- #1
nnguyen
- 8
- 0
I am planning to take my first grad course next semester in statistics (analysis of variance) and am debating if I should take grad combinatorial optimization as well. I handled 4 upper div. courses this semester pretty well (ODE, real analysis, probability theory, advanced linear algebra) but am not sure if I can handle a similar course load with grad. courses.
Since the average grad student takes only 2-4 courses a semester, would I be overdoing it if I take both courses along with 2 upper div. undergrad courses (specifically, real analysis II and stochastic processes)? What can I expect in terms of difficulty and workload from graduate courses?
Since the average grad student takes only 2-4 courses a semester, would I be overdoing it if I take both courses along with 2 upper div. undergrad courses (specifically, real analysis II and stochastic processes)? What can I expect in terms of difficulty and workload from graduate courses?