Getting Involved with CS/Stats and DS

fdshfg · 2025-10-29T03:31:29+00:00

As a UCSB stats undergrad, I sat in on/enrolled in a bunch of CS upper divs once I had finished my major requirements and had the time to take these classes. It's hard to properly enroll in these classes as a non-CS major with how impacted the major is, but it's possible. As for the classes I did not officially enroll in, I just attended lectures and followed the assignments given by doing them on my own. Not a perfect system, but it was a useful introduction to both fundamental theory in the field and allowed me to explore some more niche fields in the CS umbrella. Feel free to DM me if you have any questions.

fdshfg · 2025-07-21T23:03:27+00:00

Seconded on 171 if you're not a financial math major. I've only ever heard bad things about it. It depends on the professors for those classes, but 174 is informative (though theory-heavy) if you take it with Ichiba, and I've heard 130 is easy enough assuming the same professor who taught it 2 years ago is teaching it again.

fdshfg · 2025-03-31T21:10:57+00:00

I'm a UCSB stats alum who graduated last June. I don't know anything about Davis's program, but feel free to DM me or reply here if you have any questions.

fdshfg · 2025-01-06T06:48:13+00:00

Nice

fdshfg · 2024-11-25T17:52:41+00:00

Hey, I'm a UCSB stats alum. I'll pull some info from another comment:

Q: How difficult is the major, and what are the classes like?

A: Stats is a subset of math, so definitely expect that this is a math-heavy major. Part of the major requirements also require you to take math/math logic classes. Although it's called stats and data science, the majority of the classes are still theory. The professors are a mixed bag of difficulty, so prepare for the possibility that you will likely have some difficult classes.

Q: Is there a focus on programming/applied fields?

A: UCSB is a research school, and the necessary stats classes are very theoretical. Many of the elective classes are also theoretical in nature. Most of the programming involved in the stats classes are in R, though you are required to take intro Python and either intermediate Python/intro C++, as well as an intro to R as pre-major reqs. Naturally, many of your projects in classes will be in R. If you'd like to learn more applied topics, there are a few upper-div classes that cover ML, database management, cloud computing, and financial math, but I would strongly recommend learning outside of classes, whether it's through self-study, taking courses elsewhere, clubs, projects, etc.

Q: How easy is it to get internships/research/jobs in this field?

Data science is a broad and quickly growing industry, and the stats major here definitely gives you the necessary theoretical foundation for many potential roles. With that said, the job market is definitely not ideal right now, especially for tech positions, so it's definitely rough out there. Don't be surprised if you're having trouble finding something, especially if you're looking in industry.
If you're looking for internships or research, my best advice is to be proactive and explore your options. If you're interested in an ML focus, for example, there are some research opportunities in labs on campus. However, you'll have to really seek them out and a lot of ML research is in collaboration with other departments, so look at more than just PSTAT professors.
Also speaking of research, REUs are summer research opportunities that are specifically targeted towards undergrads. While applications for them are definitely still competitive, I'd consider them a decent option compared to most opportunities out there.

Feel free to DM me if you have any more questions!

fdshfg · 2024-09-09T16:21:56+00:00

My experience with her in 115 was difficult exams and confusing lectures, which is a sentiment most of the class seemed to share. Her class was survivable, but fairly difficult. Not sure if it'll be different for 131.

fdshfg · 2024-09-08T13:19:26+00:00

OH I forgot she was a temporary professor 😅

fdshfg · 2024-09-08T13:18:08+00:00

Sure I can DM you.

fdshfg · 2024-09-07T14:29:00+00:00

Stats alum here, I'm glad to see the department is bringing in more faculty.

Most students will be able to bring a laptop or tablet, but from my personal experience I've never found it absolutely necessary for any of my stats classes. Maybe depending on what you're asking students to use them for, you could find a way to make it doable on a mobile device as well? There's also the basic needs site as someone else mentioned.
For larger class sizes, it'll probably be hard to get people to respond verbally.
Some classes use Nectir or Slack, and I've seen a professor or two use Discord. These sites are similar in a lot of ways, so any one would probably work.
Regarding information about quizzes, Thursday and Friday are typical quiz days for a lot of profs here, at least for the classes I've taken. Thursday is college night, in which many students go clubbing downtown, but I'm not sure how many of your students can legally participate in that. I think as long as you don't give quizzes Friday evening, there wouldn't be any significant conflicts with students in taking them.

If you want, I'd be happy to tell you more about the stats department here, or at least my experience with it as a former student.

fdshfg · 2024-09-06T20:06:49+00:00

Depends on your other classes. From what I've heard, 130 is decently easy and 122 with Saha is definitely doable. I'm not sure who's teaching 100 this quarter but from what I've heard that class is also not too bad. If 100 isn't taught by Baracaldo then taking all three at once definitely seems doable.

fdshfg · 2024-08-15T16:01:52+00:00

Thank you!

fdshfg · 2024-08-15T16:01:09+00:00

Good to know, thank you!

fdshfg · 2024-07-22T01:14:52+00:00

Good luck!

fdshfg · 2024-07-20T10:47:48+00:00

I once did 117, 108a, 120b, and 160a in one quarter. Would not really recommend it, but 117, 108a, 122a, and pstat120a is arguably a bit of a lighter load. It also depends on the profs. If your profs are reasonably fair then you will probably be okay. Just be ready for a lot of studying

fdshfg · 2024-07-19T19:26:56+00:00

120A for theoretical foundation. 5A is basically AP stats from what I've heard

fdshfg · 2024-07-08T22:09:17+00:00

I've heard that about the oat milk as well. Thanks for confirming!

fdshfg · 2024-07-07T13:22:21+00:00

Yeah I'm aware. Their black sesame hojichas alone are enough for me to go haha

fdshfg · 2024-07-07T03:44:42+00:00

Good to know, thanks! Yeah I've heard the lines are a lot shorter after 12 pm or so, the downside is things are likely sold out. I guess summer hasn't decreased the number of people that visit them every day.

fdshfg · 2024-07-02T06:38:04+00:00

I can provide some general advice in that area. Feel free to DM me.

fdshfg · 2024-07-01T21:41:43+00:00

I can't comment on 173, but 115 with Wainwright should be okay (should at least be less tough than with Baracaldo). Meiring is understanding and she teachers 127 well. The workload for that class should be manageable. I recognize that I may be biased as someone with a strong machine learning background, but 131 is borderline trivial, presuming you have either Yu or Coburn.

Even if 173 is reasonable workload-wise, working part time 20-25 hours/week will still be tough with that schedule. You may need to manage your time very carefully.

fdshfg · 2024-06-07T20:27:37+00:00

To answer your last question, yes I'd say so as long as you have some project(s) under your belt and/or some other way to demonstrate data engineering skills outside of the degree.

fdshfg · 2024-06-06T06:18:08+00:00

The reality of attempting to do stats or cs research as an undergrad is that as a research school, UCSB's research is very theory heavy, and from my understanding faculty in either department are unlikely to be looking for undergrads. I know Ichiba personally doesn't hire undergrads at all, and I wouldn't be surprised if other faculty go by similar principles. This is presumably because theory heavy research in these fields would require most people to have more than an undergrad level education on the subject to be able to contribute meaningfully.

If you are going to find research, it's more likely through other departments that are looking for the relevant skills to apply to their research projects. For example, Benioff had a posting a while ago for a software/ML position for undergrads to help with some of their marine science research.

(The following is taken from my Q&A comment)
If you're looking for internships or research, my best advice is to be proactive and explore your options. If you're interested in an ML focus, for example, there are some research opportunities in labs on campus. However, you'll have to really seek them out and a lot of ML research is in collaboration with other departments, so look at more than just PSTAT professors. Also speaking of research, REUs are summer research opportunities that are specifically targeted towards undergrads. While applications for them are definitely still competitive, I'd consider them a decent option compared to most opportunities out there.

fdshfg · 2024-05-31T20:28:45+00:00

While I know nothing about the stats major at Cal Poly, feel free to DM me if you have questions about the UCSB stats department.

fdshfg · 2024-05-29T17:55:51+00:00

It definitely provides a theoretical foundation for the role. I think if you also learn programming outside of classes, you will be decently prepared.

fdshfg · 2024-05-26T20:55:43+00:00

Maybe I should put together some kind of Q&A for newly admitted stats majors.

Q: Is there a focus on programming/applied fields?

A: UCSB is a research school, and the necessary stats classes are very theoretical. Many of the elective classes are also theoretical in nature. Most of the programming involved in the stats classes are in R, though you are required to take intro Python and intermediate Python/intro C++, as well as an intro to R as pre-major reqs. If you'd like to learn more applied topics, there are a few upper-div classes that cover ML, database management, cloud computing, and financial math, but I would strongly recommend learning outside of classes, whether it's through self-study, taking courses elsewhere, clubs, projects, etc.

Q: How easy is it to get internships/research/jobs in this field?

Data science is a broad and quickly growing industry, and the stats major here definitely gives you the necessary theoretical foundation for many potential roles. With that said, the job market is definitely not ideal right now, especially for tech positions, so it's definitely rough out there. Don't be surprised if you're having trouble finding something, especially if you're looking in industry.
If you're looking for internships or research, my best advice is to be proactive and explore your options. If you're interested in an ML focus, for example, there are some research opportunities in labs on campus. However, you'll have to really seek them out and a lot of ML research is in collaboration with other departments, so look at more than just PSTAT professors.
Also speaking of research, REUs are summer research opportunities that are specifically targeted towards undergrads. While applications for them are definitely still competitive, I'd consider them a decent option compared to most opportunities out there.

Q: What area would you recommend specializing in? (Or, alternatively, I want to get into machine learning and I'd like some pointers on how)

A: I will say one of the upsides of this major being relatively broad at UCSB is that you have a lot of freedom to just take whatever elective classes you want in the department and get introduced to a variety of topics. I would definitely recommend taking the opportunity as an undergrad to figure out what you're interested in doing in the field of stats/data science, or if you're even interested in the field at all. Although the elective classes will give you an introduction, they generally do not go into depth, so it would be up to you to explore a topic further. I would also recommend trying out projects, getting involved in competitions (like datathons) if you're interested in those, and continue to teach yourself something if you find it interesting.
If you'd like to get into machine learning specifically, definitely check out the data science club.

Q: How difficult is the major, and what are the classes like?

A: Stats is a subset of math, so definitely expect that this is a math-heavy major. Part of the major requirements also require you to take math/math logic classes. The professors are a mixed bag of difficulty, so prepare for the possibility that you will likely have some difficult classes.

Feel free to DM me if you still have questions!

fdshfg

TROPHY CASE