cjrd

Hello All, I'm a 3rd year (domestic) computational physics major with a strong interest in machine learning (stemming from my physics research). I would like to transition from "physics" to computer science for my graduate studies. Currently, I've taken the following CS courses: Intro to Comp Sci Data Structures Discrete Math Algorithms Network Programming Several good ML schools (UTA UWash etc) encourage students from non CS disciplines to apply but highly recommend certain courses as background (computer organization, operating systems, and other 'standard' cs courses). My research in ML is purely through a few years of research with different physics applications (particle physics/ astrophysics), and my formal background in this area has been through self-digested textbooks and video tutorials. So here's the bind: This upcoming semester will be the last semester of CS coursework that is guaranteed to be on my transcript for CS grad apps. I'm currently enrolled for the following courses: Optimization Techniques Mathematical Statistics Advanced Electricity and Magnetism (Physics course, irrelevant here) Computer Organization There's no explicit ML courses offered this upcoming semester however there is a course in web mining that is offered at the same time as comp org. Would I be better off taking the course in web mining and pushing off comp org and os to my senior year? Web mining would give me another course in the field I want to pursue in grad school but comp org might fill some basic requirements (of course I could explain that I'm taking these courses in my personal letter, or something...) Any advice would be much appreciated. PS) IF it matters, assume my research background is strong, my GPA is perfect, and I will have some good recs. PPS) Perhaps if I left out some of the standard coursework (focusing more on ML-related topics) but scored > 90% on the GRECS?