Thoughts on Bayes with the Practicum?
I originally was planning on taking one class at a time through to the end, and was going to take DMSL (7406) to end the program with the practicum, however I've heard there's a ton of overlap with CDA. Bayesian statistics intrigues me, but I've heard bad things about the class being hard/pointless/outdated, and that it should be taken alone.
I've rearranged my schedule as we are now expecting an addition to the family in April/May timeframe, and I'm probably going to need next summer off, and I've moved 6203 to be taken with 6242 so I have the pre-req for the practicum taken care of.
For anyone who has taken Bayes in the past couple of years, have they changed anything? Chatting with Google AI it seems like it uses WinBUGS which is apparently outdated, but then some reviews mention using PyMC which apparently is far more widely used in industry. Is it both? I'm interested in it's use in AI/ML and finance applications, and even if the class half teaches it, it carves out time for me to do my own self learning, with a credential on my resume.
Should I stick with my original plan and just do DMSL+Prac in Fall 27 to finish out the program, or is Bayes+Prac going to be doable with a 3-4 month old newborn at home while also working full time? I guess I could always take Bayes after graduating, but I think the chances of that actually happening are going to be very slim to none.
For reference, I've had all As up until this point, and have an engineering undergrad, so math isn't too hard for me, but the only graduate level/calculus-based statistics exposure I've ever had was Sim this Spring. Also, I opted out of 8803 so one of the MGT electives fills that requirement.
Posted Aug 12, 2026, 2:08 PM UTC