Application of Machine learning or Neural Networks for automatic Time table scheduling
Scheduling problems might be NP-Complete problems.
It is not clear what are the specific details.
You might get lucky and have specific constraints that are leading to an easy sub problem or just an easy instance.
However, since many variations like On the Complexity of Scheduling University Courses (which might be your case), Job shop scheduling,Multiprocessor scheduling and Open-shop scheduling are NP-complete, you are probably in the same situation.

Usually, it is better to treat such problems like optimization problems and not like classification problems. If you'll try to treat the problem like a classification problem you might have severe problems in building a classified dataset that will represent well the time scheduling problem that you would like to solve.

There are general technique in order to cope with optimization problem. I also found some work related to your case. I'm not familiar with this specific case but it seems that Solving the Course Scheduling Problem Using
Simulated Annealing and the work done here might help you.