I've been thinking about AI a lot lately, but I skipped college and went straight into startups, so all my knowledge on the subject is from reading less focused materials. Reminds me of Stanford's iOS dev resources from 4-5 years ago.
[EDIT] oh god math, why can I program but I can't math unless it's trigonometry or vectors/calculus, visually applied math makes sense, otherwise I'm so lost.
For me, it really helped to be able to think of mathematical ideas in terms of code–as abstractions I could define and use in programs. I got this view by learning and using Haskell, and I do think Haskell is better-suited for this than other languages, but it's applicable to anything: think about how you would phrase the relevant math in your code, using whatever abstraction facilities you're comfortable with.
I actually took this class a few years back. There is certainly some math, but it's all math that's transferable to code in a reasonably natural way. (In fact, that's roughly what the small projects/homework assignments entail!) Doing the assignments while paying attention to the abstractions you use in your code is going to be a great way to get over the math hurdle.
Believe it or not, they still release a course every year (or semester, not sure). The latest one covers iOS 9 using Swift. You can find them all on iTunes U.
Then go through the bulleted list in order. During this process, you will also encounter things you don't know. Add these to the top of the list and start from the top anew. As you work through bulleted items, mark them off or move them to a "complete" list.
What you are creating is a list of things you need to understand in the order you need to understand them. It guides your investigation and makes it all more manageable.
Bonus: Beneath the list, create an in-order set of notes pertaining to the items on your list. This is like a personalized set of lecture notes.
Correct me if I'm wrong but I actually think the reason LISP was created was for AI.