The first 10 or so chapters are written so well that you can literally just read them as a self-study undertaking. Each chapter has an introduction and conclusion that reads like a novel, and the rest of each chapter is delivered in manageable chunks. The second half of the book is more text-booky, but by chapter 10 you will have a much better idea of the field and will have picked up on areas you want to dive into more specifically.
Chapters 1-10 cover state spaces, how deductive logic applies to machines, differences between environments from a machine perspective, and more (shoutout to the AI game chapter, it’s a fascinating introduction to how machines play games).
I’d estimate that the first 10-12 chapters would take you less than 50 hours total. From there you would have the basics you need to jump into neural networks concepts, robotic decision making, or something else practical. All of AI is built on foundations from 1950-1990 (and earlier), and the first 10-12 chapters will give you that foundation.
Neural nets are a dead end IMO