So I am thinking of learning data science and (gradually) ML. Do I need to know advanced mathematics for this (like Trigonometry and Calculus)?

You need statistics, and trends and data and simulations need mathematical tools lile derivatives, integrals… which I think may be included in calculus but I am not sure

anyway, that is a field where you can’t do without maths

I respectfully suggest you learn a little bit about matrix algebra. It sounds a little daunting, but once you get the hang of it, you’ll be ahead of the game. There are quite a few tutorials. For example, https://stattrek.com/matrix-algebra/matrix.aspx

If I had my ‘fix the world’ magic wand and I aimed it at math education, I’d totally make matrix algebra/linear algebra taught much earlier for people who want to do technical stuff.

Is matrix algebra the same as Linear Algebra (I completed the Linear Algebra YouTube playlist by 3Blue1Brown)?

Do I need to know Integral calculus p, or differential calculus can be enough?

I don’t know enough of statistics techniques to answer

Matrix algebra is what most people mean when they say linear algebra. Linear algebra is actually much bigger than most intro courses teach.

Statistics theory uses a lot of integral calculus, but you can always wait to learn integration if you need it.

Yes, matrix algebra and linear algebra are the same thing, near as makes no difference.

Well, for the average programmer they are basically the same. But for code that relies on advanced mathematics, matrix algebra is a very small portion of linear algebra.

Edit: Sorry if that comes across as pedantic. My job is writing code that does linear algebra without matrices, so the difference between matrix algebra and linear algebra is a big deal for me.

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