Lessons Learned the Hard Way: Hacking the Data Science Interview

so lessons learned the hard way data science interviews so Katy Kent gives a wonderful wonderful presentation about the overall job process and what to expect and she's seen I think she says over a hundred students go through the process now after going through the process myself and after going through about 30 or 40 data science interviews I said hey Katy I'd love to give my perspective Heath if you think could provide value and she said yeah sure once you guys do it I said cool so this is my perspective on the data science interview job process so I've met some of you but not all of you my name is Greg kam rad I was in cohort number 6 I get confused index is at 0 and epsilon I forget what it was but anyway that was spring 2015 and right now today was actually day 1 I just got a job at Salesforce as a senior analyst on the product the data science team so after completing so after completing the job interview process these are my perspectives so what did my process look like so I sent out about a hundred and five emails a hundred of those were cold and so about five of those were warm I ended up talking about 13 recruiters a 13 different team members and so that's you know 13 different companies did five take homes I talked to six hiring managers had three on sites and ended up with one offer so Katy shows a pipeline later in her presentation and you know it she must know she's talking about because this is almost exactly what it looks like for me and I know contacting sixty three unique companies the actual interview process with 40 of them and at the time that I accepted I had ten more interviews in process so that's what I went through yeah so the first thing we had a presentation from Robin from Salesforce actually you said finding a data scientist is hard hiring one is harder it's true people always talk about how how much demand there are for data scientists and it's true you'll get yourself a lot of interviews but going through the interview process it's still tough too because it is fit the right is the right fit are you technical enough do they like a background did you catch the person you're talking two on the right day you know it's there's a lot of things that go on there and another quote that I heard that I absolutely loved was I was talking to a VP and his name was her nan and he said Greg if I wanted an XYZ data scientist and so in my from my perspective he said Greg if I wanted a PhD data scientist I'd go pick one up off the street but I don't I want somebody like you which put into perspective for me you need to find the right position for yourself because you what I tried doing is I tried molding myself to the position and you're gonna have a hard time doing that you really need to work on finding a fit so this quote if I wanted to find an exercise data scientist I would but I don't I want someone like you guys so here are the three takeaways that I'm going to focus on during the presentation organize and follow up make everyone's job easier make your job easier make the technical recruiters job easier make the team members job easier and then hard creative energy that's in lieu of the word like hack your way or hustle your way hard creative energy is the way that I like to put this those two words instead so lessons learned so I've been through the job interview process for two different roles I was in finance before this and when I was applying to finance roles I thought oh let me just apply to so many applications through the front door and one of them will hit something will end up happening and reaching out means emails or calls or something like that that's how I used to do it and I had very low success through this data science process I completely switched around so what I ended up doing was honestly through those 40 companies I talked to you 30 companies I talked to you I might have applied through the front door four three four of them five of them and the rest of those were sourced via email via calls and via networking so that's my first lesson learned is I relied heavily on emails and it worked absolutely well these are cold emails mind you and we're gonna go over the template for the cold emails too because I know that I'd be worried about that so the process so my process specifically so you got to find the companies first of all you have to make your pitch you have to find the gatekeeper and you have to make your pitch to that person and then you go through the interview process so first of all sourcing so where do I find these companies that I want to apply to and how do I stay organized throughout the process so goodie number one in the list of goodies I'm going to give you is oh that's the next slide I'm so sourcing so I had a personal big list of companies that I looked at and so we're looking about about a hundred hundred twenty companies that I liked I also contacted VCS so all of these a lot of these seeds will have talent leads if you hook up with those talent leads they have their portfolio of companies and they gave me intros to their portfolio companies and I connected with those VC's be a cold email and it worked out great and so if that's something that you're interested in that's another route that you can take alternative data scientist industries so you always hear about oh tech this data science tech that data science all at towards the end of my sourcing process I thought to myself well who else would want data science data scientist and so I was thinking you know financial or energy or agriculture or you know whatever your back your experiences in your background maybe they need data science data scientists and it's not necessarily marketed as much as a tech guys if you want to go the staffing out you know I kind of took the attitude try absolutely everything so I hooked up with a couple staffing guys and they sent my name around to I got a couple intros with that and also hacker news who's hiring so I looked up for August 2015 there was 51 data scientist jobs on Hacker News August 2015 that was huge because a lot of times it's a technical guy posting his personal email saying hey contact me and then you're I mean eat right in there already and then data towel so the goal with this is you're gonna start off with a huge huge list like anything will get thrown in there put in anything you want maybe if you will only show a slight interest and then from there you want to pluck and prune according to your interests and your experiences so here we go so key takeaway number one is organize and follow-up your an in demand data scientist and you got to keep your cool and you got to stay organized if you're talking to 30 or 40 companies there's no way you're gonna keep that on I like a small little notepad to-do list you got to stay organized and good in number one is a company list and so I'm giving you guys a big fat company listed this is a generalist right now and you can start with where you want so what I did is I went to every single one of these guys and I said hey what would I rate in this company based off of my interest level do I think it's cool do I think it's not what I want to work there and that way I can prioritize my efforts start at the top and work my way down if you have any notes you know are they abroad are they here or they you know elsewhere you're all and then if they had a certain job posting now the next thing was the email and interview tracker so this was actually my email and interview tracker on the left hand side you can see here that we have a bunch of different companies and there were names of people that are contacted and their positions now I noted the last time I contacted them and the status of that specific application to that company on the right hand side here we have the actual pipeline so I put a little conditional formatting in there in Excel and I said hey if it didn't end up working out put it in red if it's still in progress keep it in green now you can see here the summary that's it the statistics for it all this worked out for me because I was sending out multiple emails to multiple companies let me I'm sorry multiple emails to a single company and then over here we'll have all unique companies unless you're applying to two positions within the same company then I put it twice this is good e number two so I'm gonna give you guys this empty empty template and show you guys how to use this afterwards and I also was curious I mean us being data guys I was really curious about where I was in the process with everybody else and so you can see here recruiter technical and then over here said take home or hiring manager offer out and then that's how we can summarize those and you can see how you're doing right then on there so pitching how do I get the attention of the right person what can I do to reduce friction so when I say the attention of the right person the way that this works is your name has to get to the recruiter to start off the process once it's in the recruiters process they'll do a regular phone screen you just want to make sure that you get on that phone screen and they say cool thumbs up and then they pass you along to the next process so what I did is I took my company's list I went on LinkedIn and I found technical recruiters and data scientists and I got them from there you can I mean 80% chance 85% chance you're gonna guess their email address shoot them or shoot them an email shoot them a quick email pitch and I swear the response rate was a lot better than I thought it'd be if you email five technical recruiters at a company one's gonna respond now you might be asking well Greg what if that's not the right person so the thing that I learned is recruiters like referring to the recruiter friends good candidates now if you're reaching out to them in you reach out to the wrong a recruiter they're gonna be like oh let me introduce you to this buddy that I have who actually manages the team you're looking out for and then there you go is it a warm intro either the person that got forward that I got forwarded to it's it's warmer than if you were to email them in the first place or email email them cold in the first place so you have to find the gatekeeper now one of the little tips that I learned is I ended up over doing my LinkedIn credits or account and it would let me search anymore so if you go to Google and you do cite LinkedIn calm and then say whatever company you're interested in technical technical recruiter it'll pull up every all the technical recruiters at that company so that's one small thing I learned out and then when you're trying to find the gatekeeper you want to assess the size of the company if it's a huge company you got to go technical recruiters if it's a place you know 50 or under the data scientists will be managing themself a little bit more you might want to contact the data scientist directly I found I had more success contacting contacting the technical recruiters in the first place and then also when in doubt reach out so I didn't think that would rhyme in that attack that I was like okay I'll keep that but if you think about what are the outcomes of me sending this email one I never talked to them again and that's about the only bad negative one I could think of no one's gonna give you a hard time for trying it so if you hit the wrong person they don't respond who cares I mean something on your list that you trying even harder if you hit the wrong person they might forward your email if you hit the right person they might be interested now I think it might have even been Katie that said this quote to me she said you might want to focus on counting how many rejections you get actually because that just means you're trying that hard now I'm not saying go out and seek rejections I'm just going out and I'm saying go out and try a whole bunch and put out you put yourself out there or the hard creative energy and then see what you can get back from there so the goal is to get your story in the right hands now this is this is all very high-level right now we're not and when I say story we'll go over that what I mean in a second so here make everyone's job easier you get one shot if that to leave your mark make it easy on the gatekeeper if you're a technical grader you're looking at emails all day long you're gonna give ten seconds to this weird cold intro email that you saw give it you want to give a good impression have them forward it off and then have a move on or third a it's really just trying to go through the process with these guys so in your actual email pitch I found three this is this is basically the format that I used a quick intro very quick I'm talking two sentences three sentences if that my a little bit of my background a little bit about galvanize links of the program and here's small little tip number two you don't want to give a link to the home page because we're trying to reduce friction here I want to give a link to either the program course description or the program alumni now Oh Greg why would you want to give the program alumni because when they go to that page and they hover over the people they're gonna see oh this person works at stripe this person works at Facebook it's like oh shoot I don't know anything about the program but I know that these people are working there what more do you want them to know about the program I mean honestly you want them to know that the program has legitimacy and the way you do that is showing where the alumni work now the other thing finally to the smaller thing Katie said this to me and this was something I needed to get over with I did find us before and I was not a finance guy anymore you are a data scientist you embody the data scientist and if anybody tells you differently you say no you're wrong I mean I'm a data scientist know what you're talking about you take that attitude it'll be a lot more they'll take you a lot more seriously now the final project I included my final project in the email as well and nobody will actually next slide talks about final project I'll go into that more but you want to make sure it's easy to digest appeal a very very quick appeal shareable and readable now express interest to learn more hey I'm excited about the type of problems you're you guys are working on I'd love to learn more about the data team blah blah blah blah blah they love that and they'll say like okay cool and so what the goal for this is you want to have them say this person knows what they're talking about I'll forward this off to the right person see if interests there because then it becomes a warm intro to that new person and then you're already a next step in the process and so like I said I've sent out a hundred of these emails and I did a lot of a be testing it looks boring but that was my best subject line for my emails out introduction space - space my last name now it's not flashy like spam you're not grabbing for attention but when I look at it I mean maybe this is my perspective I'm a little bit intrigued Oh introduction oh you know who and honestly you want to put all of your information in this one email because you're going to get forwarded no one's gonna copy and paste their stuff no one is gonna curate a new email to somebody else and actually maybe but chances chances are you're going to get forwarded off so when you get forwarded make sure all your information is there so this goes along with the lines with making it easy on everybody else making everyone else's job easier so for the final project I for the final project when you think about things that are easy to digest visuals easier to digest and text which is much easier to digest and then code not everybody needs a web app but I highly highly highly suggest you give your final project a web presence that just means a straight-up just URL if it's easy to adjust on your github cool a dedicated URLs is like a whole suite so this person like it looks almost a little bit legitimate you know so you don't need a web app I wouldn't stress out about that but you need a web presence I would highly highly suggest that make it easy for others to adjust and then when you're promoting your final project that's I could go on for another twenty minutes about how to promote a final project and how I think it should be but these are the small things that you could do reddit data sounds beautiful data science blogs newsletter Twitter after news dead it's how they all love that stuff people are constantly searching for cool information to share to others now if you make yours easy to digest they're gonna share it all over the place and what else is really cool is that say you have a small picture or something super easy to digest you can share it on Twitter people are gonna retweet this stuff you're gonna tweet it all over the place and the next thing you know oh shoot my my project went a little viral or something like that now if you want to look good this is my another Tipp bootstrap I mean we go over this in the class it's true the hype is real it's as easy as possible it's clean minimalistic and it works out well and the ultimate goal I mean if you think about this you did all this work for the spinal project and the ultimate goal is literally just to win a person over in 10 or 15 seconds as weird as that sounds you want to win the person that first person over the technical recruiter you want to win them over in the first 15 seconds or you know less so that they can put you off to the next step in the process the really hardcore people will dive into the nuts and bolts of your deep of your project but when you're talking about a numbers game you don't have much time at all and you want to make it very easy for people to read and understand exactly so let your work do the talking you don't want to be a weird blank cold email you want to give off the impression that you're smiling good-looking dude or that you're smiling good-looking one and that you can do good work and that you're personable and that things are going to be good so interviewing final process here how can I most efficiently convey my skills how can i press recalls so once you get past that first point once you're scheduling your phone screens once you're scheduling your technical interviews and all that how can i how can I best prep for it you've got a step inside of your interviewers shoes you have to do your prep there are no excuses for not doing your prep in my opinion I know the huge thing that Katie dropped knowledge on me was recruiters are your friend she put this in spec oh I'm not sure why I didn't think about this before recruiters literally get paid to put good people in positions and to successfully put you in that position recruiters want to help you after before every interview that I did I either emailed him and said hey what can I do to prep best what would you recommend if I was gonna do an in-person or a hiring manager I'd say hey could we jump on the phone real quick can we talk about you know this person their background anything because you'll pick up a lot of subtleties that you wouldn't have known before and you'll feel a little that much more confident when you're actually talking to the person talking to do your research on the interviewer blogs are absolutely gold because then you see what they're interested about how they write their stone their top their tone tile there's tone and their style LinkedIn sometimes has good information that sometimes that there are articles interests or their technology stack Greg why do I care about what technology stack the person I'm talking to uses well I mean if you think about it maybe you can drop a little something in the interview it's saying oh like I found a bunch of people that would mention ipython notebooks oh cool I mean I use a lot of ipython notebooks I don't say that directly but I say you know in the program we use a lot of pandas we jump into an AI Python notebook and we do some you know data analysis from there just that keyword ipython notebook oh I can relate to him I know what he's talking about you connected right then and there and then when it comes to questions at the end of it you know do you have any questions for you there absolutely golden absolutely golden the best ones that I found out were if you google XYZ company and then Google News you'll get the news for that company right then in there it's a current event you actually did your research and the person's like oh shoot yeah I heard about that internally maybe it's not that big a deal or something like that so let's say there's an acquisition when I was going through Salesforce they acquired a smart calendar app back in May and I said oh did your team work with the temple acquisition at all oh yeah actually we did work with that a little bit okay you can tell me about that and then if you're stuck on that you can't ask any news you can talk about role and responsibility transitions and so if you see that the person you're talking to and they're moving from one thing to another I always usually harp on that you talk to me about that transition process why did you move your thought process here blah blah blah you know you kind of you know work it around there and the ultimate goal is to be surprised no I'm no surprises and you want to be prepared yes interview key points so this is the things that I noticed the most common questions the two questions you always always always have to be prepped for no matter what tell me about your background that's a 30-second pitch and why us and why our data now just those are the two questions you're always always going to get no matter what so you just want to make sure that you're ready for those and it changes at each company although you can have a template that you use and adjust it to each company and so this is a small little personal thing that I did take this for as a grain of salt if you want but I would always open the light-hearted hey Katie how's it going today oh it's going good Greg because this is still good time for you yeah you know it's a you know beautiful day out thanks for calling me today or something like that I'll let them know that I'm a real person right then and there because a lot of the time the interviewer sometimes one they don't want to talk to you usually I mean it's time out of their day and two sometimes they were more nervous than I was on the phone and I want them to know hey everything is okay I'm a real person you're a real person let's let's have a good conversation about this now the other question they usually ask is what are you looking for - what are you looking for and I found out a sharp Direction is better than a general direction is better than I'm down for whatever so what I mean by this well so when there's the data science spectrum are you on the hardcore machine-learning PhD stats side or you on the product business analytics side you know pick a side it can be general yeah I mean try to get as short as possible but just don't just don't be that I'm down for whatever a guy because that doesn't that doesn't show interest and it doesn't show that you know what you want and it's okay to not know an answer to something they can't expect you to know every single little thing it's your goal when you're met with an answer that you don't know don't spaz and don't panic say something like hey you know that's an awesome that's actually a really good question I'd love to do some more research and get back to you on that and it's like wait you just answered it wrong but you sound so happy it's like yeah because I can get back to you later on it so it's a turning a negative into a positive and you weren't you'd be surprised about how it like sometimes when you get asked that question it's like please could just move on just move on quit harping on it like I don't get it like I don't want to tell you I don't know but this is an easy way it's it's like say hey I don't know it right now I'd love to work on and get back to you later and then the other thing that I found out was really useful for me is I want to rewrite my resume but almost because you have your resume it let's just say it has 50 bullet points on your resume you know 40 bullet points you're not gonna remember every single one at the key time that you want to if you've studied your resume a week back or two weeks back now before a huge call what I would do is I would print out my resume and I would reread it because then the information was at the tip of my tongue and when the person would ask me something having just read it I would have a bong example to drop on them when the time was right now the other things too is once you get in the interview process you're not doing as much data science as you were when you're knee-deep in the program so all the prep that that galvanize gives us it's it's really good stuff and those 120 interview questions which you guys will see you later those are good things I do the same thing go over those well Greg you've already done these three times it's like yeah but I get in a zone you know I get in the mode I get I get into it and it's easier to handle the stats questions it's easier to handle the machine learning ensemble questions after that now the SQL 0 of 3 this is a little story I was on a phone call with LinkedIn and it was pure technicals all SQL and SQL is not my strong point and so they asked me the first question and I had no idea so I was like shoot and it's funny because the recruiter beforehand he even called me because he wants it you want style now he says Greg they're gonna harp on SQL a lot and I said do you have any specific examples and he said no there's to study or SQL and it's like what does that mean you know I mean and so the first question came up I had no idea and so I worked with them and I said you know this is how I would kind of do it in pandas or how I do it in Python and this is kind of my thought process what I'm thinking about they go okay well can you try typing that out in SQL I tried it they helped my syntax and we eventually got to something that was not probably not syntax correct it was close enough they knew that I could see you know case when SQL or like where versus having SQL or something like that second question I'd absolutely no idea absolutely no idea the same thing I describe my process to them and they sin tax was wrong they helped me out third question came up was the hardest of all I was like I'm I didn't say I have no idea but I just I was sitting there and I was just like shoot man you're not getting this job you mean it's good practice though so just keep on going through it and so they helped me out again it was on colaba at it too so it's like you can't BS on clab at it there's there's no getting around that and I ended up getting the callback for that position because yeah weirdly I never getting the callback from that position because I think I just explain my process this is how I do in Python this is how I do it in pandas and they took to it and they could see that I could code nothing about SQL I mean it's not hard right I mean it's not the hardest thing in the world not you know see I mean a C+ question or something but it's uh so I think that they had a little bit leniency on there but so if you form your I don't know questions in a good way it doesn't end up always so bad so ultimate goal here is you want to efficiently deliver your preparation so this is where the hard core or hard creative energy comes in so the more work you give something the more attention the more energy you give something the more benefit you're going to get this is in lieu of what a lot of people call hustling it's in lieu of what a lot of people call hacking your way through the process you see these what I'm telling you right now isn't so conventional but it's hard creative energy you put it out there and you know something will come back for you and so here we go on to the resources and goodies that I'm gonna give you so there's the company list of about a hundred email 100 companies take that list as a starting point go run with it and build your own after that and then I recommend pruning and plucking through there for your own own interests I'll give you the email and interview tracker the cold email intro template for resumes I use credal and it was funny because I had a very fine ANSI boring times new roman' looking resume and Katie said Greg man this looks boring you got to fix it and so I went on Credle and I switched it up and I wasn't comfortable sending it out there but then I thought well dude I mean Katie knows what she's talking about I sent it out there and then I started people well greg you resume looks good oh yeah I know right and then interview prep it's all I mean it's all galvanized they give you wonderful information it's what I used and it's absolutely great and so my goal for this is that you'll use this information improve upon it and you know tell everybody else how to do awesome and data science interviews after this thank you and quickly I want to go over the interview template that I was telling you guys about before so let me see if I could so say you're sending out an email to instacart you do that it's gonna go to jack and jack is a technical recruiter and i contacted him whatever that date is now you go over here it's like okay Jack hasn't responded yet but once Jack responds that's when I put it into the pipeline because if you send out an email in the response I don't really count that as it's in the pipeline I count that isn't they haven't responded yet but if he responds he said hey I'd like to set up a call then you go into the cart and you say in progress because it's in progress and what's cool is that will format and it'll get updated it in progress over here it'll get green over here and then you can go over here and be like okay while I'm talking to a recruiter mark it in and then you have your progress all marked over here as well so again if you want this information it's all in this little repo that I put under my name so with that know also there's a company list as another tab and then there's the cold email template as another tab so here I won't go over this in detail its I mean you guys can read this on your own but this is literally what I did and what I a be tested didn't work for me so any questions sir sure so we like follow-up like after the process didn't follow up once yes so the question was how many questions could you not answer and then how many questions did you actually follow up with afterwards and the answer is how many questions could I not answer I mean out of five interviews maybe you know two or three or something like that the hard part is is one of the questions is what is PCA it's like okay well you want to find the variance across you can cross multiple variables and you redo reduction from there okay well can you go deeper than that it's like oh yeah yeah I could you only try that for a second so it's like questions like that so it's the deeper questions we're tougher than the surface awful ones yeah other questions he sure so no that's awesome I what I would do from there is I would contact them straight up at just again so if it was if it was like six or seven days since the last time I contacted him I would I'd do it again so so I were the last contact to date you know if it was more than seven days I would shoot them a reminder email hey just looking to catch up with you on this blah blah blah can we talk about it and then surprisingly some I mean the response rate after that wasn't so bad and so it's like cool that little bit of effort got me the response rate for that for the response for that person other questions Zain so when I first when I first started off I was worried that I wasn't gonna get any interviews anywhere and so I was very like brought I cast a wide net and what ended up happening was a lot of jobs are coming back to me you do a little bit more research and it's like she actually I know I probably and so in the beginning I wanted my false negative rate to be very very low meaning that everybody was going to get in I think yeah I think so I wanted everyone is going to get in and then after that then the threshold starts to rise a little bit more then I start going give me being a little bit more selective but with nice I can say this from finance to data science people answer your emails in data science which is it's like thank the Lord I mean that's it's just so much better because I've definitely done things the wrong way before in this it was really really doing this time to go into this process sir okay so you know I meant to say it's my personal I almost forgot - I wanted to harp on one thing I didn't mention an open job posting once and I did that for a reason because I didn't care if there's an open job posting or if there wasn't some people said Oh Greg you would apply even if there wasn't a data science thing on their job board it's like heck yeah I mean all the positions they're either happening in the future unposted and if it's posted you know you're probably late on it the probably in the process of filling the wreck of five other people so to answer your question I didn't care if there was a job posting open or not and for the time line graduate on July 10th accepted job offer on August 8th and within my cohort I wasn't the first one to accept I was about probably the third or fourth one to accept out of the 20 of us yeah you know that's a great point that Katie said - and that's another thing I should mention is that I did I ended up doing you know all this work and all these emails and I went with a company that was at hiring day so it's just it's funny how life works whole life works out like that oh yeah so no sales force is out the hiring day and there's some it's cool because at this point at your you know time you haven't been through these interviews you haven't talked to these teams you haven't seen the problems out there working on you learn a ton as you're going through that process and your data science compass of what you want ends up switching from there and it gets more refined and you understand what you want more now to get answer your question about types of questions I was focusing more on the business analytics product analytics data science side so it was a lot of business case questions Greg say you're managing this product and this is what it does how would you track its success how what product features would you recommend and you know things around that nature now however the guys interviewing dudes the guys in interviewing with Google we're doing the more qualitative stuff quantitative stuff they're getting hard core data science questions algorithms stats questions and that's not my foot and that's another thing I mean you have to understand where you lie on the spectrum I this was my first technical type of field and so I knew Greg you're not the data science guy I mean on the outside I'm the data science that you're not you're not the computer science guy you're not a computer science undergrad you're not you know the efficiency super hardcore knee-deep in C++ guy you got to work your strengths and my strengths was a business side and so that's where I was focusing on sir unfortunately my opinion on that is the business types of questions unfortunately are kind of on the soft skill side and so it's hard to study up on that stuff it's not like there's a definitive answer it's good it's like case-by-case so no but if I did have that question I'd probably go to kora and immediately just type in you know business case designs questions and if you'd like to go over think more things in depth that I've learned along the way with those types of questions let's talk afterwards for sure and that goes for everybody absolutely without a doubt contact me I love it whenever you guys do so it's gonna depend on what your specific project is like I said before that you see a picture is just easy to digest then text then code as easy as you can make it for somebody digests really quick the that's the best way for me specifically ended up being a picture so it's like throw the picture at as many people as possible some people liked it and you go from there yeah Colleen so fortunately for all of us the question was how often people ask about the capstone project fortunately for all of us capstone is easy to talk about because we've been working on it for so long and so even if they didn't ask for it I would almost steer him in that direction that talk talked to me about it because I knew it in and out and it's something easy to talk to you sound authoritative then you sound like you know what you're talking about and because I was doing that they asked it a whole lot more so yeah and for the past three minutes I just got done with galvanize which is a data science immersive and it ended up finishing with the final project that put online and luckily it's gotten good attention oh can you tell me about your final project sure no problem yeah any other questions awesome so it's on the it's on the github if you guys want all those goodies and so is my contact information please do not hesitate to reach out thank you [Applause]

Channel: Galvanize

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Id: 3BRLGRqj8ps

Length: 35min 43sec (2143 seconds)

Published: Tue Nov 03 2015