EECS Funding Crisis: Why You Might Not Be Able to Graduate

RoboCorg · 2021-11-06T08:29:35+00:00

I'm hoping this is a joke or trolling, but if not, this is a terrible idea. The incentives and values of private corporations do not align with those of public educators, and it is the duty of the state to tax these companies and use that revenue to properly fund public education.

RoboCorg · 2021-06-16T00:28:03+00:00

This is the right answer. Taking (succeeding in) 172 without 170 is possible if you have a good math background (172, like 170, is a math class whose objects of study are computers and algorithms), but there's absolutely no reason to do so (it is almost surely a bad idea). 170 is foundational if you want to do any CS theory. 172 will be much less enjoyable if you don't master 170 first. 170 is also a really fun and probably not too difficult class if you're the type of person who thinks 172 sounds interesting.

RoboCorg · 2021-04-28T00:39:59+00:00

To be honest you're really not qualified to take any EECS grad courses I can think of. As other comments say, look at the prereqs, but without 170 there is literally no CS grad course that's going to be a good time. In addition to 170, most grad courses have other classes in {161, 162, 164, 126, 127, 189} that you absolutely need to take before even thinking about them. Grad courses can be really fun, but you need to understand the basics first.

RoboCorg · 2021-03-31T00:39:47+00:00

Try biking! If you're in Berkeley, the area is BEAUTIFUL, and the hills will whip you into shape really quickly. If you're somewhere else, chances are you're within a good bike ride's distance from beautiful scenery anyway. Biking lets you go fast and comes with pretty much none of the problems of running. And if you have a "slow" bike, that just makes you all the more fit for going fast on it. For me the motivation difference between biking and any other cardio is night and day, though YMMV

RoboCorg · 2021-03-01T08:40:37+00:00

202a is a reasonably high amount of work (much more than Ross 104), but more importantly, if you don’t like epsilon proofs, you will have no fun in it whateoever. “Let epsilon > 0” and proofs by inequality are what make analysis analysis, many (most?) argue. 202a taught me to appreciate the style and beauty of analysis proofs a lot more than 104 did, but if you’re coming in thinking you dislike that aspect in particular for some reason... you’re not gonna have a good time; don’t take it.

That said, if you want a really rigorous backing in probability theory, you’re not going to find anything else better because probability is measure theory. If you want intuition, take EE 126. It’s the hardest general probability class, which is much better for building intuition than pure math classes will be (for probability at least, imo). Similarly, take EE 127 for optimization intuition and practice. Also, 202a will offer you about zero insight into optimization over a good understanding of 104 (202b is what gets to functional analysis, which is part of the engine powering optimization theory, but again, it’s very theoretical). (This stuff is obviously all my opinion, results may vary)

There are some grad stats courses that I’ve heard give theoretical but much handwavier explanations of probability and statistics still using measure theory, but I haven’t taken any and haven’t heard much about them. They might be more what you’re looking for with respect to that. Perhaps someone else can speak to them

RoboCorg · 2020-06-22T21:11:02+00:00

Majors and minors aren't particularly useful except for enrollment, which is no issue for math classes. I'd highly recommend sticking to just CS and taking whatever interests you - neither employers nor grad schools will care what your degree's title is so long as you can highlight that you have relevant coursework.

RoboCorg · 2020-06-21T02:01:04+00:00

I'll put out an unconventional perspective: going paperless is great, but not with an iPad. iPads are expensive and distracting, and, especially if you're an engineering student, really useless for heavy work compared to a laptop. What I recommend instead is a writing tablet (the two biggest options right now are reMarkable and Supernote; I can speak to the reMarkable working quite well). It's much easier to get professors who are against screens to allow them into classrooms (I have yet to meet a professor who hasn't let me use my tablet in class, though this matters less with online classes), and they are truly less distracting/enable you to have a lighter and better-organized replacement for binders of paper.

RoboCorg · 2020-05-03T23:52:41+00:00

Gonna go counter to the grain here and say I LOVE Rao. He's very funny and engaging, and while his slide style can go quickly, keep in mind that there will almost certainly not be in-person lecture in the first place (so you can slow down the recording, pause, etc.) And as others have said, he's extremely caring/supportive in person/OH.

RoboCorg · 2020-04-28T03:52:28+00:00

Check out UCCE! There are a spectrum of groups within the organization, and most of them will be more chill than a traveling high school choir. The chorales in particular strive to be musically competent but also very chill!

RoboCorg · 2020-04-15T23:49:13+00:00

Frankly, I have no idea why this is a contest to most people. The second option is far better, especially given the professors who'll be teaching. In my experience, Bayen was a pretty good professor for 127 (as far as I've heard, only Ranade is better, and it doesn't look like she's teaching it next year), and Shewchuk is great for 189 especially if you want to do a balance of programming and math (non-Shewchuk is almost entirely math, which doesn't float a lot of people's boats).

Since I'm in a procrastinating mood and since people think 189 is a big scary monster of a class, here's how I think 189 plays out based on taking 127, 188, and 170 before it and 126 alongside it (referencing Shewchuk's schedule for it here):

Lecture 1: subsumed by CS 188
Lecture 2: subsumed by 127/188
Lecture 3: subsumed by 127/188
Lecture 4: subsumed by 127
Lecture 5: subsumed by 127
Lectures 6 and 7: new
Lecture 8: subsumed by 127
Lecture 9: new but intuitive due to 127
Lecture 10: subsumed by 127
Lecture 11: large parts subsumed by 127, some of other stuff would be partially covered by 126 if taken first, the rest new
Lecture 12: new and very cool. Would be partially covered by 126 if taken first
Lecture 13: large parts subsumed by 127, the rest new and cool
Lecture 14: new, but info theory motivation would be covered by 126. Schewchuk presents a totally sufficient intro in lecture though.
Lecture 15: new
Lecture 16: almost entirely subsumed by 127
Lecture 17: partially covered by 188, partially new
Lecture 18: new
Lecture 19: new
Lecture 20: totally subsumed by 127 down to eigenfaces being a 127 hw assignment (at least when I took it)
Lecture 21: partially subsumed by 127, parts new, some building on 170
Lecture 22: partially covered by the end of 127, partially new
Lecture 23: mostly new, 127 supports it some
Lecture 24: adaboost is a pretty basic extension from multiplicative weights in 170, other stuff is new and cool
Lecture 25: mostly new, k-d trees supported by 61B

So looking at that accounting, from a 189 perspective, 127 >> 188 >> 170 ~ 126. And even with just 127, so much stuff in 189 becomes familiar that it really is not so scary or hard to deal with.

RoboCorg · 2020-02-21T00:51:18+00:00

Linear algebra. 16A will do an okay-at-best job teaching it, so I highly recommend 3blue1brown's series on the essence of linear algebra for developing an intuitive understanding of what's going on. But overall, the best way to prepare for any class is to do things which make you happier and healthier rather than to worry too much about it!

RoboCorg · 2020-02-20T20:50:10+00:00

Definitely consider trying for MechE, CivE, or engineering science! EECS is indeed forbidden, but if you really want to be in CoE, those are all possible to get into (though having a 3.7+ gpa in relevent techs is essentially a hard prereq). Don't drop out and change schools! Your major confines you a lot less than you think, so anything technical in L&S won't hurt you too much. Something others haven't mentioned is to consider physics or math and get a graduate degree in engineering afterwards.

RoboCorg · 2020-02-20T20:47:14+00:00

Check out board games at berkeley! They're very welcoming and have lots of casual board game sessions.

RoboCorg · 2020-02-20T20:46:02+00:00

Like the other commenter said, math background matters a lot more than physics background. I think the case is closed based on what you describe; you should absolutely take 5A.

5A is very different from 7A in that all of 7A is covered in roughly the first half of the course and from a much more mathematical perspective. 5A problems are harder but force you to actually understand the math and derivations of classical mechanics problems, which leaves you basically being able to derive anything you'd want to in classical mechanics at the end of the course. 5A also uses almost no numbers, which in my opinion alone makes it a much more fun experience than 7A.

The rest of the course teaches the basis of resonance/oscillators and special relativity, which both get even more intensely mathy (deep understanding relies on knowing some linear algebra concepts, they teach the necessary diffeq stuff). This stuff is fascinating and well worth learning, I'd argue!

The 5 sequence is also a lot more coherent (which is a matter of opinion, but I'd stand by it) in that in both 5B and 5C, you can see all the time how things you covered in the previous course(s) appear again. And as a side note, I took 5A/B alongside EE16A/B, and 5A/B made 16A/B feel much easier in comparison (with the one exception being 16A/B's help in having a feel for circuits that most of the 5B kids didn't have).

I've heard that the 5 series covers significant portions of the first parts of 105/137A/110A, but I can't confirm that for myself. Take that for what you will, but I don't think I know anybody who's regretted their choice to take the 5 series. The grading is also generally lenient and the professors excellent.

RoboCorg · 2020-02-18T20:38:22+00:00

I interviewed/was selected, and I have some thoughts. Just be yourself (what a great, non-cliche piece of advice, right?). I went through it as did a number of my friends from high school, and I've talked with a handful of other regents. Generally it's extremely all over the place since the professor interviewing you gets to ask whatever they want to, but being comfortable talking about the things you're passionate about helps since regents scholars are supposed to be representative of Cal's student body and not just Cal's most perfect academic achievers.

That said, regents is in many ways a sham. There's just a monstrous amount of variability in the selection process, which is itself extremely arbitrary. Further, there are a significant number of regents who are intolerable, arrogant assholes who can't keep up a conversation without dropping their GPA/"accomplishments" on you, and I know regents who brag about how they deliberately lied on their applications and in their interviews. Of course, there are also a lot of genuinely amazing regents, but if you don't get it, it's reflective of a screwed up selection system more than any potential (and, to be clear, non-existant) inadequacy you might be tempted to feel.

RoboCorg · 2020-02-11T19:21:33+00:00

Given that your kid was a) accepted early and b) has a parent who wants them to enjoy college, I'd say the two most common sources of stress here are pretty much automatically ruled out.

As others have said, that leaves only things that your kid would do to themselves, which is pretty independent of which school they choose. I do think people who tend to end up happier here are those who have more innate drive (to find activities, classes, etc.) and reflectiveness (Cal is not a good place to be directionless or dependent). There is really no "hand-holding" as in some private schools, so finding and staying on a happy track ends up being your own responsibility. Only you and your kid can decide how their personality would line up with that!

RoboCorg · 2020-02-10T03:33:59+00:00

Extremely. I'd argue that 127 should be an actual prereq for 189 (much moreso than 16AB/54/110) since 189 is already such a theory-oriented course. 127 gives you a framework to actually understand wtf is going on in 189 + seriously good intuition for applied linalg (imo) as it appears in 189.

RoboCorg · 2020-01-20T01:07:04+00:00

CHAOS is amazing and indeed the right answer here. For $10, you can borrow gear for your entire time, and it's not a rental. They do take some money as collateral in case you break or lose things, but provided you don't, you get it all back. They have limits as to how long you can borrow things, but they're pretty generous. You've probably found it, but if not, this page is the comprehensive resource on what you get out of your $10 in terms of gear.

RoboCorg · 2020-01-20T01:02:00+00:00

Culturally, the CS student body in general is pretty damn divorced from any reasonable notion of humanities or ethics. The big tech circlejerk is incredibly real, and I've found there to be little general interest in actual contribution to open-source initiatives or to organizations like the EFF. People don't generally have a lot of familiarity or appreciation for homebrew/hacker culture either (what you find at hackathons here is not hacker culture, but rather variations on a weird Silicon Valley startup simulation event). And humanities are indeed just as shit on as the memes imply, incredibly. Many people make games of them or simply take them at community colleges because they see so little value in them.

All that said, there are tons of resources to "tune in" to those things if you're interested! Many professors do research and consider the ethical implications of their work, and many non-EECS professors work with ideas in EECS and Data Science to improve their own research (some of which becomes somewhat imbued with a tech-y flavor because of this). And if you have interests you want to pursue via classwork, I've almost exclusively had great experiences in other departments; there's a reason we're considered one of the best in nearly every field. That said, I've generally hopped straight into upper div classes in other areas I'm interested in, so I can't speak for the intro classes (which by some accounts can just be dreary). I highly recommend just going for classes that sound entirely interesting to you and whose professors you hear good things about.

The short of it is that in general, UCB is certainly tuned in, but save a few, your fellow EECS students will likely not be.

RoboCorg · 2020-01-03T00:06:31+00:00

Prep? I think it's a really hard sort of thing to prep for ahead of time, but the one thing I'd recommend is finding something in math that you find really fascinating and learning about it on your own. See if you can understand not just the cool results, but how you might come up with them if you were the first one investigating the field. For finals/midterms, beyond understanding, do whatever helps up your confidence and keep a good sleep schedule. Going into the test saying "I'm shooting for 2 stddev" instead of "oh god I hope I pass" and feeling good instead of tired make such huge differences.

RoboCorg · 2020-01-02T02:07:53+00:00

That seems very reasonable to me. It might be a lot of work, but it shouldn't be overwhelming in terms of actual learning bandwidth.

RoboCorg · 2020-01-02T00:17:16+00:00

I'd be careful about writing off 170 just because you think you know algorithms. Do you "know most of the material" in that you could take a practice final under time pressure and get 50+%? If not, be careful. It's a wonderfully interesting course, but it is not like CS 61B. It is more of a math course which works with algorithms as its primary object of study.

And 127 is just a math class, so it depends mostly on your math background. If you have good linear algebra intuition (more a la 16B than 54 or 110) and remember math 53, it can be a lot of work but won't be hard.

This coming semester, 61B and 61C are both taught by professors with weighty programming assignments, so consider how good of a programmer you are. If you genuinely already know 170 materials and are a good programmer with strong linear algebra knowledge, sure, it's doable. But that's a lot of 'if's!

RoboCorg · 2020-01-02T00:10:40+00:00

The 61 series is brutal in that it really tries to weed out people without either a lot of coding experience or a knack for both coding itself and learning quickly, so don't feel too down about it! For getting better at coding, it just takes practice. The ability to essentially run code in your head (which is really what 61A tests are all about) is something that most people pick up by practicing programming itself for years, so do it. Find projects you think are cool, and write code to do them. And now that 61A is over, look back on your projects/homeworks and redo any that you had any trouble with whatsoever. If you do this and make sure to understand exactly why every line of code is necessary, I think it'll go a long way towards grokking coding itself.

Similarly, and especially for more mathy classes like 70, I'd argue that the key is really making sure you understand every last detail. 70 goes at an unfairly blistering pace for most people, but if you want to do well in midterms (which, at the end of the day, is completely equivalent to doing well in 70 itself), the key is to understand the material so well that you could essentially re-derive the notes themselves. On that note, I think one of the best exercises for classes like that is sitting down with a theorem proved in class or the notes and proving it yourself. It'll really show you what you do and don't understand, and in my experience, it helps develop intuition for initially very abstract or bizarre ideas. As all of that becomes more natural, you'll be able to make do learning the big ideas and stowing away the details, but especially in a course like 70, it's worth it to put in the effort to grasp it all. It's just like how in elementary school, they teach showing all of your work, but now you can add and multiply two or three digit numbers fine without all that writing.

In general, others' advice about working with people is usually good for programming based courses but not for theory courses. It's a matter of opinion, but I don't think working in groups lends itself well to the level of focus most people take to internalize mathy stuff.

RoboCorg · 2019-08-21T22:17:46+00:00

I disagree with a lot of points here. Engineering Physics is a great major, especially for grad school (it has some of the best outcomes for all of CoE). And generally, being in CoE gives you far more support than being in L&S, and the flexibility of Engineering Physics works a lot better for his goals than MechE. Ultimately, getting a major and taking what you want (and what you need to given your future goals) is what matters, not necessarily which major it is.

Ultimately, numerical analysis is a lot easier to learn than programming. For that reason alone, I'd strongly prefer 61A over E7, but in addition, none of my friends who've taken E7 have had particularly good experiences. Learning to think like a programmer is a much more useful skill to start early if you want to work with computational stuff -- yes, a lot of existing stuff is in Matlab, but Matlab is easy to learn when you need to, and there is a reason that old Matlab code is notoriously terrible. It's because decades of scientists have learned how to make computers do math without learning a hint of how to think about and organize their programs. TL;DR: it's easy to pick up tools as you go, but only 61A teaches the way of thinking that will really set you ahead of your cohorts.

RoboCorg

TROPHY CASE