i am a bit confused. What do you mean with "school"? If you really want to become an "ML/AI master" this is more complicated then you seem to think.
If you mean university it will take some time (and rightly so) until you can choose your courses. ML is rapidly changing, so you can't just learn "one trick", you need to be able to adapt quickly and learn new techniques (this can be really fundamental compared to other branches like programming). Also most of the concepts are hard and you can't (or it's difficult to) learn them without some theoretical background (for example a bachelor in math/physics/engineering). Of course you can assemble something in TF based on a quick MOOC, but this doesn't make you an "ML/AI master", just somebody who can use a library and who will meet his boundaries quickly.
The usual requirements are Probability/Stats, Calculus, Linear Algebra. To really scratch the surface you need to take about 2 or 3 semester of courses. When i was in school i didn't imagine it to be this challenging. I also didn't imagine it to be so rewarding, but i know that i would be unable to pass them if i were studying alone.
There are always exception to the rule and i only started diving into ML recently, so take this advice with i grain of salt. But just because you taught yourself programming it doesn't mean you can do the same with ML/AI that quickly and also alone. Take it seriously and don't expect to get results too quickly. But each step is really rewarding, so just start to study and see where it takes you.
If you mean university it will take some time (and rightly so) until you can choose your courses. ML is rapidly changing, so you can't just learn "one trick", you need to be able to adapt quickly and learn new techniques (this can be really fundamental compared to other branches like programming). Also most of the concepts are hard and you can't (or it's difficult to) learn them without some theoretical background (for example a bachelor in math/physics/engineering). Of course you can assemble something in TF based on a quick MOOC, but this doesn't make you an "ML/AI master", just somebody who can use a library and who will meet his boundaries quickly.
The usual requirements are Probability/Stats, Calculus, Linear Algebra. To really scratch the surface you need to take about 2 or 3 semester of courses. When i was in school i didn't imagine it to be this challenging. I also didn't imagine it to be so rewarding, but i know that i would be unable to pass them if i were studying alone.
There are always exception to the rule and i only started diving into ML recently, so take this advice with i grain of salt. But just because you taught yourself programming it doesn't mean you can do the same with ML/AI that quickly and also alone. Take it seriously and don't expect to get results too quickly. But each step is really rewarding, so just start to study and see where it takes you.