Yeah, on reflection, I think that’s the crux of it. There were some users from a more tight knit subreddit that I got to know well, but we all moved to discord a few years back. I miss some of the more active niche subreddits, but otherwise Lemmy replaced it very easily.
It’s entirely possible that my timing was just bad for Mastodon and good for Lemmy. The fact that I could jump on Boost and have an extremely familiar experience was a big plus. Bluesky was more similar in terms of migration experience to Lemmy than Mastodon was.
The other issue is that in a forum site you follow topics, where on a microblog site you follow people. The topics are here on Lemmy (to some extent), even if the people aren’t, but I don’t really care about the individual contributors as much. The people I wanted to follow for microblogging went to Bluesky, and that matters a lot more there.
That was actually part of my issue, and I experienced the same problem on Bluesky at first. The difference for me was ease of discovery and the influx of people I followed on other platforms. If they had gone to Mastodon instead, I’d have been more inclined to give it more effort. As it stands, I’m content with Bluesky and don’t feel I’m missing much on Mastodon. Perhaps I’m mistaken, and that’s my loss. Just trying to add some perspective.
It’s important to note that my experience is from a year ago, and I imagine a lot has changed. Part of my issue at the time was that I couldn’t see things like who people I followed were following because they were on a different server, which made discovery challenging. Also very few people who I followed on the bird site went to Mastodon.
I’m not saying the platform can’t work or that the barriers make it unusable, just that the draw wasn’t there to warrant the investment in learning a more complex platform than the alternatives.
Anecdotally, I joined Mastodon, found it difficult to find people who I personally know that were on different instances, kind of lost interest and thought kbin might be a better solution for both forums and microblogs all in one place, then my Mastodon instance shut down, and then kbin died too. Hence me being on lemmy.world, as default and stable of a server as there is here.
Bluesky felt fun and familiar right off the bat, my only issue was that it was still so small when I joined. Now that there’s an influx of new users, many of whom I followed on the bird site, it just feels like Twitter 2, which I suspect is what most people want.
FWIW I have a highly technical job and consider myself pretty tech literate, so I don’t think any of the issues I had with Mastodon weren’t things I could’ve figured out or worked around, I just didn’t feel incentivized to bother. I suspect they’ve smoothed out a lot of the federating issues I saw before, but at this point I’m happy enough on Bluesky to stay put.
A BS in Physics was my primary degree (I double majored so I also had a BA in a language that has never been of any professional use to me).
Python is so ubiquitous that it’s a great tool to know for a multitude of applications, and it pairs well with a physics background since that increases your usefulness as a generalist.
It is important to make the distinction between a programmer with a hard science/math degree and one with a computer science degree. The former will likely struggle more with building up larger libraries, following best practices for modularity/extendability/backwards compatibility, and other computer science sort of stuff that the latter will ingrain much better. The flip side is that computer science tends to not have as much of an emphasis on a math background, so analysis and Data Science applications often benefit more from the science/math background than the comp sci one (please note that I’m making highly generalized statements here based on what I’ve observed).
To summarize, if you want to build an app to do something, you want comp sci, but if you want to build a statistical model and have the ability to rigorously validate it and explain what it’s doing, you’re going to need that math background.
I did what you’re describing and it worked out well for me, but YMMV. Here’s what I did:
I got an undergrad degree in physics, and was hired right out of school by a government contractor. My only hard skill from the degree was coding in LabVIEW, something I never have done in the workplace. Arguably my only real use in my first job was to be a person who submitted a timesheet that could be billed as a person with a STEM degree.
I changed jobs for a much better contractor where I did a lot of “system engineering” style analysis with MatLab, which I mostly learned on the job, and eventually moved into Python which I learned entirely on the job. Python really resonated with me, particularly using it for Data Science applications. I got a Masters degree in Applied Physics from a highly renowned school taking after hours courses that my job paid for. Most of the courses had no conceivable application to my day job.
I eventually was hired away from the contracting world and am a Data Engineer for a private company.
The thing a physics degree truly demonstrates is the ability to learn difficult concepts, think analytically, and have the math to back it up. If you go this route, you’ll kind of be a generalist right out of the gate and need to be open to trying a bunch of new things to figure out what works for you. A master’s degree certainly helps, and learning a useful programming language really helps. Be prepared to start somewhere as an analyst, and build from there.
Excellent, thanks!