I just finished another quarter of graduate school and am not so patiently awaiting grades.  The courses I took include algorithms, operating systems, and reasoning with partial beliefs.   All of them were interesting in their own way.  Algorithms  is  like solving a chess  puzzle.  You wait for the aha moment when the solution pops in your head.  This can be frustrating on a test because you never know how long it will take before this occurs.  If you have seen the problem before it is usually incredibly easy. 

One of the problems on the final was to prove the following problem is NP-Complete.  Is it possible to seat N knights around a table such that no two knights that have a quarrel are side by side.  The solution is to use a hamiltonian circuit and to reduce the finding of a hamiltonian circuit to that of seating the nights around the table.  When feeding the hamiltonian circuit to the knights problem you consider the vertices of the graph as the knights and each pair vertices that are not connected by an edge have a quarrel.  This will show that a hamiltonian circuit reduces to the knights problem.  You still have to show that a solution to the knights problem can be verified in polynomial time which is trivial in this case.

I think everyone knows what an operating system, but it helps to get your hands dirty with the kernel code.  It really seems fairly simple when you get to know the different pieces and Linux is a great platform with the source available to poke around.  In the class we wrote a Virtual File System and a Block device driver in addition to a simple shell.  All very instructive. 

The last class I took was, as I detailed before, about reasoning with partial beliefs and specifically using Bayesian Networks as a formalism to represent causality and to answer queries about a system giving beliefs and evidence.   This has many applications from data mining using a naive bayes model which simplifies notions of independene to genetic modeling of genes.  This area is one of my interestes as I look to specialize in Artificial Intelligence.  There still seems to be lots to be done in these areas as the field is relatively new. 

Now on to next quarter.