Unless you are particularly interested in a specialization, I'd recommend using that academic time to just become a better generalist. Yet more data structures and algorithms. Yet more math. Yet more database stuff. Sure, add some ML and neural nets on top, but you don't need to go overboard. Learning core stats is more useful imo.
A lot of the stuff you'd want for general employment isn't taught in school. It's boring stuff that you learn over time with a lot of Googling unless you're already a sysadmin or something. It's kind of absurd how long it takes to get a junior dev set up with an environment for coding on a particular project, they usually don't know how to put things in PATH or use docker and so on. But if you can do math or solve challenging (but yet boring) problems or do full stack web dev, you'll be a reasonably hot commodity.
In my experience, there are good trajectories that are about specializing and carving out a niche to the point that you could start your own enterprise using your contacts and knowledge (make a co-op or something). At the same time, you don't want to be stuck 15 years later not having generalized at all and in an industry where your specialization has been made obsolete. Having a bit of both is a good place to be.
Realistically, we can do little to meaningfully predict where the industry is going to go, because it is currently halfway through a significant collapse of existing business models (the ones built on the principle that free money means you never need to make a profit). What we can do is take a look at what the big players are investing in and try to extrapolate from there. Sadly, the big players are either going in on utterly insane things (Hi Meta), are looking for ever more IoT insanity to build (Hi Amazon and Google), or are splitting their bets between 'replace a lot of programmers with AI-generated software' and 'just do monopoly things' (Hi Microsoft), so good luck with those tea leaves...
The whole field is still going strong. Choose something that interests you. Tons to do in ML, AI, robotics, quantum computing, theory (so much gd theory), bioinformatics, graphics, security, etc, etc, etc.
Oooh, what exactly is bioinformatics? I'm kind of interested in biology and even took some classes in it (but I majored in history), but now I would like to go for a master's. I learned that I would like to do something with "building the future" and bioinformatics sound like a good way to use a field of science that I like in doing so.
We must seize futurism from the clutches of the Muskrats.
I'm not involved with the field personally so I'm not sure but it's basically using programming to solve problems in biology, such as gene identification. If I had to hazard a guess it probably uses a fair amount of data science. Try reaching out to a bioinformatics professor at whatever university you're looking into.
I am Ted's infinite sadness :a-guy: The irreparable harm that the advance of tech under capitalism is doing to human beings as a species is absolutely tragic.
I feel like it's hard to map the trends in industry with the types of things you can get a master's in. Like I work on cloud/kubernetes/devops stuff, and it's definitely going to be big for the next few years at least, but I don't really know how you study that stuff in school (I don't really recommend it either, it sucks). I guess an obvious one is cybersecurity. There are a lot of security masters programs I think, and the field definitely isn't going anywhere.
Data science isn't a dying field, just the term "data science" is less trendy compared to whatever other trends people are using now for "doing statistics on my computer". ML is data science, and new AI is mostly data science as well. An ML masters seems like a good idea because that's one area of computer science where a higher level degree matters more so than just general programming.
If I was getting a masters I would do something in programming language or compiler design. It doesn't have the same level of hype as security or AI, but I think it would be really interesting. Over the last decade, we've seen a bunch of new and innovative languages displace the old C/Java/Ruby status quo. Stuff like Rust and Go is pretty mainstream now, and more experimental ones like Zig, Nim, or ReasonML are getting a lot of attention. Hopefully this trend of language innovation keeps up and there's more work for language designers going forward.
What are you looking for in a masters? Why do that instead of just jumping to some new companies?
I really want to get out of the US
Hey me too. I'm hoping that I can manage it with just a bachelor's, but we'll see.
If you're mainly focused on a career, cybersecurity or something businessy is probably best I think.
someone on reddit said that ‘data science’ is a dying field
don't worry about the internet, it's just a fad
Data science also has a lot of non-office environments to work in. Around here there are environmental data scientists who do field work in the Rockies.
No, don't trust reddit. Tech gonna evolve endlessly. A bunch of fat bum that sit on their basement on reddit and bot have zero credibility.
Guy on reddit says Data Science is a dying field :data-laughing:
- if you start a sentence with someone on reddit said . . . Then stop, don't waste your time with STEMlords even if you are one
- there are plenty of fields in computer science, just do the one that you find the least boring
All computer science uses the same fundamental skills, no matter what you specialize in you can still generalize. Me and my friend have this meme where no matter what problem we're faced with and despite all the derranged solutions we cook up the most optimal one always involves the use of a stack.
EDIT: Just read you wanna escape the US (Same), if that's your only goal the steps are easy.
Pick the country you want to go to, learn its language, get a language teching qualification, get hired to teach English in that country.
Like, reddit, seriously. lmao. Wish Elon had bought that instead of twitter, f*ck that shite hole of a shite.
hmmm I dont know if I'd call it a dying field? Seems extreme. But its boring, I hated data science, go for ML or AI.
It's the technological base that is used in a lot of data science.
As someone with a 20 year career in programming, I'd say it's more or less all a dead field; the future is in retrocomputing. Go ahead and major in history.
As someone who had to build systems to replace legacy systems, you're not wrong. Hell even that was almost a decade ago now. Give it 5 more decades and someone will probably be replacing my legacy systems with yet more "how many more bandaids until the beep boop money machines come back on and I don't get more angry phone calls" fixes for their boss who just leans on shit and yaks about golf all day.
