Getting Up To Speed For Data Science: Maths

As I mentioned in previous posts, I’ve just finished my second contact week with the Uni for my apprenticeship and I am re-motivated to learn.

The maths is the thing that has me the most stumped, so I’m going to take charge and stop hoping that the material I’m struggling with will suddenly make sense.

Luckily, I have a really good idea of what I need to learn now!

Firstly, I did not do any calculus in school, and it turns out that stuff is really useful in real life. Who could have guessed?

After remembering how awesome Coursera is, I ran a couple of searches and found this:

Seems like a pretty good place to start! So far the videos have mainly begun with probability, which plays a bigger part in data science than I thought. It’s a good thing I studied some statistics and probability last year, although not on the level I need for this!

The main thing I have noticed so far with my apprenticeship is just how prevalent calculus is. Although I’m sure the Data Science Math Skills course will include that, I want to be sure so I found a calculus course as well.

Right now I think that’s enough to get on with. I’m trying to decide if I should follow a Linear Algebra course as well, but I think these two should bring me up to speed on most of the things I’ve seen. Besides that, my degree has a module explicitly for linear algebra, so maybe I can just follow that? We’ll see later I suppose!

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