| AI is a very broad field. Much of the academic "classical" AI requires some advanced math to understand in depth. A fun place to start is video game AI because it is visual. For example, path-finding algorithms, the ghost AI in pacman, chess/checkers, bots which play video games. Another fun visual subfield is computer vision. If you have a webcam, you could get OpenCV and play around with recognizing faces and motion detection. If you are really into math, I always think that attempting an automated theorem prover would be fun. It is an up and coming science (in fact there was a HN post today about it), and I bet there are a lot of ad hoc approaches you could take if you choose a specific area of math. If you want something very practical, nowadays search/recommendations/etc. are important on the web. There are some high-rated books on Collective Intelligence that are more practical-minded than the academic AI classics. And mining the web for a dataset could be a fun project. As for the best language, it depends on which subfield you want to pursue. Scheme/Lisp are probably the most strongly associated with AI. However, in practice they are rarely used. I would say it does not matter, as long as you are motivated :) |
You have some recommendations in math books?