Gnome Chomsky 2.0

I started working. I did recently complete a graduate certificate in Software Architecture and Design, but this was a few years after I already started working as a software engineer. Long story short, the UW CLMS program has a internship option instead of the thesis. I took up an internship at a startup in Seattle doing computational linguistics work. After completing the internship, I stayed with the company as a software engineer, working on the back-end of their web app. After a few years there, I got a job at a big company as a software engineer. I don't see myself going back to doing pure computational linguistics since I really like what I'm doing now.

Reposting what I posted in another thread: I graduated from UW CLMS program a few years ago. I had a BA in linguistics and a few CS classes including Data Structures and a probability/statistics class. I completed the MS in one year and did the internship option instead of the thesis. You can complete the program in one year once you start the core classes. A lot of people spent a year taking prereqs in CS and probability/statistics. They're pretty lenient about probability/statistics and will let you self-learn it if you can pass the placement exam. But you pretty much have to take up until Data Structures. You can do this at a community college or at UW. UW has a very well respected CS program and teach Java. You can still take the linguistics and elective CLMS classes in the first year while taking the CS prereqs. As far as the core classes go, it's a lot of programming. There's a programming assignment each week. You're probably best off doing them in Python since it's a simple language and has a lot of NLP libraries. One of the core classes requires Python since you have to use NLTK. Although there's a lot of programming, you aren't held to any standards like you'd be in a CS class. Your code basically just has to run. As far as after you graduate, there are many routes you can go. A lot of people go on to do NLU/NLP at the big companies like Amazon and Microsoft. A lot of people, including myself, went on to just do straight up Software Engineering. Some other people have gone the more machine learning route. Other people go on to do research. Overall, it's a very diverse field and program. There's about a 50/50 mix of people coming in with linguistics vs CS. There are a lot of group assignments and people can play to their strengths. Even if you're not the strongest programmer, you can team up with someone who can handle more of the technical bulk. They're aware of the fact that people come in with different levels of experience, which is why they're pretty lenient, but they still have some minimum programming standards.

I graduated from UW CLMS program a few years ago. I had a BA in linguistics and a few CS classes including Data Structures and a probability/statistics class. I completed the MS in one year and did the internship option instead of the thesis. You can complete the program in one year once you start the core classes. A lot of people spent a year taking prereqs in CS and probability/statistics. They're pretty lenient about probability/statistics and will let you self-learn it if you can pass the placement exam. But you pretty much have to take up until Data Structures. You can do this at a community college or at UW. UW has a very well respected CS program and teach Java. You can still take the linguistics and elective CLMS classes in the first year while taking the CS prereqs. As far as the core classes go, it's a lot of programming. There's a programming assignment each week. You're probably best off doing them in Python since it's a simple language and has a lot of NLP libraries. One of the core classes requires Python since you have to use NLTK. Although there's a lot of programming, you aren't held to any standards like you'd be in a CS class. Your code basically just has to run. As far as after you graduate, there are many routes you can go. A lot of people go on to do NLU/NLP at the big companies like Amazon and Microsoft. A lot of people, including myself, went on to just do straight up Software Engineering. Some other people have gone the more machine learning route. Other people go on to do research. Overall, it's a very diverse field and program. There's about a 50/50 mix of people coming in with linguistics vs CS. There are a lot of group assignments and people can play to their strengths. Even if you're not the strongest programmer, you can team up with someone who can handle more of the technical bulk. They're aware of the fact that people come in with different levels of experience, which is why they're pretty lenient, but they still have some minimum programming standards.

Is that your excuse?

Are you still annoying?

What's your undergrad GPA in your field? The other stuff shouldn't really matter.

Linguistics is the science (structure, sound, meaning) of language. Even though linguistics might be contained in the same school as foreign languages at your university doesn't mean the two are closely related. Linguistics can come in handy to leaning/teaching foreign languages though. I'd suggest taking a few real linguistics classes before making a decision to pursue a linguistics PhD. It can be some heavy stuff. If you're not passionate about R expressions, syntactic movement and anaphoras, then maybe linguistics isn't for you. My advice: do as much research as possible before making a major life decision.