An update on Signal Data Science (an intensive data science training program)

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.

While I understand Fluttershy's concerns, overall I was quite happy with the program. I think many people could benefit from it, and I would expect things to go better in a number of ways for the second cohort.

I think one of the problems we did have was that the pace of the program was simply too quick for some of the participants. This shouldn't be an issue for the second cohort, since it is intended to last 12 weeks.

Similarly, it was somewhat unpleasant to have the program taking place in the same house where many of the participants were living. I don't blame Jonah and Robert for this, since at the beginning I thought it would be more convenient this way myself, but it didn't turn out that way. However, my understanding is that there will be separate office space for the second cohort, which will be a big improvement.

I think it's going too far to say that the program is "effectively self-directed," but it's true that there was less structure imposed than some would expect, and that a good part of the benefit came from personal study. In this sense, a more established bootcamp might be better for people who have somewhat less self discipline, but as Gentzel points out, there are also specific advantages to this one.

I was one of the students in the first cohort of Signal Data Science. I had a very positive experience with the program--so much so that I decided to turn down looking for $100k+ data science jobs in the Bay Area to join Signal as an assistant instructor, because I believe in what Jonah and Robert are doing and want others to have the same extraordinary experience that I did. Now that I'm working for Signal, what I say about the program should be taken with a grain of salt, but I feel that it's important to share my experience.

To put my reflections in context: Coming into this program, I was very disillusioned with structured education, having had extremely negative experiences in university. (I found the coursework overly structured, onerous, and intellectually unstimulating.) However, prior to the beginning of Signal, I had positive opinions of both Jonah and Robert (they were both friends of friends), so I decided that it might be worth giving the program a try. Within the very first week of instruction, I was already amazed by the speed at which I was learning new material, the ease with which I was picking up R, and how effortless and enjoyable the whole experience was--in stark contrast to all of my previous experiences with structured education.

I was very impressed by both the breadth and the depth of the knowledge of the instructor and the TA (Jonah Sinick and Sam Eisenstat). Although I had done multiple research internships in college, all of which contained at least some tangential relation to data science and statistical techniques and three of which were highly quantitative in nature, they were able to offer me new insights even in areas where I had domain-specific knowledge and training (e.g. in the field of cognitive genomics). They were always available to help me when I got stuck and always acted congenially and professionally. Also, they were able to point me in a number of very fruitful directions for projects and further study, which I pursued to great benefit.

I also benefited greatly from the voluntary pair-programming structure of the program. At the beginning, I wasn't confident in my knowledge of R, but I was paired up with someone who had substantial past experience programming in R. In that single day, I learned more R than I did spending hours working through the R labs in Introduction to Statistical Learning. Afterward, I was similarly able to transmit my newfound expertise to other students, and finally, when I got started on my own projects and on days when I preferred to work independently, I was free to work by myself.

Lastly, there were interview and resume prep sessions every weekend with Robert, which helped me immensely. I still recall how, on the very first Saturday, we started out doing nontechnical interview prep: I stammered in my responses to the example questions and gave uncertain, incomplete responses. I was a total mess. And I still recall how, after an entire intense afternoon of practice (both with other students and with instructors), I was able to answer nontechnical interview questions confidently and fluently, as if I had been practicing these replies for years. I was astounded by the progress I had made in just five or six hours--and I can say the same about all of the Saturday interview prep sessions. It's very clear to me that Robert is an expert in interviewing and the complex dynamics of the job search.

As for the logistics of the program, I was generally happy with how Signal handled things. In particular, the bootcamp was willing to find housing to accommodate students, which is a service that no other bootcamp provides for its students--meaning that I didn't have to worry at all about trying to figure out where I would be living in Berkeley even though I was flying in from Seattle. To be sure, there were certain fixed costs that were unavoidable on account of the cohort being the first cohort, ever, of Signal Data Science, e.g. having to put together furniture for the house like beds and tables--but it was pretty clear to me going in that there was going to be stuff like that which just had to be taken care of. On balance, after considering the opportunity cost of finding and managing housing for students as well as the time saved on my own end, I definitely got an amazing deal on the rent. Of course, living in the same house with other motivated and intelligent students came with its own social and intellectual benefits as well. :-)

Overall, I would enthusiastically recommend the program to a friend. In fact, I have already been doing so to many people I know--because I want my friends to have the same amazing time here that I had!

Since I've talked to several of the people involved (Jonah and two students), and I'm a data scientist, I figured I should weigh in.

It seems to me like data science, like programming, is mostly about thinking clearly, and so it's in some sense unsurprising that people could be trained to do it quickly, assuming that they start off thinking clearly and just need to learn specific techniques. But while this is somewhat true for programming, it seems less true for math (and statistics as a branch of math)--I would not expect, say, actuarial boot camps to be a reasonable thing.

My standard bootcamp advice also applies--the value of a programming bootcamp, for example, is that it gets you from 0 job offers to 1 job offer, and so it may be worthwhile to do the interview process first, and ensure that you actually need a bootcamp to get hired. (This is somewhat dangerous since most companies will only look at candidates once per year, and so if you don't get hired, do a three month bootcamp, and then try to get hired again, you may need to wait ~9 months.)

It's also worth pointing out that the better employers are mostly looking for quantitative PhD types; I was recently approached on LinkedIn by someone who is about to graduate from a one-year masters program focused on data science and I was reluctant to recommend that he apply to where I work because it was unclear he would pass either our HR filters or our technical interview process. (And if I'm reluctant to recommend him, I'm also reluctant to recommend anyone from Signal.)

But that said, there are a bunch of companies out there who need some sort of data science work, and there are multiple gradations of it. Lots of companies have many more 'analyst' roles than they do 'scientist' roles, and I would expect people who can make it through Signal to have a good shot at those. (Similar bootcamps boast high placement rates, but if you look at the sort of roles they mention, many of them are 'data analyst' or 'software engineer' roles that I would be reluctant to call "data science" but that may be because I take a fairly narrow view of the term, as a job description. If a software engineer goes to a bootcamp and gets a software engineer position afterwards, it's not clear whether or not that reflects a success.)

Be aware that the instruction will be fairly self-driven, and that you'll mostly get instruction on the level of "this is how you would find that answer" instead of "this is the answer," and if you're looking for the latter you should probably look elsewhere. (For example, instead of fixing a particular error, expect to be taught how to read error messages and Google them, which is overall a more useful answer.)

Also be aware, as mentioned earlier, that the value of a bootcamp is getting people from 0 offers to 1 offer, and until the first cohort has finished their job search, how effective Signal is at that remains unknown.

TL;DR: I can't feel comfortable recommending Signal until they have a proven track record, but talking with people involved has put my worries to rest. If you think you'd be a good fit for the environment at Signal (and the best way to figure this out is probably talking with Jonah) and you estimate the improvement in career prospects is worth the cost, go for it.

How many students have found work in data science (so far), what problems are they solving now, and what are the associated companies/cities/salaries?

"We're planning another one in Berkeley from May 2nd – July 24th."

Is that June 24th?