[jph00]

You might find it helpful to see what other people are doing with deep learning - see if any of it seems relevant to your interests. For instance, here's some examples of folks from diverse backgrounds using DL in their domains of interest: https://www.fast.ai/2019/02/21/dl-projects/ . Or here's a rather deep rabbit hole - hundreds of replies from people showing their learning projects: https://forums.fast.ai/t/share-your-work-here/27676 .

I find it useful to think of DL as just another way to get computers to do what you want. Rather than focusing on control flow and setting/reading variables, you focus on providing examples to learn from. Both approaches can do many of the same things, but each has areas that they're better at. Eg DL is better for things that are hard to explain just how you do them (e.g. seeing pictures, hearing sounds, reading text) and traditional coding is better for things that need specific logical steps. A combination of the two is often best for solving end-to-end problems in practice.