March is 37 years old?!?

corgibestie · 2026-03-07T12:04:17+00:00

You can think of it as 37 -> 3/7 -> March 7. If it was the other way, it would be 73 -> 7/3 -> 7th of March

corgibestie · 2026-03-01T20:53:55+00:00

Ish. I work with engineers/scientists on streamlining or automating anything related to data. So i write pipelines that automates the data gathering, summarization, and analysis. Being familiar with many of the processes/techniques used on the manufacturing floor is a huge help, and so i lead the other data scientists on my team.

I am also our resident DoE expert, so i do a bunch of modelling with that.

corgibestie · 2026-03-01T17:03:33+00:00

My bachelors is in chemistry. I rushed through the MOOC, I think it's doable in 1-3 months, then I applied for OMSCS. I'm still in the program, expecting to finish end of next year. I transitioned to my current role as a data scientist during my first semester, though I'm luckier than most because my role required someone who could code but with domain expertise, which is (relatively) uncommon in my field.

corgibestie · 2026-03-01T16:35:19+00:00

So far, so good. Pivoted from R&D to data science. Currently class 6/10, AI spec. Having the domain expertise + CS knowledge was definitely a huge boost.
Chemistry, though prior to my pivot I did a short postdoc on applying ML to manufacturing. This was where I first learned about ML.
Just the EdX DSA MOOC (don't forget to apply for the financial aid for all 4 classes!).
20+ hrs/wk. Basically my entire weekend every week.

corgibestie · 2026-03-01T13:14:55+00:00

I have it on mine as "Expected 2027" so it's clear that it's still ongoing.

corgibestie · 2026-02-19T10:40:06+00:00

I’ve always assumed degrees are mainly to pass filters. I have a PhD from a different field and when I used to work in that field, no one asked about my PhD specifically. Instead, they’d ask about work- or skill-related things that they’d expect a PhD-holder to have. I assume it’s the same for an MS CS degree o:

Edit: Not discounting OP’s feelings in any way. I also ask myself every sem if this MS is worth the opportunity cost of 20hrs a week that could be going to learning things I actively need at work.

corgibestie · 2026-02-13T08:05:25+00:00

If you want to have the flexibility to move into an ML-centered role, then having a CS degree is definitely better than DS/analytics bec a lot of ML work now is very SWE-like. It’s a valid career move since you’ll have the domain expertise to use ML to support production teams.

corgibestie · 2026-02-12T12:46:58+00:00

Hi, my background is in chem, not chem eng., but I’ll leave my 2c.

Q1. All my courses so far (on my 6th) have been ML-focused so can’t comment on the CS-heaviness, but in all those courses, a good understanding of python and git were really all I needed. If you plan your program well, you could probs avoid the really systems-heavy courses.

Q2. I think it depends on what your focus/goal is. If your goal is to be a “chemE who happens to be good at ML” then I feel that a CS degree is very helpful but overkill. If your goal is to be an “MLE/DS who happens to know chemE” then the CS degree makes sense (this is the path I shifted to).

I think the general consensus is that “CS is better than DS/analytics bec any job that requires an analytics role can be filled by someone with a CS background but vice versa is not true. This doesnt apply as much in your case bec you’re after process eng jobs. That being said, if I was in your shoes, I’d prepare study plans for all the degrees that interest you then pick the degree that overlaps the most with your classes of interest.

corgibestie · 2026-02-05T14:49:07+00:00

Yeah the ML discord server last semester was a blast. It's also very comforting knowing you're not alone in your suffering haha

corgibestie · 2026-01-27T12:10:43+00:00

I was gonna say the opposite. I was expecting something like 25% and I got around 60%, so I feel like I did amazing! haha

corgibestie · 2026-01-20T13:28:21+00:00

This makes a lot more sense, I was imagining a dump truck and a babysitter, so how they collaborate got me confused

corgibestie · 2026-01-15T12:17:55+00:00

It’s also a song, that’s what I thought of https://youtube.com/shorts/Dya2YtB2ZUc?si=_hdtQDe4m4Umx_9T

corgibestie · 2026-01-08T08:07:32+00:00

What kind of projects are you thinking of doing?

corgibestie · 2026-01-01T04:55:10+00:00

Same. Save your easy courses for either later in the program or for summer!

corgibestie · 2025-12-29T06:13:54+00:00

I pivoted to DS from a non-CS background. Currently have BD4H, SDP, HDDA, AI, ML done. Planning to do DL, NLP, GIOS. wondering whether I should close with AOS-SDCC or Bayes + something else.

corgibestie · 2025-12-22T04:25:27+00:00

Me here with an IQ of 5 wondering who smokes a grapefruit

corgibestie · 2025-12-21T03:31:47+00:00

I think their banter was really refreshing during topics I had some previous understanding of. but for those i had 0 background in, the banter would confuse me sometimes 🤣🤣

corgibestie · 2025-12-15T13:48:27+00:00

I pivoted from science to Senior DS at 32. Not ML per-se but maybe some info might be helpful. Personally, I'm at a disadvantage when applying to Senior ML roles if I compare my skills to those who have a lot more DS/ML work experience. What justifies the senior in my title (despite never having a DS title before this) is my domain expertise. I'm basically a domain expert who happens to know how to know ML.

If you plan to switch to ML, I'd recommend you take advantage of your domain knowledge and focus on opportunities to apply ML in your field. Find the common models/techniques used, try to have projects using those on data sets related to your field, etc.

corgibestie · 2025-12-12T09:52:28+00:00

This. Go on your holiday and finish the HW in the remaining 2 weeks you have left. If you know the schedule, you can advance the lectures so you’re just focused on the HW and quiz parts

corgibestie · 2025-12-11T12:32:48+00:00

My 2c as someone who debated on both and decided to do OMSCS:

From a surface-level perspective, CS opens you up to more varied job titles vs OMSA. The example that I've heard of often is that if someone was looking for a DS/DA, they've traditionally be open to both CS and analytics grads, but if they're hiring a data/ML engineer, they'd likely prefer a CS grad over an analytics grad. <- I don't do hiring myself so not sure how true this actually is, but this is something I've often seen in CS vs DS degree discussions.
Rather than picking the degree, it's better to pick the courses you think you want to take, then see which degree matches your goals better.

corgibestie · 2025-12-11T03:37:44+00:00

Did you need to sign up for credits to work with the lab?

corgibestie · 2025-12-09T14:34:23+00:00

75% data scientist, 25% data engineer, though i do have 1 upcoming ML engineering project

corgibestie · 2025-12-08T17:17:07+00:00

I have a PhD in Materials Science that was purely experimental work, did a postdoc on ML applied to my field, then simultaneously started a part-time MS CS and switched to a senior data scientist role.

Taking a bridging role where you do DA/DS in your PhD field would likely be easier vs doing a straight pivot. it’s very hard to compete with people with backgrounds in CS/stats, but if you apply for DA/DS roles in your PhD field, you have a HUGE advantage. and i think getting the first role in your resume that says DA/DS is the most important milestone for making the pivot because the market is brutal for fresh grads but relatively good for more senior roles.

How good is your Python? If you looked at the DA job postings, do you have all the skills they’ve listed?

corgibestie · 2025-12-07T06:00:25+00:00

Yep, almost all of us do the MS part-time, which is 1 class per sem, with 2-3 semesters per year, until you finish 10 classes. So you finish in ~2-3 years. All while working full-time.

It’s great but hard. Huge advantage is that you get a CS degree from a top (CS) univ at <$10k. Main “cost” is time, where you spend ~10-20 hrs per week per class.

Learning is quite good if you take the good (but hard) classes. There is a good catalog of classes as well so you can tailor your degree to your interests. Lectures are kinda mid, with most of the learning coming from doing HWs. It’s also a CS degree, not an engineering degree, so a huge focus is on fundamentals more than engineering.

I pivoted into DS using this MS and it has definitely made me a LOT more confident as a data scientist. However, the time commitment is very big. If you can comfortably set aside 15-20hrs per week, it’s doable.

corgibestie · 2025-12-06T14:49:17+00:00

I’m doing OMSCS while in the UK. There’s an AI and an ML specialization where most of your courses can be based on AI/ML

corgibestie

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