You won't understand AI unless you know something about its history - including the part played by rule-based systems. Why, for example, did symbolic models become popular in the late 50s?
For a brief run-through, see Chapter 8 of The Guide to Expert Systems, by Alex Goodall (Learned Information, 1985; RSL Comp BD 36; PSY KH:G 061). This was written in 1985, near the height of the expert systems hype. Indeed, the book was a result of this. A new expert systems journal had just started up, intended for a commercial audience. The book was to be given away (or sold cheaply) to new subscribers with no knowledge of AI, as a way of easing them into the subject.
For a more recent perspective, see AI: the tumultuous history of the search for artificial intelligence by Daniel Crevier (Basic Books 1993; PSY KH:C 068). I've just got this into the library, and will be recommending it as an introduction to AI in future years. Chapters 6 and 8 deal particularly with expert systems and their part in the commercialisation of AI. In a few years, it will be time to do the same for neural nets.
Some points in early AI history:
You can fill in the rest yourself. If you're not interested, you shouldn't be doing the course anyway! Be aware that different people have different interpretations of history, and that I've only mentioned a very small part of even the early work above.