Calculus studies with their courses. It makes me very sad, but after starting their Integral course, I had to realise that I can’t do both Dataquest and MIT’s Calculus at once.

So my question is, how much Calculus knowledge is required for Data science?
I saw that there is Calculus included in the Data Science path here. Do you think it’s enough for a start? If not, do you have any recommended (not as detailed and theory heavy as MIT’s courses) resources?

Thank you!

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I would say yes, that should be enough for a while. I am assuming the curriculum was designed to make sure of that. Try to get some exposure to multivariate calculus if possible.

If you feel getting stuck with any concepts down the line, then worry less about not knowing the fundamentals (or falling behind etc) in those moments and think more about covering those gaps from that point forward. Try to keep your own notes so that you can fill in details or add to them as you encounter anything more complicated.

Depending on what direction you take in DS, slowly more and more math fundamentals might start to become more important and relevant. But, I would say, till then spend time on projects using what you already learned before trying to go too deep. Focus on developing intuition as much as possible through those projects.

In the future, if you want to continue then MIT’s or Khan Academy’s videos should be good enough as per me. For more intuitive overviews 3Blue1Brown could be helpful - Essence of calculus - YouTube

Of course, everything I say should be taken with a grain of salt since I don’t work as a Data Scientist currently.

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Thank you for your reply and your recommendations!

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