What are the pros and cons of studying machine learning before deep learning? I'm a biotech student and I'm currently working on single-particle tracking. For my work, I need to use aspects of deep learning (CNN, RNN and object segmentation) but I'm not familiar with these topics. I have some prior knowledge in python.

So, do I have to learn machine learning first before going into deep learning, or can I skip ML?

What are the pros and cons of studying machine learning before deep learning?
That question doesn't really make sense: deep learning is a sub-topic of machine learning, so you can't really 'skip' it. It's a bit like "I want to learn about trigonometry, but do I need to do geometry first?"

Having said that, in order to make sense of deep learning you should really know about the general principles of machine learning, otherwise you won't understand it. Or, more importantly, you won't understand what problems deep learning can be applied to, and what issues are better solved with other methods.

You don't need to go into much detail, but should at least get an overview.