How I got Google Cloud Professional Data Engineer Certified

Nice hoodie, bro. Where'd you get that one? What's that? It's supposed to be my Google Cloud Professional Data Engineer certification, but the printer ran out of ink. It looks way better in digital version anyway. How'd you get that? Oh, it's a bit of a story. I'm listening. Alright. Now, this is a story all about how my life got flipped, turned upside down, I'd like to take a minute, just sit on there, I'll tell you how I became a Google Cloud Certified Professional Data Engineer. Let's get this hood off, it's a bit warm in here. Still not quite winter yet for the hoodie. Just a heads up, what I'm going to share in this video is the steps I took to get Google Cloud Data Professional certified, like did the certification exam, without necessarily having the prerequisite 3 years professional experience /1yearwithgooglecloudplatform. And just to show, exemplify how fast this field moves, I did the exam before March 29th, 2019, so there have been some changes to the exam since then, but I've listed them in an article I've wrote to go, to go, or written, wrote, written, to go along with this video. So there'll be a link in the description for that. You can find all the resources there. Let's start with why. Now, why would you want to do the Google Cloud Data Professional certification? Now, what is the purpose of certificates as a whole, as general? Well, if you think about it, there's two real ways to show your proof of skill. One is to have a portfolio where you can show people projects of what you've worked on and what you've done to say, "Hey, look, this is what I've done. I can do these things." Number two is some things are a little hard to show on a portfolio, like being able to use Google Cloud for data pipelines and data engineering infrastructure. So as to where this comes in, I know it's in black and white, right? Like, if I printed in color, if the printout coloring doesn't matter, but that's where a certification comes in. What it's saying is that I've gone to the trouble of learning how to use Google Cloud for, for data engineering problems, and I've also gone to the trouble of doing the exam to have recognition from Google to say, "Yes, my skill set is valid to be able to use Google Cloud for data issues or data problems." And now this is something you could take to a potential employer or a potential client or something like that to be able to go, "Hey, if you're needing help using Google Cloud, I've got these skills and I can back that up with this certification that I have." Alright, so who would want to do a Google Cloud Professional Data Engineer certification? Maybe you're a data scientist, maybe you're a data engineer, maybe you're a machine learning engineer like, like myself. And what you probably know is that cloud services are getting more and more prevalent. You probably use one if you've, if you've worked in data science or worked in data engineering, you've probably used one of the cloud vendors before. There's, there's about 4 big ones at the moment, maybe 5, but definitely, definitely at least 3 major players that have a lot of the market share. And why is this? Well, in a nutshell, computing used to be done in a business's office. They used to have servers and whatnot in the actual building, but now it's slowly moving towards being done on the cloud. And what are the benefits of this? I'll let you, you look into that. Long story short, for any type of computing, cloud skills are becoming more and more in demand, and especially to do with any kind of data. If you're an existing data scientist or data engineer or machine learning engineer and you want to upskill yourself for the future, looking into a certification like the, the Professional Data Engineer may be something you want to check out. Now, in saying that, do you need a certificate like this to be a good data scientist, data engineer, or machine learning engineer? The blunt answer is no, right? A certificate should never be confused with skills. This is simply a measure of validation that you can show someone quickly to go, "Okay, yes, this person knows how to—" If I showed someone this, right, on my LinkedIn or an employer or something like that, they can quite quickly assume like, "Okay, he's gone to the trouble of getting that. I can trust that he's got skills using Google Cloud for data problems." But even if you didn't have the certificate, you can still have the skills to use Google Cloud. You can still have the skills to be a data scientist, data engineer, you know, machine learning engineer. Okay, so you've got the spiel of who should do it, why you should do it, but how much, how much does something like this cost? Well, to sit the exam is $200, and if you fail the exam, you only get a— actually, at the end of the exam, you only get a pass/fail, right, mark. So at the end, you, it'll go pass or fail, and then if you pass, it'll go your exam has to be validated, and then if you actually did pass, you'll get another message saying passed, and via email. But if you do fail, you'll have to pay the $200 again to resit the exam, and there's a little buffer period. So, for example, you can't sit the exam multiple days in a row. You have to— yeah, you have to wait 2 weeks or something like that in between resets. And there are a few costs involved in some of the training materials, particularly the ones that I use to get upskilled to obtain the certificate. But we'll get to those in a second. Alright, so you've sit the exam and you've got, you've acquired the certificate. How long does it last? 2 years, and then you'll have to resit the exam to re-obtain something like this. That makes sense to me, a lot of sense to me, because this field changes so quickly. Well, you've actually, actually, as I said at the start of the video, the exam's already changed since I did it. That's to make room for all of the new technologies coming on board on Google Cloud, and I'm assuming in 2 years' time it's going to be a little bit different, right? So you're going to have to continually upskill yourself, and this will be across the board board, not just with Google Cloud. This will be with any other cloud vendor and any other data science or machine learning technique. It's, it's an evolving field. You've decided you're going to sign up, right? You're going to pay the $200 US. What are the prerequisites required before sitting the exam? Now, Google recommends 3+ years of industry experience and 1+ years of managing solutions using GCP for professional level, for all their professional certifications. So that means 3 years of being in the industry and 1 year of using Google Cloud. Now what happens if you don't have either of these? I personally didn't have either of these. I had more like 6 months of each. So to supplement this, I used a combination of different training resources. For the specifics on each course, like the cost and time and length and more details and the helpfulness— oh, actually I'll list the helpfulness in this video, but I recommend checking out the article I've linked below. That's kind of got a bit more details about each one, and that way you can sort of suss them out and think about which one might be best for you. The main one I did was kind of like a 0 to 1 course for getting around the Google Cloud Platform for data engineering. Had a lot of lectures, a lot of practical hands-on stuff, and that was the Data Engineering on Google Cloud Platform specialization by Coursera. And I've rated it a helpfulness of 8 out of 10, with 10 being, well, definitely do this course. This was definitely the longest, and I've made a few videos in the past of me going through this. But in terms of not having any experience with Google Cloud, in special, like a data-focused way, that's probably out of all of these, this is probably the best one to kind of go, as I said, from 0 to 1 on Google Cloud for data engineering. After I completed the Coursera specialization, a few things got in the way. Life got in the way, other projects and whatnot. So I'd kind of been off Google Cloud for a little bit because I was just doing other things. And so to get back into it, I did the A Cloud Guru Introduction to Google Cloud Platform to kind of re-jog my memory. I could have probably revisited the Coursera course, but this is just what popped up. I think someone in the office was doing it and said they found it valuable. So I decided to jump in so we could kind of do it together. This one was great. However, I've rated the helpfulness at a 4 out of 10. Why? Don't, don't take this as it being a bad course. It's definitely a great resource, but in terms of, let's just say it's not targeted for the Data Engineering certification. So it's more of a GCP as a whole, and as you could imagine, Google Cloud has a lot more services than just data engineering. This is kind of a grassroots one. If you've never ever used Google Cloud, you might want to start with the A Cloud Guru Introduction to the Google Cloud Platform. After the Cloud Guru course, I did, did one on Linux Academy, which is called Linux Academy Google Certified Professional Data Engineer. Whew, some of these are a mouthful. And now this was the most helpful way in terms of doing the actual exam. Now the whole entire Linux Academy Google Certified Professional Data Engineer course is dedicated towards the exam. So the instructor has, is certified. Of course they're certified, you'd want them to be, right? But the way it's structured, it's kind of tiered as, as the exam is tiered. So it goes through all the different stages and it even comes with a free ebook called the Data Dossier. I'll link that one below because alongside this article that I've written, because that is just a great resource on its own and it's free. So Linux Academy, if you're looking for a course, a single course dedicated just for the exam, this would probably be the one to go for. And so those three are probably the main three aside from using the Google Cloud Platform itself. Those are probably the main three. If you're limited for time, I'd stick to those because they have the bulk of material and education out there. Otherwise, the rest of these are kind of like supplementary ones that could just, just do a little bit more to spark your knowledge. There's a Google Cloud 1-minute videos playlist on YouTube. Which is a series of, I think there's 100 or 90 or so Google Cloud services described in 1 minute by people who use Google Cloud and what they're for. And so going through all the material in the Linux Academy and the Coursera courses, it can be a bit overwhelming because there's so much stuff, but the Google Cloud 1-minute videos help to sort of shorten or give, give an idea of what each service does in a concise manner. I found those helpful. And I mean, there's a lot more than just for the data engineering side of things, but I kind of cherry-picked the ones that I recognized. So BigQuery, Bigtable, that sort of stuff. I kind of just looked at those instead of every single one. And these two I found after the exam, so I haven't actually done them, so I haven't given them a helpfulness rating. These are just something that I've stumbled across when I was helping or recommending a few things to a colleague who wants to get Google Cloud Data Engineer Professional Certified. I'm going to get that wrong every single time. The Preparing for Google Cloud Professional Data exam on Coursera. I looked into it briefly. It's relatively short, but again, it's like a Coursera version of the Linux Academy course of just being solely targeted for the exam. Like not, not in terms of using the platform as a whole, but just, just for the exam. And then there's the Google Data Engineering Cheat Sheet. By Maverick Lin. And now this is, this is, it's a comprehensive cheat sheet. It's again, it's free, it's on GitHub, so I'll link that below. I'll link all the free resources below. It's a 9-page or so document that's very comprehensive but also concise on, on just some of the major things about data engineering on Google Cloud Platform. And there's a lot, and I mean, it's, it's ever going to be updated, but it's a good resource to check out, something you could use to sort of read over after you've done some, some practice exams or something like that. What did I do after the courses? All right, so I'd spent a couple of months going through these, these courses. As I said, the Coursera one is kind of like a 0 to 1 on Google Cloud Data Engineering, so it takes a fair bit of time. And then of course the other ones also take time. But after the courses, I started digging into the practice exams, both on the Google Cloud website for the, for the Professional Data Engineer certification. I didn't find that one as good as the Linux Academy practice exam. So again, the Linux Academy course shining here with a, with an awesome practice exam. I did that multiple times, probably half a dozen times, even sitting in a cafe before the actual exam. I was going through it again just because I read some good things on the forums of people, people rating, rating the practice exams as being great. And now I kept going at them until I got 95%+ accuracy or correct constantly. So if I did the exam fresh, I would get 95%+ correct without really trying. And now where I found a lot of value was going over the practice exam on Linux Academy and then finding out what I got wrong. And then writing down, why did I get that wrong? What did I get that confused with? Because some of the services are similar, but they're, they're kind of different. I can't recommend the practice exams enough. As for the actual exam itself, it took me the full 2 hours, right? It's about 50, 50 multiple choice questions. And it's about, I would say, at least 20% harder than any of the practice exams I did. And so that is why I recommend doing the practice exams constantly until you're, you're nailing them, right? Because there's— it doesn't say anywhere what the passing mark is for the, for the, for the Professional Data Engineer exam, but you should be aiming to get over 70%. That's what I've heard. Again, as I said, at the end of the exam you get a pass/fail mark, so you don't actually figure out what score you actually got. You just pass or you fail. Now, what would I change if I were to do the exam again? Number 1, more practice exams. I mean, I cannot stress enough how valuable the practice exams were, especially from Linux Academy. That's the number 1 thing. I even remember back to university, I'd kind of skip the practice exams because they were hard, but they always turned out to be the most valuable resource when sitting any kind of exam. And the second one is, of course, more practical experience. Experience hands-on with Google Cloud, but again, you're going to be limited with time, alright? So I, well, I was limited with time. So if you can't get, it's hard to really get practical experience across everything just because there's so many different services, and unless you're sort of working nonstop on data engineering problems with Google Cloud, that practical experience isn't really just going to be there. That's something you accumulate over a long, long period of time. Hence, the recommended 3 years in industry. But if you don't have that, you can supplement it with some of the courses that I've listed. What happens after the exam? Well, right at the end of the exam, in my case at least, you're sitting in this booth and it's quiet. You're not allowed to talk to anyone in the room. Makes sense because it's an exam. And the computer you're at, well, at least in my case, had no internet access. It just had the exam. That was it. So, you're clicking through the exam, went back through, double-checked it, At the end, it was a tense moment when I clicked submit. Clicked submit, got a little word on the screen, one word, "pass." Your exam will be verified by someone from Google or something like that. You'll be notified within 72 hours. And so I think it was the next day, so relatively quickly, I got another email saying, "Congratulations, you're Google Cloud Professional Data Engineer certified." Got a color version of this one and got a redemption code. What we've all been waiting for, redemption code for a specialized Google Cloud Data Professional store where you have a choice of redeeming it for something like a backpack or a t-shirt or a sweet hoodie. Let's put the hoodie back on. Look at this. This is actually a real comfy hoodie, right? So aside from the certificate, you get some sweet swag. Scott, Scott Google Cloud. We'll just zoom in on this one. Boom, Google Cloud and Google Cloud Certified Data Engineer. So you probably expect this in future videos, but yeah, now you're certified. You don't have to worry about exams for another 2 years. You can get back to what you do best and that's building things and Google Cloud provides. We're so lucky to have such an accessible service to start building data pipelines, data engineering services. On something that's so easily, easily accessible. I'm saying accessible a lot. Now you can use this, you can add it to your LinkedIn, you can show potential employers, hey, I've, I've got Google Cloud skills, I'm a Google Cloud Professional. You can show clients if you're doing consulting work or something like that, you can trust me that I'm eligible to use Google Cloud because I've got the skills and I've gone to the trouble of getting this certification. One more thing, do not forget that the exam has changed. I know, right? I probably should have made this video earlier, but I mean, it's always going to change. It's changed on March 29, 2019. I've put in the article in the link below that you can access some of the changes. I'm not going to list them all off here. It's not that, it's not that great. Sorry, the changes aren't that many. They've sort of just concise that plus added a few more things targeted towards machine learning. As you know, the whole world is moving towards machine learning, but you can, you can see those in the article as well as on the, on the version 2 of the Google Cloud Professional Data Engineer exam page. Otherwise, that's it. That's how I— that's going to wrap up the Google Cloud Data Engineering series of what I've been learning. For at least another 2 years or so. Maybe I'll make some more videos on Google Cloud in the future, who knows. But, um, yeah, if you have any questions, feel free to reach out. I'm happy to answer them as best I can anytime. But as always, keep learning. I was trying to say that in like some sort of Star Wars way, like, you know, the Sith or something like that, but it didn't really turn out like that. Anyway, I've got to get back to writing this article. There's a few more things I've got to finish off. Peace. 3, 2, 1. Alright. Now this is a story all about how my life got flipped, turned upside down, and I'd like to take a minute, just sit on there. I'll tell you— I'll tell you— How does it go after that? Take a minute, just sit right there. I'll tell you how I became professional data certifi— I can't even say anymore. Google Cloud. Google Cloud Certified Professional Data Engineer. How I became a Google Cloud Professional Data Engineer, Google Cloud Certified, sitting right in this chair. Google Cloud Data Professional Certified Data Engineer. No. Ah, that was close, but— Now this is a story all about how my life got twisted upside down, and I'd like to take a minute, just sit right there, I'll tell you how I got Google Data Professional Certified, sitting right here in this chair. How'd that sound?