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> why should I trust the university selection process more than those corporate hiring ones? I don't know the US education system enough, but there are some sc

> why should I trust the university selection process more than those corporate hiring ones? I don't know the US education system enough, but there are some schools out there which are much more selective than any SWE interview process. You can be guaranteed that the worst student from these top schools could nail any algorithm interview with minimal preparation. But these big companies hire many more people than these few schools can provide, and they do so globally, from countries that may not have such elite schools.

majormajor 5y ago
Needing to hire more than just the top schools graduate is certainly a reason companies can't limit themselves to university selection processes. But that's not all that's going on here! CalTech is pretty selective as far as US schools go (6% acceptance rate). Slightly more than MIT, slightly less than Stanford. SAT score stats all in the same 1500+ range. But they're offering this course, and that makes me think that no, the worst student from these schools in the US, at least cannot nail any algorithm interview with minimal prep! And that makes sense, from a US perspective! Getting into CalTech or Stanford or MIT is about doing well at high school/early-college level material in high school, and about extracurricular activities, with a dash of being able to afford it and being told it's something you should try for. Most of that high school curriculum - even most college-level CS material - isn't super applicable to a software engineering job. It's heavier on memorization (we have google for that!) and it's heavier on theory than on creative application of things. I might argue that any test or course where the answers to the exams come straight out of the textbook isn't worth as much as it used to be, since we've got Google and SO and all the books too! That's a big part of why a lot of these whiteboard interviews aren't simply "write out Dijkstra's algorithm" (boring, textbook!) but are about seeing if you can figure out how to use apply CS in a situation where the way the problem maps to the algorithm isn't immediately obvious. Creative work has a long history of not aligning well with traditional US university admissions criteria and evaluations.
- yodsanklai 5y ago
  > But they're offering this course, and that makes me think that no, the worst student from these schools in the US, at least cannot nail any algorithm interview with minimal prep! I think it's impossible to nail these interviews without minimal prep. It's very specific, and every candidates are well-prepared, many of them have done 500+ leetcode questions before interviewing. Regarding the US universities, I'm not sure but I wonder if some students can somehow compensate a lack of academic mathematics excellence with extracurricular activities, or being rich or from a minority. Maybe companies want to filter those out? As for creativity, leetcode interview questions is all about preparation. There's little creativity.
  - saagarjha 5y ago
    > I think it's impossible to nail these interviews without minimal prep. It's very specific, and every candidates are well-prepared, many of them have done 500+ leetcode questions before interviewing. It’s definitely possible. Mostly you’d want to learn your algorithms well in college and continue to exercise them in your work. The rest of the interview is a lot about how you present yourself, which is mostly along the lines of “work out the problems out loud and ask questions”. Also, FWIW, I’ve had a decent amount of opportunities for creativity on Leetcode-style questions. When permitted I often pick the language that I feel would make the solution simpler or easier to understand. When doing things like linked list or graph traversal you’re often asked to define the datastructure you’ll be using, which is a good chance to use different types of polymorphism or algebraic datatypes that can make your task easier. Even if you’re just churning out for loops, a lot of them can be replaced with functional methods or selective application of interesting utilities such as array rotation.
    - yodsanklai 5y ago
      > Mostly you’d want to learn your algorithms well in college and continue to exercise them in your work. The rest of the interview is a lot about how you present yourself, which is mostly along the lines of “work out the problems out loud and ask questions”. Not my experience. When I interviewed at Google for a senior position, I mostly had difficult questions with little interaction with the interviewer. Before my preparation, I could solve all the questions within let say a couple of hours and I knew very well all the algorithms. But that's not what's expected to pass. You're competing with people who have been working very hard on this style of interviews and you need to be among the best. You're expected to find the answer to a couple of questions within a 40 min. That includes finding the solution, writing the code (not pseudo-code), testing your solution and discuss complexity. Thinking 15min + sketching some pseudo code is not enough, or maybe for a particularly hard problem.
- thaumasiotes 5y ago
  > But they're offering this course, and that makes me think that no, the worst student from these schools in the US, at least cannot nail any algorithm interview with minimal prep! My take on this is that the problem is misaligned expectations. I failed Google's algorithmic interview round twice under the assumption that when the interviewer asked me a question, the point was to see if I could come up with the answer. But that isn't true. The interview questions are chosen with the expectation that candidates cannot come up with the answer themselves. Instead, the point is for the candidate to cold-read the answer from the interviewer. When a test -- or a computer -- asks you how to do something, it won't care or even realize that you spent ten minutes thinking about the problem before starting to write a solution down. But an interviewer will fail you for doing that. That insight was enough to pass the interview round. And it also suggests that a course in "how to pass an interview" should boost CalTech grads' passing rates to nearly 100%, because all they need is to be informed of the "proper" technique.
SteveDR 5y ago
> You can be guaranteed that the worst student from these top schools could nail any algorithm interview with minimal preparation. Considering that CalTech offers this course, they must be realllyyyy misguided, or you’re talking about schools that are far more selective than CalTech (7% acceptance rate).
- yodsanklai 5y ago
  I don't know what it takes to study at CalTech. But I nailed the interviews at FB and Google and there's no way I could have studied maths at Cambridge for instance. Leetcode is just a matter of solving enough problems so that you can do them almost out of memory on the white board. The curriculum is basically algorithms at undergraduate level. Seriously, it's easy.
SamReidHughes 5y ago
Caltech does get the occasional bad admit, where the admissions office gets bamboozled or takes a risk. The one case I knew personally could write code decently well compared to many Stanford grads, but couldn't handle the Caltech curriculum and would probably do poorly on a coding interview.
saagarjha 5y ago
> I don't know the US education system enough, but there are some schools out there which are much more selective than any SWE interview process. You can be guaranteed that the worst student from these top schools could nail any algorithm interview with minimal preparation. There’s a whole lot of spread at any college. Assuming a hypothetical ranking from 1-100 with 1 being unable to program or problem solve and 100 being your Jeff Dean/Fabrice Bellard/Linus Torvalds programming god of choice an average state school might give you people from 30-70 and a top school might be 40-80. Lots of smart people go to state schools and lots of idiots come out of top ones.
closeparen 5y ago
I went to a highly selective university and I certainly could not not nail any algorithm interview with minimal preparation. Algorithms is one class. It consisted mostly of proofs, a little pseudocode, zero working programs. The particular algorithms we spent a lot of time on were pretty obscure in the interview world: Gale-Shapley matching, Ford-Fulkerson max flow. The goal was never to have a wide repertoire of algorithms that you could write down on command, and certainly not anything to do with implementation.

majormajor 5y ago

Needing to hire more than just the top schools graduate is certainly a reason companies can't limit themselves to university selection processes. But that's not all that's going on here! CalTech is pretty selective as far as US schools go (6% acceptance rate). Slightly more than MIT, slightly less than Stanford. SAT score stats all in the same 1500+ range. But they're offering this course, and that makes me think that no, the worst student from these schools in the US, at least cannot nail any algorithm interview with minimal prep! And that makes sense, from a US perspective! Getting into CalTech or Stanford or MIT is about doing well at high school/early-college level material in high school, and about extracurricular activities, with a dash of being able to afford it and being told it's something you should try for. Most of that high school curriculum - even most college-level CS material - isn't super applicable to a software engineering job. It's heavier on memorization (we have google for that!) and it's heavier on theory than on creative application of things. I might argue that any test or course where the answers to the exams come straight out of the textbook isn't worth as much as it used to be, since we've got Google and SO and all the books too! That's a big part of why a lot of these whiteboard interviews aren't simply "write out Dijkstra's algorithm" (boring, textbook!) but are about seeing if you can figure out how to use apply CS in a situation where the way the problem maps to the algorithm isn't immediately obvious. Creative work has a long history of not aligning well with traditional US university admissions criteria and evaluations.

yodsanklai 5y ago
> But they're offering this course, and that makes me think that no, the worst student from these schools in the US, at least cannot nail any algorithm interview with minimal prep! I think it's impossible to nail these interviews without minimal prep. It's very specific, and every candidates are well-prepared, many of them have done 500+ leetcode questions before interviewing. Regarding the US universities, I'm not sure but I wonder if some students can somehow compensate a lack of academic mathematics excellence with extracurricular activities, or being rich or from a minority. Maybe companies want to filter those out? As for creativity, leetcode interview questions is all about preparation. There's little creativity.
- saagarjha 5y ago
  > I think it's impossible to nail these interviews without minimal prep. It's very specific, and every candidates are well-prepared, many of them have done 500+ leetcode questions before interviewing. It’s definitely possible. Mostly you’d want to learn your algorithms well in college and continue to exercise them in your work. The rest of the interview is a lot about how you present yourself, which is mostly along the lines of “work out the problems out loud and ask questions”. Also, FWIW, I’ve had a decent amount of opportunities for creativity on Leetcode-style questions. When permitted I often pick the language that I feel would make the solution simpler or easier to understand. When doing things like linked list or graph traversal you’re often asked to define the datastructure you’ll be using, which is a good chance to use different types of polymorphism or algebraic datatypes that can make your task easier. Even if you’re just churning out for loops, a lot of them can be replaced with functional methods or selective application of interesting utilities such as array rotation.
  - yodsanklai 5y ago
    > Mostly you’d want to learn your algorithms well in college and continue to exercise them in your work. The rest of the interview is a lot about how you present yourself, which is mostly along the lines of “work out the problems out loud and ask questions”. Not my experience. When I interviewed at Google for a senior position, I mostly had difficult questions with little interaction with the interviewer. Before my preparation, I could solve all the questions within let say a couple of hours and I knew very well all the algorithms. But that's not what's expected to pass. You're competing with people who have been working very hard on this style of interviews and you need to be among the best. You're expected to find the answer to a couple of questions within a 40 min. That includes finding the solution, writing the code (not pseudo-code), testing your solution and discuss complexity. Thinking 15min + sketching some pseudo code is not enough, or maybe for a particularly hard problem.
thaumasiotes 5y ago
> But they're offering this course, and that makes me think that no, the worst student from these schools in the US, at least cannot nail any algorithm interview with minimal prep! My take on this is that the problem is misaligned expectations. I failed Google's algorithmic interview round twice under the assumption that when the interviewer asked me a question, the point was to see if I could come up with the answer. But that isn't true. The interview questions are chosen with the expectation that candidates cannot come up with the answer themselves. Instead, the point is for the candidate to cold-read the answer from the interviewer. When a test -- or a computer -- asks you how to do something, it won't care or even realize that you spent ten minutes thinking about the problem before starting to write a solution down. But an interviewer will fail you for doing that. That insight was enough to pass the interview round. And it also suggests that a course in "how to pass an interview" should boost CalTech grads' passing rates to nearly 100%, because all they need is to be informed of the "proper" technique.

SteveDR 5y ago

> You can be guaranteed that the worst student from these top schools could nail any algorithm interview with minimal preparation. Considering that CalTech offers this course, they must be realllyyyy misguided, or you’re talking about schools that are far more selective than CalTech (7% acceptance rate).

yodsanklai 5y ago
I don't know what it takes to study at CalTech. But I nailed the interviews at FB and Google and there's no way I could have studied maths at Cambridge for instance. Leetcode is just a matter of solving enough problems so that you can do them almost out of memory on the white board. The curriculum is basically algorithms at undergraduate level. Seriously, it's easy.

SamReidHughes 5y ago

Caltech does get the occasional bad admit, where the admissions office gets bamboozled or takes a risk. The one case I knew personally could write code decently well compared to many Stanford grads, but couldn't handle the Caltech curriculum and would probably do poorly on a coding interview.

saagarjha 5y ago

> I don't know the US education system enough, but there are some schools out there which are much more selective than any SWE interview process. You can be guaranteed that the worst student from these top schools could nail any algorithm interview with minimal preparation. There’s a whole lot of spread at any college. Assuming a hypothetical ranking from 1-100 with 1 being unable to program or problem solve and 100 being your Jeff Dean/Fabrice Bellard/Linus Torvalds programming god of choice an average state school might give you people from 30-70 and a top school might be 40-80. Lots of smart people go to state schools and lots of idiots come out of top ones.

closeparen 5y ago

I went to a highly selective university and I certainly could not not nail any algorithm interview with minimal preparation. Algorithms is one class. It consisted mostly of proofs, a little pseudocode, zero working programs. The particular algorithms we spent a lot of time on were pretty obscure in the interview world: Gale-Shapley matching, Ford-Fulkerson max flow. The goal was never to have a wide repertoire of algorithms that you could write down on command, and certainly not anything to do with implementation.