>>12301172>building mathematical modelsWhat systems are you modeling?
I'll speak only from modeling natural systems, as that is where most of what my experience is with. Developing mathematical models assumes a concrete understanding of ODEs and PDEs, either one (or both) depending on the nature of the systems you intend to model. If your systems only evolve in relation to time spend most of your time on ODEs. If space or some other variable crops up a lot some time should be spent on PDEs. Dynamical systems is another subject to become well-acquainted with, as this has applications in chemistry to engineering to physics to biology etc. Beyond these subjects some knowledge in statistics and probability theory is necessary, as your models may not always be deterministic but stochastic, and a knowledge of these subjects will help when randomness plays a part in the evolution of your system (which it almost always does). An acquaintance with these subjects will help you build your models, but actually analyzing them is a different story. You'll probably pick up some familiarity along the way studying the aforementioned fields, but just in case some additional familiarity is useful: optimization/control theory (e.g. "what is the optimal trajectory for this system?"), as one anon mentioned, multivariable calc, linear algebra (although this is a prereq for the prereqs imo), a decent amount of programming skills, networks/graph theory (depends on the models), bifurcation theory, sensitivity analysis, blah blah blah
Hope this gives you a general idea
