Jonah and Robert have good intentions, and I was actually happy with the weekly interview sessions taught by Robert. However, I had a poor experience with this program overall. I’ll list some observations from my experience as a member of the first cohort below.
First, this program is effectively self-directed; most of the time, neither the TA nor the instructor were available. When they were, asking them questions was incredibly difficult due to their lack of familiarity with the material they were supposed to be teaching. To be sure, both the instructor and the TA were intelligent people—the problem was just that they knew lots of math, but not very much data science.
Second, there were lots of communication issues between the instructors and the students. I really do not want to give specific examples, since I don’t want to say something that would reflect so poorly on the LessWrong community. However, I assure you that this was an incredibly large issue.
Lastly, everything about this program was disorganized. Several of us paid for housing through the program, which ended up not being available as soon as we’d been told that it would be. The furniture in the office space we used was set up by participants because Signal was too disorganized to have it set up before we were supposed to start using it. The fact that only two out of twelve students pair programmed together on an average day was also due to a lack of organization of the part of the instructors.
Jonah and Robert clearly worked very hard to make this program what it was, but attending was still a bad experience for me. If you already have a background in software engineering and want to pay $8,000 to teach yourself data science alongside other students who are doing the same, this program is a good fit for you. Otherwise, consider attending a longer, more established program, like Zipfian Academy that actually uses pair programming and has instructors available to answer questions.
I’m sorry that you had such a negative experience at the bootcamp. It isn’t for everyone, and I don’t think I would recommend Signal to people who are looking for what you wanted out of the bootcamp. I wish that it had been otherwise; nevertheless, I want to thank you for sharing your thoughts in such an honest and frank manner.
However, I think it’s important to separate out your own experience from the experiences of other students. In many cases, including my own, they were radically different.
I’m not personally comfortable with your comment insofar as it seems to implicitly speak for all the students in the bootcamp. I know that my life improved greatly because I was able to come down here, but if I were a prospective student now, your comment might have dissuaded me from coming. For that reason, I believe it’s useful to be more specific in your epistemic claims here—it may very well be true that the program is unsuitable for people in your reference class, but I think it would be bad if that fact ended up discouraging applicants for whom the program would be a great fit.
I’m surprised that you think the instructors don’t know very much data science. On top of having a strong command of the underlying mathematics, Jonah and Sam were able to teach me things that aren’t explained in textbooks, like the intuitive explanation of why the sum of squared error is minimized in linear regression and the fundamental importance of dimensionality reduction techniques. The numerous discussions I’ve had with Jonah have shaped my intellectual growth generally and made clear to me many of the more obscure aspects of data science specifically—for instance, I had been reading a couple papers on boosting out of personal interest and offhandedly made a remark to Jonah about something I found fascinating, and he was able to immediately understand and rectify a minor point of confusion I had been having.
Again, your perception of the instructors’ competencies may have been the result of a mismatch between the sort of environment the program was trying to offer and the sort of environment you were hoping for. I wish that your experience could have been as positive as mine and hope you’re able to find what you’re looking for in the future. Based on your feedback, Signal is giving higher priority to giving prospective students a clear sense for the program’s environment so that they’re are well equipped to make informed decisions.
Again, your perception of the instructors’ competencies may have been the result of a mismatch between the sort of environment the program was trying to offer and the sort of environment you were hoping for.
This actually sounds about right.
I think that I care more about job-preparedness, potential for impact, and preparing people for being able to earn-to-give or do direct EA work. I think that Robert also cares about those things, which is why I liked his weekly interview sessions, as I mentioned above.
However, I didn’t get the sense that Jonah, the instructor for the first cohort, really cared about these things quite as much. Jonah strikes me as an intelligent individual whose heart is in academia, rather than in data science or industry. This was quite problematic, because, among other reasons, it meant that even his explanations of grittier things were too focused on the big picture, and too spare on details for some people to figure out how to actually do the thing at all. It also skewed the distribution of topics taught away from things relevant to industry.
Could you please elaborate with specific examples of times when Jonah’s explanations were too abstract and not sufficiently practical?
This will be useful information for us, because we certainly want to identify areas in which our curriculum needs further improvement. My personal recollection of Jonah’s lectures is that they involved a lot of example code, visualization, back-and-forth Q&A, and interactive exploration of real datasetsin lieu of presenting, say, abstract mathematical proofs.
It also skewed the distribution of topics taught away from things relevant to industry.
Along similar lines, what are some specific topics that you think were neglected in favor of more abstract but less applicable material?
I’m particularly interested in what material you thought was overemphasized in the curriculum—my impression is that all of the topics covered were very fundamental to data science as a whole. While one can express a valid preference for certain fundamental topics over others, I would be hard-pressed to say that any of the topics covered in the Signal curriculum weren’t extremely industry-relevant.
I’ve already had versions of this conversation with Robert and Jonah in person, but I’ll reiterate a few things I shared with them here, since you asked politely. Also, this conversation is becoming aversive to me, so it will become increasingly difficult for me to respond to your comments as we get farther and farther down this comment chain.
specific examples of times when Jonah’s explanations were too abstract and not sufficiently practical?
There were actually multiple times during the first couple weeks when I (or my partner and I) would spend 4+ hours trying to fix one particular line of code, and Jonah would give big-picture answers about e.g. how linear regression worked in theory, when what I’d asked for were specific suggestions on how to fix that line of code. This led me to giving up on asking Jonah for help after long enough.
what are some specific topics that you think were neglected in favor of more abstract but less applicable material?
Intermediate and advanced SQL, practice of certain social skills (e.g. handshakes, being interested in your interviewer, and other interview-relevant social skills), and possibly nonlinear models.
Thanks for the written feedback (which adds to what I had gleaned in person).
There were actually multiple times during the first couple weeks when I (or my partner and I) would spend 4+ hours trying to fix one particular line of code, and Jonah would give big-picture answers about e.g. how linear regression worked in theory, when what I’d asked for were specific suggestions on how to fix that line of code. This led me to giving up on asking Jonah for help after long enough.
I think that what happened here is me having misunderstood what you were asking for, rather than any disinclination on my part to help you with individual lines of code. I will take this feedback into account.
Intermediate and advanced SQL, practice of certain social skills (e.g. handshakes, being interested in your interviewer, and other interview-relevant social skills), and possibly nonlinear models.
This is helpful detail regarding what you were looking for. Which topics would you have preferred to have been been dropped in favor of these?
I (or my partner and I) would spend 4+ hours trying to fix one particular line of code, and Jonah would give big-picture answers about e.g. how linear regression worked in theory
For context, what was your programming ability before you started the course? It seems strange to spend 4 hours getting (one line of) linear regression to work, but it also seems strange for an instructor to give a vague answer to something so basic, unless he was using the “Socratic Method”?
That’s a funny comment. It does exactly the same thing twice: Please tell us where we didn’t do too well, oh, and you are COMPLETELY WRONG because we did everything very well.
In context, it makes a lot of sense for him to do that. He’s working for Signal now, so presumably is interested in how to improve the program, and he was a participant at the same time as Fluttershy, so he got an impression of the program as a participant.
In context, it makes a lot of sense for him to do that.
No, it doesn’t. Continuing with the charitable interpretation, wearing these two hats at the same time is… difficult. Either he, as an employee of Signal, is genuinely interested in feedback, or he as a participant thinks Fluttershy is all wrong and making shit up because it was perfect for andrewjho (here he, of course, committs the typical mind fallacy, but that’s a minor issue at this point).
That’s OK, this is not a requirement :-/ Fluttershy is clearly speaking from his/her personal point of view. If your experience was different, that’s fine but that does not devalue the experience of other people.
it would be bad if that fact ended up discouraging applicants for whom the program would be a great fit.
The situation is symmetric: it would also be bad if some fact ended up encouraging applicants for whom the program would be a bad fit.
I think it is better to assess personal fit for the bootcamp. There are a lot of advantages I think you can get from the program that would be difficult to acquire quickly on your own.
Aside from lectures, a lot of the program was self study, including a lot of my most productive time at the bootcamp, but there
was normally the option to get help, and it was this help, advice, and strategy that I think made the program far more productive than what I would have done on my own, or in another bootcamp for that matter (I am under the impression longer bootcamps may develop specific skills at using the software better, but they don’t convey nearly the same level of conceptual understanding of statistics in data science, and likewise there are many types of mistakes graduates of other programs will make that graduates of Signal’s cohort have been taught not to). When there was not the option to get help, I usually shifted my work schedule and it wasn’t much of a problem: there are so many projects to work on, that there was almost always something productive to work on where I wouldn’t get stuck (optional exercises on prior projects or making prior projects better). I can see this being very frustrating for some people though, as getting stuck and not having immediate feedback interrupts flow.
Many of the organizational problems didn’t seem to really be problems, and seemed more like differences which are good for some and not for others. Pair programming was not always optimal due to the large degree of differences between students. It wouldn’t have made sense for everyone to pair program since it would have been holding back some of the faster students. A more rigid structure would have helped people who were less naturally self directed/focused though. Organizational problems that happened with respect to the first cohort in terms of setting up (furniture, internet, whiteboards, etc.) are unlikely to be problems for future cohorts now that the instructors have learned from experience and have a place set up. The first cohort took the risks and costs of such things, which later cohorts probably won’t have to worry about.
This is not like other bootcamps, it is less expensive, more individually focused rather than having the entire group doing all the same curriculum, and there are a bunch of rationalists iteratively helping you decide which jobs are best to apply to, who can network you into what position, and which skills actually matter most for aiming for the specific jobs you are aimed at. I don’t expect you to be able to have the same opportunities at a normal bootcamp, but a normal bootcamp is probably also lower risk if you don’t trust yourself to make things work out (other programs may have quizzes where they throw you out if you fail, and essentially force you to remain focused, with Signal you are more in control yourself, and can take time off to apply to jobs.
I think it is better to assess personal fit for the bootcamp.
Yes, this is correct.
Pair programming was not always optimal due to the large degree of differences between students.
You’re good at socializing and very pleasant to be around, and didn’t generally had problems finding pair programming partners when you wanted to work with someone. I’m shy, and couldn’t even find anyone who wanted to pair program with me most days, even though I was generally interested in working with others, and often asked Jonah or other students if anyone wanted to work together.
I don’t intend this as a demand, but you may wish to edit your top comment.
As it stands, the first line of the first comment on this post is “Avoid this program.” Based on the comments in this thread it sounds like you think the program might be a good fit for some people.
Yet another student reporting in with a highly positive experience!
I personally felt Jonah knew data science really well. In addition to solid theoretical understanding of the mathematics, he was extremely proficient with using R and statistics to dissect and analyze complex real world data sets. At the beginning, he provided virtually step by step guidance on analysis and interpretation of several data sets using a variety of techniques and packages in R. The program only became more self-directed over time because the students, with diverse backgrounds and experiences, focused on different areas and progressed at different rates. Even then, I felt Jonah was very actively providing individually tailored guidance for the students on their learning and projects.
If you have strong fundamentals and are capable of getting up to speed on R quickly, then you can get a lot out of this program as I did. It provided me the basic knowledge and practice on using programming/statistics/machine learning to find patterns in real world data and make useful, meaningful statistical predictions from them. After this program, I know more or less how to approach data science, work independently, and fill whatever gaps I have. I would highly recommend this program to a self-motivated, mathematically minded person looking for a job in data science.
A lot of us came in with very different levels of knowledge and a big factor that determined success was whether or not you had experience with programming beforehand. To be fair a lot of non-programmers ended up being stars, like the student who made the word cloud, but they had to work a lot harder.
Avoid this program.
Jonah and Robert have good intentions, and I was actually happy with the weekly interview sessions taught by Robert. However, I had a poor experience with this program overall. I’ll list some observations from my experience as a member of the first cohort below.
First, this program is effectively self-directed; most of the time, neither the TA nor the instructor were available. When they were, asking them questions was incredibly difficult due to their lack of familiarity with the material they were supposed to be teaching. To be sure, both the instructor and the TA were intelligent people—the problem was just that they knew lots of math, but not very much data science.
Second, there were lots of communication issues between the instructors and the students. I really do not want to give specific examples, since I don’t want to say something that would reflect so poorly on the LessWrong community. However, I assure you that this was an incredibly large issue.
Lastly, everything about this program was disorganized. Several of us paid for housing through the program, which ended up not being available as soon as we’d been told that it would be. The furniture in the office space we used was set up by participants because Signal was too disorganized to have it set up before we were supposed to start using it. The fact that only two out of twelve students pair programmed together on an average day was also due to a lack of organization of the part of the instructors.
Jonah and Robert clearly worked very hard to make this program what it was, but attending was still a bad experience for me. If you already have a background in software engineering and want to pay $8,000 to teach yourself data science alongside other students who are doing the same, this program is a good fit for you. Otherwise, consider attending a longer, more established program, like Zipfian Academy that actually uses pair programming and has instructors available to answer questions.
I’m sorry that you had such a negative experience at the bootcamp. It isn’t for everyone, and I don’t think I would recommend Signal to people who are looking for what you wanted out of the bootcamp. I wish that it had been otherwise; nevertheless, I want to thank you for sharing your thoughts in such an honest and frank manner.
However, I think it’s important to separate out your own experience from the experiences of other students. In many cases, including my own, they were radically different.
I’m not personally comfortable with your comment insofar as it seems to implicitly speak for all the students in the bootcamp. I know that my life improved greatly because I was able to come down here, but if I were a prospective student now, your comment might have dissuaded me from coming. For that reason, I believe it’s useful to be more specific in your epistemic claims here—it may very well be true that the program is unsuitable for people in your reference class, but I think it would be bad if that fact ended up discouraging applicants for whom the program would be a great fit.
I’m surprised that you think the instructors don’t know very much data science. On top of having a strong command of the underlying mathematics, Jonah and Sam were able to teach me things that aren’t explained in textbooks, like the intuitive explanation of why the sum of squared error is minimized in linear regression and the fundamental importance of dimensionality reduction techniques. The numerous discussions I’ve had with Jonah have shaped my intellectual growth generally and made clear to me many of the more obscure aspects of data science specifically—for instance, I had been reading a couple papers on boosting out of personal interest and offhandedly made a remark to Jonah about something I found fascinating, and he was able to immediately understand and rectify a minor point of confusion I had been having.
Again, your perception of the instructors’ competencies may have been the result of a mismatch between the sort of environment the program was trying to offer and the sort of environment you were hoping for. I wish that your experience could have been as positive as mine and hope you’re able to find what you’re looking for in the future. Based on your feedback, Signal is giving higher priority to giving prospective students a clear sense for the program’s environment so that they’re are well equipped to make informed decisions.
This actually sounds about right.
I think that I care more about job-preparedness, potential for impact, and preparing people for being able to earn-to-give or do direct EA work. I think that Robert also cares about those things, which is why I liked his weekly interview sessions, as I mentioned above.
However, I didn’t get the sense that Jonah, the instructor for the first cohort, really cared about these things quite as much. Jonah strikes me as an intelligent individual whose heart is in academia, rather than in data science or industry. This was quite problematic, because, among other reasons, it meant that even his explanations of grittier things were too focused on the big picture, and too spare on details for some people to figure out how to actually do the thing at all. It also skewed the distribution of topics taught away from things relevant to industry.
Could you please elaborate with specific examples of times when Jonah’s explanations were too abstract and not sufficiently practical?
This will be useful information for us, because we certainly want to identify areas in which our curriculum needs further improvement. My personal recollection of Jonah’s lectures is that they involved a lot of example code, visualization, back-and-forth Q&A, and interactive exploration of real datasets in lieu of presenting, say, abstract mathematical proofs.
Along similar lines, what are some specific topics that you think were neglected in favor of more abstract but less applicable material?
I’m particularly interested in what material you thought was overemphasized in the curriculum—my impression is that all of the topics covered were very fundamental to data science as a whole. While one can express a valid preference for certain fundamental topics over others, I would be hard-pressed to say that any of the topics covered in the Signal curriculum weren’t extremely industry-relevant.
I’ve already had versions of this conversation with Robert and Jonah in person, but I’ll reiterate a few things I shared with them here, since you asked politely. Also, this conversation is becoming aversive to me, so it will become increasingly difficult for me to respond to your comments as we get farther and farther down this comment chain.
There were actually multiple times during the first couple weeks when I (or my partner and I) would spend 4+ hours trying to fix one particular line of code, and Jonah would give big-picture answers about e.g. how linear regression worked in theory, when what I’d asked for were specific suggestions on how to fix that line of code. This led me to giving up on asking Jonah for help after long enough.
Intermediate and advanced SQL, practice of certain social skills (e.g. handshakes, being interested in your interviewer, and other interview-relevant social skills), and possibly nonlinear models.
Thanks for the written feedback (which adds to what I had gleaned in person).
I think that what happened here is me having misunderstood what you were asking for, rather than any disinclination on my part to help you with individual lines of code. I will take this feedback into account.
This is helpful detail regarding what you were looking for. Which topics would you have preferred to have been been dropped in favor of these?
For context, what was your programming ability before you started the course? It seems strange to spend 4 hours getting (one line of) linear regression to work, but it also seems strange for an instructor to give a vague answer to something so basic, unless he was using the “Socratic Method”?
That’s a funny comment. It does exactly the same thing twice: Please tell us where we didn’t do too well, oh, and you are COMPLETELY WRONG because we did everything very well.
In context, it makes a lot of sense for him to do that. He’s working for Signal now, so presumably is interested in how to improve the program, and he was a participant at the same time as Fluttershy, so he got an impression of the program as a participant.
No, it doesn’t. Continuing with the charitable interpretation, wearing these two hats at the same time is… difficult. Either he, as an employee of Signal, is genuinely interested in feedback, or he as a participant thinks Fluttershy is all wrong and making shit up because it was perfect for andrewjho (here he, of course, committs the typical mind fallacy, but that’s a minor issue at this point).
That’s OK, this is not a requirement :-/ Fluttershy is clearly speaking from his/her personal point of view. If your experience was different, that’s fine but that does not devalue the experience of other people.
The situation is symmetric: it would also be bad if some fact ended up encouraging applicants for whom the program would be a bad fit.
I think it is better to assess personal fit for the bootcamp. There are a lot of advantages I think you can get from the program that would be difficult to acquire quickly on your own.
Aside from lectures, a lot of the program was self study, including a lot of my most productive time at the bootcamp, but there was normally the option to get help, and it was this help, advice, and strategy that I think made the program far more productive than what I would have done on my own, or in another bootcamp for that matter (I am under the impression longer bootcamps may develop specific skills at using the software better, but they don’t convey nearly the same level of conceptual understanding of statistics in data science, and likewise there are many types of mistakes graduates of other programs will make that graduates of Signal’s cohort have been taught not to). When there was not the option to get help, I usually shifted my work schedule and it wasn’t much of a problem: there are so many projects to work on, that there was almost always something productive to work on where I wouldn’t get stuck (optional exercises on prior projects or making prior projects better). I can see this being very frustrating for some people though, as getting stuck and not having immediate feedback interrupts flow.
Many of the organizational problems didn’t seem to really be problems, and seemed more like differences which are good for some and not for others. Pair programming was not always optimal due to the large degree of differences between students. It wouldn’t have made sense for everyone to pair program since it would have been holding back some of the faster students. A more rigid structure would have helped people who were less naturally self directed/focused though. Organizational problems that happened with respect to the first cohort in terms of setting up (furniture, internet, whiteboards, etc.) are unlikely to be problems for future cohorts now that the instructors have learned from experience and have a place set up. The first cohort took the risks and costs of such things, which later cohorts probably won’t have to worry about.
This is not like other bootcamps, it is less expensive, more individually focused rather than having the entire group doing all the same curriculum, and there are a bunch of rationalists iteratively helping you decide which jobs are best to apply to, who can network you into what position, and which skills actually matter most for aiming for the specific jobs you are aimed at. I don’t expect you to be able to have the same opportunities at a normal bootcamp, but a normal bootcamp is probably also lower risk if you don’t trust yourself to make things work out (other programs may have quizzes where they throw you out if you fail, and essentially force you to remain focused, with Signal you are more in control yourself, and can take time off to apply to jobs.
Yes, this is correct.
You’re good at socializing and very pleasant to be around, and didn’t generally had problems finding pair programming partners when you wanted to work with someone. I’m shy, and couldn’t even find anyone who wanted to pair program with me most days, even though I was generally interested in working with others, and often asked Jonah or other students if anyone wanted to work together.
I don’t intend this as a demand, but you may wish to edit your top comment.
As it stands, the first line of the first comment on this post is “Avoid this program.” Based on the comments in this thread it sounds like you think the program might be a good fit for some people.
Yet another student reporting in with a highly positive experience!
I personally felt Jonah knew data science really well. In addition to solid theoretical understanding of the mathematics, he was extremely proficient with using R and statistics to dissect and analyze complex real world data sets. At the beginning, he provided virtually step by step guidance on analysis and interpretation of several data sets using a variety of techniques and packages in R. The program only became more self-directed over time because the students, with diverse backgrounds and experiences, focused on different areas and progressed at different rates. Even then, I felt Jonah was very actively providing individually tailored guidance for the students on their learning and projects.
If you have strong fundamentals and are capable of getting up to speed on R quickly, then you can get a lot out of this program as I did. It provided me the basic knowledge and practice on using programming/statistics/machine learning to find patterns in real world data and make useful, meaningful statistical predictions from them. After this program, I know more or less how to approach data science, work independently, and fill whatever gaps I have. I would highly recommend this program to a self-motivated, mathematically minded person looking for a job in data science.
A lot of us came in with very different levels of knowledge and a big factor that determined success was whether or not you had experience with programming beforehand. To be fair a lot of non-programmers ended up being stars, like the student who made the word cloud, but they had to work a lot harder.
Just commenting as I have a new review up that disagrees with this comment.