I did a Masters in Data Science and worthiness depends on a lot of factors. - The experience is what you make of it, how challenging a course-load you choose,

I did a Masters in Data Science and worthiness depends on a lot of factors. - The experience is what you make of it, how challenging a course-load you choose, etc. It is often possible to coast thru these programs by taking the easiest classes, if you just want the degree. It is also possible to really go off the deep end and learn a ton, if you want to put in major hours. - Office hours with professors made it worth-while. I utilized almost every one and grilled the profs hard with questions. I imagine you can get this for free if you work at Google/Meta/etc but I didnt have access to that type of intellectual sounding board, so the MS made a lot of sense. - Degree diversification makes sense. I had an east coast ivy league undergrad, so I wanted to balance that out with a west coast technical institution with a very different alumni base, so I chose my MS program accordingly. - The network matters. Find a Uni with a great network. - Ecosystem matters. Find a Uni with a great ecosystem of startups, accelerators, VCs, and FAANG workers who are adjunct. That limits you to Bay Area and possibly NY/Boston in the US, but I think people underestimate how valuable this is. I compared my undergrad (rural Ivy league) to grad (Bay Area) and the difference was night and day. There is just very limited ecosystem possible when the University is stuck in the mountains. - Job placement can be good or bad. Uni recruiters have their "target student profiles" whom they work with to place them at top companies. If you arent on their "target student profiles" list, they wont help you. I spoke to great students in 2021 graduating at the absolute peak of the tech hiring craze, who had been sent away by the university recruiters noting "there are no jobs now." - To learn deep ML you need to start a hard-startup and dive deep into it w/o a dayjob. I did. I did an ML/CV startup diagnostics firm focused on medical imaging. I learned more in 3yrs than I did in 10yrs in industry. I did this in parallel with the MS in DS and that would a wonderful combination because the campus had numerous benefits for students with startups. I could also run hard problems I encountered by my professors and TAs. The MS gave me theoretical knowledge and the startup forced me to truly learn things because otherwise I couldnt ship. - A small number of students (15%) were outstanding and I keep in touch with them, they made the experience worth it. - A large number of students (30% ?) were not paying anything for the degree, often it was being paid for by the US Government as part of US Gov benefits programs. I'm sure it was worth it for them. In some cases they didnt value it as much those paying out of pocket. I saw some completely free-riding and doing no work and leaving most of the effort to team members. - Ambitious projects get seen. I had many, many employers reach out and try to hire me after seeing my masters projects. But you have to learn to manage, market, document and be very vigilant with whom you work with. One free-riding student can seriously tank a major project, and you end up suffering. A cohort of equally ambitious students is unstoppable and a pleasure to work with. If you want, you are welcome to email me and I'm happy to speak to you on the phone.