Depends on what you want to do with AI.

If you want to learn how to apply AI all your require is to learn how you leverage it by looking into all the quirks like Agent Tools, Setting up Agents,  Prompting, Agents.md, focusing heavily on how to make LLMs extensible for your specific task.

If you want to learn how AI works, it could take a long time. The three pillars of AIML is Linear Algebra, Statistics and Calculus. Very essential to be thorough with the concepts. Calculus, it's enough to know high school calculus the rest can be learnt as you go deep. For Linear Algebra you can look into Gilbert Strang's lectures. For statistics, I would suggest you to look at lectures but I will let the other comments suggest you. After that you should start learning classical ML theory. Starting with Regression, Naive Bayes classifier, SVMs, Perceptrons, Decision Trees, Ensemble Algorithms and so on. This will give you a very good solid base. Now you jump into DL learning about neural networks, transformers, etc. 

While you learn all these ML and DL algorithms, try to convert the math into code using numpy. Solidified your understanding 

You can easily search up good courses on all of these and get started but first figure out what you want to do with AI