Hopefully the OP will be able to answer your question, but I thought I might offer my 2 cents:
I'm currently working on an MSc in IT. My actual project does not involve NLP directly, but all the 'related research' does (ie. all previous systems which achieve the same goal as mine)so I had to read up on it. This was a struggle... YMMV. I find a few good resources along the way though - recommend reading this first
http://www.staff.ncl.ac.uk/hermann.moisl/ell236/manual1.htm
then on iTunesU/YouTube you'll find a good course on computational linguistics from MIT, watch the first half dozen lectures at least (don't worry if you don't fully understand them all). A lot of the theory can be traced back to Chomsky's work on grammars, so I suggest reading some of his papers (his style is quite clear). I found I needed to do all this just so I could properly follow the recent papers on NLP (specifically NL interfaces to DBs) that I must review. I really had to start from the beginning, light wikipedia'ing wasn't cutting it. I'm currently reading The Oxford Handbook of Computational Linguistics to consolidate my knowledge, it's pretty good.
So anyway... tough subject, try not to get bogged down. If all the reading's too dry, then 'Godel Escher Bach' is a fun alternative that touches on similar theory.
If I were to choose a pure NLP project myself, I'd maybe do something like 'How NLP can add value to existing systems/software.' ie. look for imaginative practical applications, rather than theorizing yet another parser with some new trick/quirk