How I passed the TensorFlow Developer Certification exam (and how you can too)

you know what I believe and this is a bit of a lie won't take two weeks surely it's there already cuz it oh my goodness congratulations your passes heads flow deliberate oh oh you cry I cry you'll be happy to know I didn't cry the only two times I will allow or permit myself to crying is in the final scene or one of the final scenes of Terminator where he's sinking down into the lava thumb up or when fixing a cooter error when training a machine learning model they're the only two times but what you just saw was me passing the tensorflow developer certification exam and so four weeks ago or so start of May I decided you know what I'm gonna get tensorflow developer so fine and so that's what we're gonna do in this video I'm going to talk about what it is why you might want to look at doing yourself how I did it and subsequently how you can - let's start with what so what is the tensorflow developer certification but first what is tensor flow well tensor flow is an open source numerical computing library and what I mean by that that's a fancy way of saying it's a computing library that allows you to take some sort of data and a data can be a whole data is very wide wide-ranging term it could be a structured table of numbers it could be an image it could be a body of text anything you can imagine almost turn that data into numbers so that's that's usually called pre-processing and then find patterns in those numbers usually referred to as models typically you will build a deep learning style model which is a neural network with 10th apply and then this is all within tensor flow by the way and then you can use the same library to serve or to deliver those patterns that you find in data to people all over the world through the form of an application for machine learning powder vacation now tensorflow has sections within its library it's a very big library that allows you to do each part of those it's what Google uses to power all of their machine learning services now the tensorflow developers certification as you might have guessed is a way to showcase your ability to use tensorflow now if we think about it I just broke it down to the flow into pre-processing modeling and serving at its current standpoint the tensorflow developer certification is focused on the modeling part and so what I mean by that more specifically is building deep learning neural networks for computer vision natural language processing so identifying patterns in natively written text or naturally written text and time series forecasting so if you're imagining you have a series of events across a certain time period how can you build a deep learning model to predict what comes next in that time series now that you have a rough idea of what tensorflow is and what the tensorflow developer certification is why might you want to get tensorflow developer certified well my first reason was fun that's sir the first reason I use for a lot of things but it was at the start of May and I'm like you know what I'll sharpen up my machine learning skills and so I've discovered well this is a great thing to work towards to to give me an excuse not only to read this beautiful book that we'll get into later but to just sharpen up a few other things that that I'd wanted to learn for a while I wanted to practice for a while now two other very valid reasons aside from fun I kind of touched on it just before is to number two would be to acquire the foundational skills required to build machine learning powered applications and number three to showcase your ability to work on machine learning problems to a potential future employer and speaking of future employees based on some data from hacker news now this is from a website called hey Chen Transcom and based on some data from hacker news is who's hiring Paige it seems that tensorflow outperforms in terms of job postings like if if the the D planning framework was mentioned in the job posting of a company its hiring it seems that at the moment tensorflow outperforms other deep learning frameworks now this is not to say that one is better than the other it's just just an observational thing like it could be completely different depending on on what kind of role you're going for and of course a paid certificate is no guarantee for a job but in the world of online learning where most of us or many of us are learning these skills now it's a way to to compensate or to go to someone hey you know what I've done the effort I've put in the effort to learn these things and I've gone to the trouble of going through this this skills competency test to make sure that I can go hey look I can do these things I think of it and I'll say this probably more than once I think of it as a nice to have not a need to have it's something that you can use beside to go alongside with the projects that you've worked on yourself now you might have heard all this and be like yep it sounds great how do I do it well let me tell you how I did and maybe give some inspiration for how you can - the first thing I did was read the handbook that you can find on there tensorflow developer certification homepage and then I did my research on what I needed to know so once I've done that I put together a curriculum document in notion namely I wrote out each of the different topics are needed to cover and then gathered resources together for each topic so if we started by reading the handbook the exam says it's going to be on and now I'm breaking down each of these into into the four main topics it's building training neural network model using tensor flow to point X ok a match the input shape of data to the input shape of a neural network then was number two image classification can you define convolutional neural networks or trained on real-world images number three natural language processing can you build models that identify the category of a piece of text using binary or multi-class classification a number for time series sequences and predictions use recurrent neural networks and convolutional neural networks for time series and forecasting models now if you were to first read this handbook if you've had some experience with tensorflow you might read that and go you know what this is pretty straightforward I might need to touch up on a few things but none of it seems too outlandish to me but if you're a beginner and you're you're you're new to the field and you're still learning machine learning I mean I'm still learning machine learning but if you haven't had much experience or hands-on experience with tensive all you might read it and be quite overwhelmed but that's okay the resources that I'm about to list the ones that I'd collected and discovered after I knew that the what the exam was on they will help you to learn these things the first place you want to go is if you want to have for the exam or if I only had to pick one resource was the tensor flow in practice specialization on Coursera and then I actually used a few more so the three the main three that I used was a tensor flow in practice specialization on Coursera their hands on machine learning book with scikit-learn Chara's and tensor flow by or rayleigh Onderon now only half of this book is related to the exam so it's a part on neural network so I think and I've done exactly what page it's on what starts and but in the blog post I list what exact chapters are relevant to the exam from this book finally was the introduction to deep learning by MIT so the first three lectures of that series on YouTube most relevant to the exam ah finally the bonus one is the getting started with pycharm and tutorials and the pycharm website because the exam takes place in pycharm and so if you haven't if you're not familiar with pycharm i most of my development i do in jupiter notebooks so if you haven't used PyCharm before it's it's definitely a good idea to get familiar with that before you start the exam so now that we know kind of a brief overview over like one of the main resources I'll just quickly run through a bit more details about each namely cost and how long and usefulness of each one first up was the tensorflow in practice specialization taught by Laurence Moroney and Andrew M who are Titans of tensorflow in fact titans of artificial intelligence and machine learning incredible incredible instructors you might have seen some of their videos on YouTube now the cost for this was about 59 US dollars by the way all the costs in this video US dollars and and well it costs that much after a seven day free trial I believe but and you can apply for financial aid and there are also equivalent versions of the videos of Coursera on on YouTube so there'll be links to all of that below now in terms of helpfulness as I said before if I could only pick one resource for the certification this would be it the tensorflow in practice specialization not only is it great for the certification it is phenomenal for just getting hands-on practice with tensorflow in general and so for me it took to go I started about the 8th of May and I took the certification on June the 3rd so it took me about three weeks now I want to stress this is that I have experience with tensor flow and machine learning so I was able to go through the projects relatively quickly but if you're if you're a beginner adds for all of these resources you want to take as much time as possible because at the end of the day you're not optimizing for getting a certification you're optimizing for for building skill that's what you're you're mostly after and what my puppy's saying hi see ya alright let's dance okay well it looks like sevens gonna be in my feet for the rest of this video and so where were we well yes I the tip it was a please please please not only take your time take as much time as you need but for the for the coding projects be sure to write the code yourself and when you do the coding projects you'll get these gaps that your to fill in but I found it extremely valuable is to write out the whole thing so you get familiar with writing the end-to-end project yourself it does take longer but what's important is to understand what's going on in each line rather than just becoming an expert at just filling the gaps where someone else has built the structure for you you should become that expert as building the structure and familiar and gaps yourself now the second one is a hands on machine learning book with scikit-learn carers intensive Lowe Wow I had to I was reading that from behind and that was kind of difficult by Aurelien Garron amazing amazing book as I said for for the exam only part to the part that covers neural networks is related to the to the certification but if you're if you're a long time machine learning practitioner and you want to or you want to set yourself up with a solid foundation for the future I highly highly highly recommend getting a copy of this book read it through I've read it through I read it through cover to cover I was averaging about 25 to 30 pages a day because I would I would read an hour per day and then do 2 to 3 hours of practical work I think that's a really good balance is that whatever you're reading try to balance that with this same or watching videos that is so if you watch one hour of video do at least one hour of coding if you read one hour of over a book do at least one hour of implementing what you've read so I rated this a helpful helpfulness rating 7 out of 10 only because half the book is not related to the certification but in terms of helpfulness rating for machine learning in general this gets a 10 now the cost will vary depending on where you're from but it's around about I've got the physical copy because I just like reading physical books but yeah it will depend it's around about 55 US dollars but you can see all of the code examples that come from the book for free on github now 3 is the introduction to deep learning by MIT or intro to deep learning comm now this is the 20/20 series which is phenomenal let's just put it that way like the quality of these reisel we're talking world-class deep learning material world-class University all on YouTube all for free so again I've rated this one a helpful in this level at 8 out of 10 only because some of it isn't related to the exam but in terms of getting started with deep learning in general and I would highly recommend it so it's going to get it it's going to get a 10 for that I only watched the first three lectures and went through the tensor flow lab that they did on github myself again writing out all the code because they're the most the first three lectures are the most relevant to the certification again the Seri of student will want to not only go through all of the all of the series you'll want to to put into practice what you've learned much like now before was a getting started with pycharm resources on the pycharm website and so this is this is also free but it's basically required so when I went through the the PI Chun resources I got not only did I get familiar with pycharm just the interface it's a little bit different that if you typically use collab or a Jupiter notebook and I went through to tens of flow tutorials on the tensorflow website to make sure that tensor flow worked on my local machine so that's that's definitely required get familiar with pycharm before you take the exam now that we've covered the resources I use to learn the materials I've kind of touched on a little bit of how I went through them but I just want to just go through a few things that you might want to that you might be interested in in terms of like studying tidbits let's let's call it that studying tidbit so when I as I said I collected all of the the resources that I needed I went through the tensorflow Handbook made sure I was aware of the criteria for the exam this is kind of what I do for for any project going forward is that I create like a base a baseline ground truth put it that way in machine learning terms I've created ground truth for myself and that is I've been using notion you could use almost any note-taking software or whatever notion just has a few cool things you can do and so when I was studying I put down all the resources in my notion document created a curriculum and then put them into a car barn chart so what that is is it's kind of it has four in a simple way it has three columns I was like not started in progress finished and so as I went through each section so for example I read a chapter of this I would move it through in progress to finish I I went through a module of the the tenth of law and practice visualization I'd move it from not started to in progress while I was doing it and then to finish and then I worked through until I was pretty satisfied with what I'd learn in terms of how it was related to the had I gone through the criteria enough that's what I was I was going through this process so a little ritual I sort of created throughout May was every-morning get-up go for a walk get some physical activity get the brain working do an hour of reading do 2 to 3 hours of coding so going through the Potenza flow and practice specialization again I can't stress that enough cohhd cohhd cohhd cohhd and then now sevens getting treats all right now a poppies out of a room I should really take care of this before I start recording videos anyway so the ritual I would do was walk for an hour in the morning come home or about now and read code two to three hours and then once I'd finished a module say for example I finished the computer vision module of the telephone practice specialization I'd wrap it all up by watching the MIT deep learning lecture related to module so this kind of tribe route approach I find I learn best from I learn best from multiple different sources you're probably similar so if you have someone you might have some teacher explain something you don't really understand it but then you you read it you read it in a different way and you understand it better and then kind of you we create your own knowledge through practice so that's how I approach things terms of going through all of this how long should it take well as I said it took me about three weeks but that being said I have experience with using tensor flow so whatever your timeline is you want to adjust it for your for your own own level of knowledge and of course not everyone has a luxury of being able to study four to five hours a day so again fill it in to where you can and remember learning anything worthwhile takes time alright you've done all your study what happens is with the actual exam well the actual exam costs a hundred US dollars to take and if you fail well you have to pay again but you also have to wait two weeks before you can do that if you fail again you have to wait a little longer and the timeline you have allocated for the exam is five hours so when you press Start or by the way tidbit when you sign up when you register for the exam it takes about an hour while it did in my case for your because you because you have to formally register you have to scan your documentation it takes about an hour for things to go through so if you're expecting to take it as soon as you sign up you might have to wait a little while so that's I was like yep I'm gonna take it today here we go what do we have to do Oh your ID has not been verified I probably should have done this first should not your ID must complete verification before you may redeem or attempt the exam right so I had to wait an hour or so before I could start the actual exam but once you do start the exam once you hit start officially head start a timer gets set up and pycharm and you've got five hours to complete the exam now as I said I made sure tensorflow worked in Python before I started but I spent about the first hour you could have guessed it well goodness gracious me we got it fixed ran into the absolute epitome of tensorflow errors just then turns out add to get into the Python source code and change something in Python three point seven point three which I have no idea why I would have to do that since yesterday it was all working here we go this is the thread I'll put a link somewhere now the exam stresses that you need Python 3.7 but for some odd reason when I I have pi from 3.7 for some odd reason I found myself for the first hour of the exam deep in a github issues thread of tensorflow trying to figure out what was coming on an arrow kept coming up every time I ran tend to flow it turns out I had to change a line on specifically line 48 in line cache dot pi to fix error in the Python source code that is and now I'm not sure I'm probably putting that down to some sort of user error maybe I've done something wrong but once I implemented the fix I found on github everything worked fine so if I didn't have that sort of roadblock at the start of the exam of trying to fix everything I think it would have taken me probably under three hours so that the five hour time limit is so that you can train deep learning models on your computer because the way you get marked is by submitting a trained model file which gets automatically validated so again another tidbit here is that if your computer isn't fast enough to train a deep learning model and these are these are not large models they're they're quite small but if it's still not fast enough to train it in that five hour time frame you could train it on on google collab for example download it and then store that saved model file file in the Python directory that the tensorflow developer certification creates for you once you start the exam if all of this doesn't really make much sense you'll it'll be clear when you sign up for the exam and read the read the instructions of how to complete it now do I have any feedback for the example how was it like did I feel like it was testing my abilities so probably my main piece of feedback would be it would be great and I know this is it's only the first iteration so it's no doubt at legal to be changed over time as these things go because you get the certification in over the last three years so going forward if you want it recertify if you want to resharpen your skills you're gonna have to take it again but i would like to have seen it a little bit different to the to the Coursera intensive law and practice specialization so if if you're a keen student you'll probably notice that the the tensorflow developer certification handbook is basically or the criteria for it is basically the outline of the tensorflow Coursera intensive flow in practice Coursera specialization that is a mouthful so yeah that is why I recommend that as being the number one resource that you should go through if you're looking to take the certification as I said that the certification only focuses on the modeling part of a machine learning pipeline maybe in the future there will be others on pre-processing modeling and then serving a model but we'll see so you finish the exam what do you do next well the first things first is that once you've submitted it and you'll have a pretty clear indication as you go through as to how your progress is going because for each model you submit it gets marked fairly quickly and you get a score out of I'm not gonna run anything but you just get a score for that and you'll know pretty pretty quickly whether or not you're on track to pass the exam so once you go through you get an email at the end once you once you click Submit you get an email which which will say congratulations you passed if you did if not that's okay there's always you can always take the second attempt but you won't you won't get much feedback it'll just say hey you passed or how you didn't pass but within that email there will be a form that you can go fill out that you can receive your a pencil offif a pencil official tensorflow developer certification this this bad boy here I actually just got my this morning so it takes it takes about a week and you can register to the Google certified developers Network so what that means is that if someone is looking for a tempt certified tensorflow developer on the online somewhere in their region they can search up your name and find you and go hey well this person's this person's got tensorflow skills they've taken this certification exam they've proven that they can build things with tensorflow so I think that is pretty cool and then once you get your certification of course and your badge and whatnot you can share that on your professional network you can share that put it next to the projects that you've made on your portfolio and that way again just as I said at the start it's a nice to have it's a nice thing to to be able to stack next to other things that you've worked on to to say hey look I've got these skills here's the proof finally and most importantly I love you can see if you can't there's a big big checkmark here that says today get certified we're gonna cross that right off boom we're done but as I said it is not about the digital certificate or the badge it's about acquiring the skills the skills to use tensorflow to build machine learning powered applications that enable the change you want to see in the world to happen if you have any questions about any of the resources how I study how I created my curriculum or the actual exam itself I can't share too much about that leave a comment below and I'll answer it but don't forget to check out all the resources including the curriculum that I created an ocean try creating out one of your own by clicking the duplicate button they'll be in the description below as well as a full blog post detailing all of the information we've talked about as always keep learning keep creating and I'll see you next time [Music]

Channel: Daniel Bourke

Views: 255,678

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Id: ya5NwvKafDk

Length: 26min 24sec (1584 seconds)

Published: Tue Jun 09 2020