UTexas seems to be crushing it in the ML/AI space as they offer far more recent courses with deeper topics; for everything else OMSCS is probably a better choice even though it has a relentless pace of busywork making even easy classes draining. Stanford OTOH is like GT and UT merged together (both crazy difficult projects and a lot of math), but at 2x the pace. UT is way more relaxing than either, one can take 3 courses alongside a job and be fine, which is next to impossible at GT and Stanford. Conversely, if one wants to continue by doing research, Stanford and GT are much more useful due to ample opportunities to do so.

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sanufar 6 hours ago | parent [-]

Could you elaborate more on continuing with research?

	▲	storus 6 hours ago \| parent [-]
		GT used to have a collaboration with Meta's FAIR and one could do final projects in the DL and NLP classes on recent research topics from Meta AI; some people ended up at top conferences with their work. Not sure how it's going to be now given Meta effectively disbanding FAIR in favor of Wang's Superintelligence. GT also has team research project under VIP (Vertically Integrated Projects) where a prof leads a team of students towards new findings; there are also a bunch of PhD seminars one can take. Stanford has a plenty of CS3xx research classes one can take where the final project has to be some novel research.