I read that to be a data scientist you need to know statistics, linear algebra, and calculus. I think you teach statistics and linear algebra.
I found some websites with math training but one of them is recommending that before linear algebra and calculus I need to review algebra I, geometry, algebra 2, trigonometry, and pre-calculus.
Do you think I should review all of that? I want to make sure I become a good data scientist and I don’t want to be short math skills. It seems like the greater your math skills the more you can do with the data so it seems the most important. However it will take me a lot of extra time to study all that math and I’m not sure if most of it would be used a data scientist.
Hi Jesse!
Thanks for reaching out.
It is great to hear you are so motivated to become a data scientist. I’d say this is the most important ingredient, apart from hard work, towards turning data science into your profession.
Then, data science is practically a combination between mathematical, statistical, business, and programming skills. But that’s the most general definition we can provide, probably. In fact, they are intertwined and there’s no data scientist that is extremely strong in all fields altogether.
Our program prepares you for all – statistics, mathematics, programming, business intuition, and their interaction. By the end of the program, you will have a much better idea about the general picture, since you will have practised on all. Moreover, you will have done a lot of exercises on the hardest of concepts related to each of these fields.
Finally, we do update our content regularly. So, by the time you complete all lectures and exercises, there will be new content prepared for you.
Hope this helps.
Best,
Martin