Hello everyone, I am a fairly new programmer here, and have almost completed the python for everybody course.
I am fascinated by the machine learning course, but i have heard that it is quite tough for a beginner and should not be the one of the first courses one does.

However I think I may have a chance at giving this a go, but because I am unsure I thought about asking the community for advice.
Let me explain:
Despite being new to programming though, I do hold a masters degree in mathematics, and having spent 4 or so years studying areal and complex analysis, number theory, linear algebra, Riemannian & differential geometry, hilbert spaces and functional analysis, I think I can confidently say that i know a thing or two about tensors and tensor calculus!
At least from what i have seen FFC does not go nearly into as much detail on tensors as I studied in my degree.

But whilst i know the tensor flow part of machine learning, I do not know if I am ready to learn the rest of the course, as I am new to programming after all.
What do you guys think, should i give it a go, or is a strong mathematical background not enough just yet?

I’d give it a try and see how far you get. You can always look up bits of Python as you go along or decide that you need to go back and cover some Python fundamentals.

A lot of new programmers struggle with abstraction and converting logic into a symbolic form, but you should be able to transfer some of your pure mathematics skills into programming to help you learn faster.

You won’t know until you try. But I think the bigger question is whether you will end up using machine learning in your profession or would you want machine learning to be more of a hobby.

Your pure mathematics background will server you well in learning some nitty-gritty details of machine learning. However, that is only necessary if you want to learn why something works and why some models are better than others. This is true for non-deep learning methods because they rely more on statistical and algorithmic models. Also, some are based on complex and elegant mathematics, like support vector machines that think about high dimensional hyperplanes. But I digress.

Nonetheless, your math background will be helpful in the deeper levels of thinking of why a model works and to understand its strengths and weaknesses. So try it out, there are plenty of courses and YouTube videos out there to try and see if you like it. And if programming is difficult, then you may want to try more graphical interfaces for it as well now that machine learning will soon/is democratized to less technical people. Good luck!