Should I learn Math or DSA before ML?

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I'm a BCA first-year undergraduate student [4 year degree] planning to pursue Masters in Machine Learning and choose ML as my carrier. I have basic knowledge of Python but I lack some basics in mathematics, should I focus on ML theories and start doing projects or learn the required math or else should I master DSA before all these. Is it possible to learn DSA and ML at the same time.

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You can do both. If you are keen on understanding the concepts, there are many self-learning courses available online (both for math/linear algebra concepts etc., and data science/analytics).

Check out:

https://ocw.mit.edu/

https://see.stanford.edu/

https://www.edx.org/

https://www.mooc.org/#course-categories

I would say, earmark some time each day for self-paced learning and in a couple of months you would have the required conceptual knowledge.

If your BCA program allows you to pick electives, you may also choose these subjects if they are offered by your school.

So in tldr learn math and dsa then ML and yes I do have options to pick electives as ml related topics.

Im sure its possible to learn both, depends on how much time you have and how badly you want to learn them.

Do you think all these topics can be covered in the next 3 years.

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