By - zoule
What kind of experience does it take to get in?
I'm a STEM PhD and have spent the past year really interested in data and data analysis. I've taken all kinds of online classes and started following blogs etc., but I don't have any experience. I am not in a genomics lab, so I'll never get my name on a paper with fancy data analysis.
My current strategy is to keep learning and get to the point where I can do some interesting data analysis/visualizations, and I guess get them online somewhere. So, is anybody really impressed by these blogs with random visualizations that keep popping up everywhere? How do I get actual experience without going back to school? A data science bootcamp really seems ideal for me. I'll know when I get to the point that I can handle it without embarrassing myself; how will I convince everybody else?
What does it take to get in? Python, stats, basic modeling. I completed Learn Python the Hard Way, already had a good feel for stats/probability, and went through many of Stanford's ML videos. With a little self study, it sounds like you'd be ready for the course. If you already have coding experience, you might be ready right now. Apply and get access to the first coding challenges!
I'm impressed by random blogs! But I'm a student, not a hiring manager. The program has encouraged us to blog- we've heard a number of examples where having a blog has helped past graduates get hired. It showcases your skills, ability to present technical information/communicate, and personality.
Actual experience without going back to school? Hmm. I'd consider building a portfolio and github repository. You could work on kaggle challenges, or develop your own projects from found data sets. Many cities across the US have Open Data data sets, and while my experience is limited to the bay area, there seem to be lots of volunteer opportunities where you can get involved on projects. You could go to data science meet ups- especially for networking.
For anyone interested, here's a series of blog posts (not mine) about the whole 12-week experience: http://yet-another-data-blog.blogspot.ie/2014/04/zipfian-academy-all-12-weeks.html
Psh - get cracking on your project over doing an AMA! Your code wont write itself! ;)
Source: was in cohort 6
I know youuuuu ;)
Talking about the program is good stress relief!
Thanks for doing this! This was very well-timed as I am right on the verge of making the decision to apply to Zipfian with minimal experience and no formal background.
Some questions I have are:
Did you have any projects, final or in process, that you were able to link to in your application?
Outside of the basic needs you mentioned (python, stats/probability, ML), what additional items do you recommend for someone who has free time beyond just the basic MOOCs?
I am currently working as a data analyst and I have the liberty to pursue data science projects at my job for a few hours a day. However, I have also considered quitting my job and dedicating myself full time to getting in to Zipfian. Given what you know about the application process, what would you recommend?
I had no coding/data science projects for my application, nothing on github, and had only taught myself Python for the interviews. I was a more math-heavy applicant, and focused my study on coding while working full time. That worked great for me!
The more python and coding experience you have, the better off you'll be. Have you taken an Algorithms course? That seems to be the most common recommendation, and something I'm going to do as soon as I have time.
If you can start working basic kaggle competitions- even the tutorials- you'll be a step above (guesstimate) more than half your cohort. You could also learn these python tools- pandas, numpy, scipy, matplotlib, and sklearn.
Feel free to ask more here, or PM me.
Hey thanks for answering questions about the program! I'm strongly considering quitting my job and taking the galvanize bootcamp in SF.
I was looking at the alumni page, and it looks like the majority of them had a masters/PhD before attending the bootcamp, and/or had industry experience in a statistics or a high level technical field (other than some anomalies like the professional poker player).
My question is: how do people with just bachelor's degrees stand among these other very highly qualified people? From what I understand, admissions to the bootcamp is pretty selective. Would someone with a bachelors degree in Mechanical Engineering (with very little experience working in the nuclear industry) who goes through the free courses in the "data science primer" be a very competitive applicant?
Also, do you have any perspective about the long-term job prospects for graduates of the bootcamp (as opposed to the traditional applicants to data science jobs)? How seriously are graduates from zipfian/galvanize taken compared to people with PhD's in statistics and other relevant majors? I'm concerned that even after quitting my job and taking this bootcamp, I'll still be underqualified for a good math-y data science job.
Thanks again for answering these questions! I'd love to hear about your experiences after going through the hiring process as well. Good luck on your project!
Hey! Sorry, I've been swallowed by capstone-project-creation.
If you can cut the math and have the skills, I don't think the program will care about what degree you have. Getting hired is a different problem that I haven't gone through yet. But seems like there's room to shine/get hired if you can demonstrate skills regardless of degree.
Not sure about your second question at all, or at least, I'd only be able to muse on it and I should be modeling instead. I know graduates get hired with the title of Data Scientist. Beyond that...
Update time! Two weeks post hiring day.
Companies contacted: 11
Waiting to hear back from first email: 1
Companies in interview process: 6
I turned down: 2
Turned me down: 2
Phone interviews so far: 5
Scheduled in-person interviews: 2
Scheduled phone interviews: 3
All companies so far are from hiring day or through contacts of friends. I'm trying to write to two new companies a day around work. OOF!
I expect to negotiate on full hiring package- salary, equity, benefits, holidays, wfh, bonus, etc. That said I get the impression that hiring bonuses aren't unheard of, but not especially common.
Uh, I'm in final offer negotiations. Company moved really fast- I first talked to them two weeks ago.
So nervous! Fingers crossed.
I'm just a lurker that searched this sub for info about bootcamps, and I'm here to say good luck! :)
Thank youuuu. I just signed a job offer I'm thrilled about on Friday!
I am also interested in experience needed to get in, acceptance rate and the like. I come from a non-STEM field (applied linguistics with a focus on computational linguistics) but I'm earning a data science certificate online from a brick-and-mortar school. When i graduate I'll have a thesis under my belt that involves a little data science but I'm wondering if it'll be enough.
An easy answer is to check out the program's Data Science Primer: https://github.com/zipfian/data-science-primer
Your lack of data science experience won't hurt you if you have enough python, a good grasp of stats/probability, and understand the basics of modeling techniques (I used Stanford's ML videos).
I'm not sure of the exact statistic, but I believe they mentioned that they accept around 20% of applicants.
Hmmmm, thanks! I know a good deal of Python, and I'm learning R and SAS right now.
You're probably set then- I only just finished LPTHW before interviewing, and had no problems!
Oh, also, what was the timeline like? Like when did you apply, when did you hear back, when did you actually start classes?
I graduate with my masters in May but I'm going to spend spring semester trying to look for a job. I'm hoping to apply to Zipfian as a backup but I don't know about the timing.
My situation was a little weird, so I can't give you a definitive answer- but it took some time. To be safe, I'd start the application process at least two months in advance of when you'd like to start. Probably more. I started the process about a month and a half before, and the cohort I was hoping for was filled.
You could apply early and defer your acceptance to a later cohort- I don't think they'd have a problem with that, and you could ask when putting in your application. Classes start every 6-7 weeks, so lots of options.
Is there a particular industry you want to apply data science in? / what problems can greatly benefit from data science?
What kind of interview questions do you get when applying for a data science academy like Galvanize?
I'm interested in Data Science for Social Good and thinking of specializing in geospatial analysis. I don't expect to get to DSSG work right away- I'm looking to gain solid experience first and find a problem type to specialize on.
Interview questions included python challenges (more advanced than fizzbuzz but not extremely so), basic probability/stats, and modeling basics. Little to no in-person questions were asked about my experience or background.
What is job placement like?
The last study they ran had a 93% placement rate. I've seen the data (they provide it when you're accepted), and the number checks out.
I think I'm allowed to give these details...
The 93% placement rate in-field was measured for at six months post graduation. Within six months of graduation the placement rate was lower, but that included folks who had graduated within mere weeks of the study.
We have weekly talks from companies who are hiring and trying to attract talent, and even the mentors we're assigned have been hinting that they're hiring. The question seems to be not if you'll get a job- but if you'll get a more desirable mathy job.
That said, I haven't gone through hiring yet!
Were you living in the area before you started this bootcamp? Every time I hear about these I wonder where people are living while they go through them if they didn't already live in the area. The FAQ for these programs generally don't deal with practical questions like where people are supposed to live, and how they are supposed to pay bills while doing this.
Yup, I was living in the area previous to the program. Housing is... pricey right now around SF. Check out craigslist for current prices (not PadMapper, they lost craigslist data).
The transit system here can enable you to live within an hour's commute of the program and find a somewhat cheaper rent- I live in Oakland and my commute's about 45min door to door.
HOWEVER, they've also opened up programs in Seattle and Denver- if you're flexible on location, you might be able to cherry pick the city with the cheapest cost of living. Tho if you're trying to relocate to a specific area, it behooves you to attend the same.
Thanks for doing this, and congratulations on being placed in this bootcamp! I've heard about Zipfian and really wanted to apply for it as well, but I need to learn a bit of python first :)
My question is, can you elaborate on the depth of "basic modeling techniques" part of the admission requirement? As in, do we have to memorize the actual formulas/derivations of basic techniques like linear/logistic regressions, factorial analysis/PCA, or just simply know when to use which in a particular situation?
The short answer is that I studied enough to know which type of regression was which, to understand general modeling considerations, and to recognize and interpret common modeling graphs. I went through most of the overview topics in Stanford's ML course:
But note that I'm just a student and can only speak of my experience- I don't know their admission requirements. For those I can only refer you to the galvanize website.
Hey not to be too terribly much of a dick or anything but are you guys basically all Insight rejects? Is there anyone you know of in your program who got in to Insight but turned it down in favor of this?
Insight is a post-doctoral program, I have but a masters!
So no, I didn't bother applying to Insight.
About a third of my cohort has PhD's, the question might be more relevant for them...
What does your average day look like?
Also, I'm an international student here on an F1 visa for grad school. Are there many international students in the program?
Code for a half hour, lecture for an hour, code for three hours, lecture for an hour, code for three-five hours, go home, try to do the reading or catch up on something, fall asleep, repeat.
Weekends I mostly spend trying to catch up too. There's a lot of material.
There are a number of Canadians in my class- and they tell me there have been other countries represented in past classes. Not sure of visa requirements etc, you'd have to talk to the course directly.
Hey, Thank you for doing this! :D
I have a master in mechanical engineering with little programming experience mainly in Matlab. Right now I'm taking Python coding thru Code Academy and I might take some more programming via Coursera. How much programming do I need to start an application for data science bootcamp? Do I really need to have a degree in computer science?
Is there any other data science bootcamp equivalent to Zipfian not located in SF? (I live in NY)
No comp sci degree needed for Galvanize/Zipfian- I only completed Learn Python The Hard Way before interviewing. I also have an engineering masters. The more python/coding experience you have, the better off you'll be, but it sounds like you'd be fine.
Not sure about opportunities outside of the SF bay area, but a quick google search netted me this fine list that might interest you:
Is there any student in your class that came from another country pretty much just to enroll in that bootcamp? I'm asking this because it's actually what I'm planning to do.
Also, do they use R?
We've got two Canadians in my cohort that came just to enroll, and I've heard that other countries have been represented in the past! Not sure about Visas etc, you'd have to ask Galvanize/Zipfian directly.
No R, it's all Python instruction and lessons.
are you learning things you cannot have taught yourself?
Yes and no.
I could never have forced myself to do a tench as much in so little time. Having on-site help means I don't get stuck on syntax and data type errors. I'm picking up good coding/work flow habits/tricks off instructors and other students that I wouldn't get on my own. The tailored resume, interview, and presentation help is invaluable. And have I mentioned networking? That's a huge chunk of what I'm paying for.
If I had the motivation and significant time, sure I could find tutorials and teach myself the material on my own. It'd take longer, be much harder, and there wouldn't be a team devoted to getting me employed, so I'm feeling keen about the choice thus far.
Someone asked me to give a brief update on my outcomes from the experience and I can already say something.
I've been hired by Galvanize to stay on as a DSR (Data Scientist in Residence, teaching aide + personal portfolio building) through December. It's a paid position.
I also had luck at a recent networking mixer- found a company that was interested in me, and was asked to submit a full application. Waiting to see what comes of that. Networking == invaluable!
edit: Through December
How large is your cohort?
Could you break down the cost? Is there financial aid/loans?
We had around 23 students, I think the next two cohorts are closer to 18.
For financial info I'll refer you to their website. In brief loans are available, and there's some chance of partial scholarship, but I don't have details: http://www.zipfianacademy.com/faq/#scholarships
Hmm. I think that's 7% of graduates who didn't find a job in data science, not who are unemployed to this day. That said, there are folks from my cohort going into PhD programs instead of employment that would account for our 7%. I've only got anecdotal info on this one.
What are the educational backgrounds of the rest of your cohort?
Anywhere from physics or engineering doctorates to bachelors in cs. We had an actuary, a drop out from an economics doctorate program, two or three physics doctorates, the same number of engineering doctorates, and maybe ten folks who stopped with masters degrees. One recent biology doctorate. Very varied backgrounds led to a very varied range of experience within the cohort.
Follow up brief note- three weeks post graduation.
I'm done with the bootcamp for myself, but have been asked to stay on as an associate instructor through December. My classmates are interviewing, doing take-homes, and starting to get offers at the expected rates. It appears to take anywhere from 3 weeks to two months from initial contact to offer with any given company. I'll be starting my full application process mid-Oct.
Do you have any sense for which of the students are tending to get offers right away? Basically, is the cohort self-selected via the application process for success in the job market? Or are there students who are successfully making a more dramatic career change by merit of the bootcamp?
I am a mid-career professional considering the upcoming Seattle program, so this is a major consideration for me.
Offers right away seem to be going to students with the highest level of interest and activity in the job search. Second factor might be skill/confidence in the material- especially because those of us who aren't as confident aren't as active in the job search. Not sure how to separate that out. Last factor, some companies are slower than others- if you're interested in a specific place with a slow turn around time, it takes longer.
I've made a dramatic career change- from excel monkey/management trainee in a government business environment to an assistant data science instructor. Seems like it's more the norm to be swapping fields than not.
Zoule, would you mind starting a blog on your experiences/advice? I am particularly interested on the hiring statistics from your cohort, as it seems to represent a good range of experience and backgrounds. I am also interested in the longer term trajectory of your career path post-bootcamp (>1 year) and of others in your cohort.
Galvanize has been appealing to me for a few months now, but comments I've read about the exaggeration of hiring rates/salaries have discouraged me from applying. Data science interests me, but if bootcamps get much less credibility than a full graduate program (statistics/compsci/etc.), then I may choose to go that route.
Hey, thanks for asking.
I'm on the fence about this- appearances to the contrary I'm a little shy, and linking my real name to details about my current job hunt could risk me a position if I'm too frank about my preferences. And, er, this forum is an easy way to share because I can respond to user questions without having to formulate content. I'm strongly considering your suggestion though, I think it'd be a good thing for Galvanize and potentially good advertising for me.
That said, here's more of an update.
My full hiring day was last Tuesday. I had five especially great interactions with companies.* Two additional companies emailed me and asked me to apply, one of which I'm taking up on for an interview this week. I'm still reaching out to other leads that I made that day.
* One of those companies I met at a mixer through Galvanize. I completed a mini project for them (EDA and basic regression on their data set) and presented it to their team on-site. That company in particular has asked me very strongly to come on board. I'm starting the formal application process for that position tomorrow.
I'm bowled over (and a little overwhelmed) by how well it's going, I've got at least five companies to follow up with tomorrow.
Looks like things are going really well for you, congrats! I was recently accepted to Galvanize in SF and will be starting this January. While I'm excited, I'm still a little skeptical.
Have you been impressed with the overall makeup of the class? Do you think they did a good job with screening for experience/knowledge/aptitude?
How do you feel about your instructors?
I've seen a few Linkedin profiles of graduates who look like they have been job-searching for a while, any idea what the reasons may be?
Any idea what % of you cohort gets hired through the hiring day?
Lastly, any advice for preparation before the program and how to succeed during?
Congrats! Mind if I contact you in early 2016 to ask about your experiencing? I'm toying with the idea of a data science bootcamp but wouldn't be applying to one for another 7 months at the least.