Spent the last couple years teaching myself AI/ML and helping others do the same. The biggest time-waster isn't the math — it's these three things:

1. Starting with theory instead of code. You don't need to understand backprop derivations before you train your first model. Write code first, understand the 'why' as questions come up.

2. Tutorial hopping. Jumping between 5 different YouTube courses because each one feels incomplete. Pick ONE structured path and finish it before starting another.

3. No notes system. Beginners consume content passively and forget 90% of it in a week. Write your own condensed notes as you learn — it's the single highest-leverage habit for retention.

I put together a structured notes bundle (AI fundamentals + Python for ML + core ML concepts) for anyone who wants a shortcut past #3. Happy to answer questions if you're stuck on where to start.