Noted about the importance of experimental design and lack of for probability. On the topic of experimental design, the two courses my uni offers are 'Introduction to Experimental Design' and 'Experimental Design Theory and Methods', the former isn't required to take the latter, fortunately. Probability courses are important AFAIK for work in finance, which I'm trying to keep doors open for as I like the field (I think).>what is your goal after you graduate
I've just entered my upper-div studies, so I'm really trying to figure that out. I have all the lower-div requirements for either a math or cs degree currently, was gonna double major but at my school it adds an extra year, but I can cherry pick the best classes and call it minor and graduate when I want. I feel I'm unfortunately trying to optimize for 'not closing any doors' and by doing so I'm not really specializing enough to be employable anywhere, but essentially I've gone through phases of wanting to do (roughly in chronological order over the last year) post-grad pure math, working as a dev straight out of uni and going to grad school for cs/finance.
So, unsurprisingly, my planned classes are a barebones combo of pure math (2-3 classes each of analysis, algebra and topology), applied (cs courses like OS/Algos/DBs/Languages, along with some optimization and numerical analysis) and the stats/probability we've been discussing. There's only so much I can fit, so I'm trying to trim the fat wherever I can. I would say at this point I've almost totally ruled out wanting to go to grad school for pure math, but I still feel compelled to take the classes mentioned (can shelf those desires though).>Statistical Computing and Data Visualization in R
I agree about your summary here>ML
Unfortunately, it seems the ML course does not require any stats as a prereq, which is really unfortunate. I will def look into the stats learning course more