This piece of advice is short but sweet. Don’t expect to understand everything. Don’t beat yourself up for it, it’s normal. Some things are too complex and simply unnecessary to know. For example, machine code – what’s the use of knowing how to write hexadecimal instructions or binary if you don’t need to? Same goes for some mathematical proofs, understanding the idea is usually enough, be pragmatic about what you need to know and avoid following rabbit holes into pools of unnecessary knowledge. This can be difficult to begin with as you’re less experienced at classifying what’s useful and what is not. A general rule of thumb is that if there isn’t a huge amount of information available online, it’s usually not worth knowing to begin with.
As your data science career develops you will begin to specialise and acquire more of this rare knowledge where necessary. Don’t try and learn it all at the start. Sounds simple, but you might come across people who like to know things others don’t, leading them to almost brag about something niche and impractical for the sake of sounding intelligent. Avoid this trap at all costs, people will listen if you have something that can actually add value to them.