ParanoidAndroid

In terms of reputation, I think NC State has a bit of an upper hand (US News and NRC). Location also seems to work in its favor being a part of the research triangle.

Basic linear algebra will definitely help. Review linear transformations, matrices, determinants and analytic geometry.

From what I've gathered on this forum and around the web, Columbia's program is really big. This means you're likely facing hundreds (~300) of others as competition for those finance jobs in New York. The MA program doesn't seem to be on par with the reputation of the department.

And FYI, Apostol also has books called Calculus, Vol. I and II. I think of his Mathematical Analysis book as a sequel to these texts.

They're about the same level. Apostol goes through more topics. Baby Rudin is very terse for an Analysis text. It becomes especially challenging at the topology section (Chapter 2). Apostol is more complete, but his exercises aren't as "soul-searching" as Rudin's. My suggestion is to start with Rudin and use Apostol to fill in the gaps.

Have you taken a Real Analysis course before? Otherwise, going straight into baby Rudin might be overwhelming. I imagine Real Analysis will be better for PhD applications. If you decide to go that route, make sure to supplement Rudin's book with Apostol's Mathematical Analysis.

You forgot the veggie/meat. Anchovies?

Asian fusion. Kimchi fries are amazing:

http://www.youtube.com/watch?v=eRBwvIX7Sao Can't believe Spike Lee bothered to remake this masterpiece.

Technically no. 25 years and a bit is strictly larger than 25. ....

+1 for the math puns.

It seems like you're only approaching this matter in terms of academic interests. How do you know there is no common ground? Did you discuss anything other than research? Approach this individual as a person, not mathematician. The reason for the downvote was this part: A little judgmental, don't you think?

Pokemon Yellow

Working full time and taking an intensive course will be difficult. At least if you study on your own, you can work at your own pace. Honestly, the OCW video lectures are top notch and chances are you're not going to get better instruction anywhere else. Plus, they supplement the lectures with readings, notes and assignments. Above all, they're free! As an alternative, have you looked at Coursera? They offer free week long courses in many subjects. This one is being offered by WashU starting May 19th: https://www.coursera.org/course/mathematicalmethods Mathematical Methods for Quantitative Finance The Mathematical Methods for Quantitative Finance course reviews the mathematical methods fundamental for the study of quantitative and computational finance. The areas of focus include calculus and multivariable calculus, constrained and unconstrained optimization, and linear algebra. Topics covered include the following: Functions and inverse functions Limits, derivatives, partial derivatives, and chain rule Integrals and multiple integrals, changing the order of differentiation and integration Taylor series approximations Newton’s method Lagrange multiplier method Vector and matrix arithmetic, determinants, eigenvalue-eigenvector decomposition, singular value decomposition Numerical methods for optimization This is pretty much the standard material you learn in a MVC course, minus the big theorems (Green, Stokes, Gauss).

Are you required to register in a summer course by your graduate program? Or do you just need to be familiar with the material? If the latter, I would suggest using online references for vector calculus (there are a ton of great ones, like MIT Courseware). It certainly beats paying to take a course.