Is the Google Professional Machine Learning Engineer Worth It?
Gone are the days when Machine Learning (ML) and Artificial Intelligence (AI) were fantasies or hopes and dreams for the future of technology. In record time, AI and ML went from the fantastical to the everyday. These days, it's not unusual to have ML algorithms running and solving everything from the most exciting and thought-provoking challenges to incredibly boring business needs. In fact, machine learning and artificial intelligence solutions are now so widely available to companies that it's rarely the question anymore of whether or not it's possible to implement ML into business practices, but whether it's even worth doing.
A Google Professional Machine Learning Engineer is someone who's trained to always ask that question first. And then, if the answer is yes, they know all the best solutions for getting it done. Machine Learning isn't a one-size-fits-all solution and it's certainly not a fire-and-forget solution either.
The Google Professional Machine Learning Engineer is earned by those who know how to architect ML solutions using the Google Cloud framework that revolutionizes companies and solves some of the hairiest problems companies face.
What is the Google Professional Machine Learning Engineer?
The Google Professional Machine Learning Engineer is an advanced IT certification maintained by Google. At its heart, the certification proves that the person who earns it can train, deploy, monitor, and improve machine learning and artificial intelligence models. You can think of the Google Professional Machine Learning Engineer certification as having two key emphases. First, the person who earns it knows how to design, build, and production-ize ML models for solving unique business challenges. Second, the person who earns it is deeply familiar with all the Google Cloud technologies that make ML and AI possible, as well as the ML models and techniques that are considered industry best practices.
The Google Professional Machine Learning Engineer is a certification that can be earned by someone specifically tied to machine learning but is also useful for people working in different career fields than applied machine learning and artificial intelligence. Knowing how to frame Machine Learning problems and architect their solutions is a skill that's useful for IT professionals in many different fields.
You'll have to pass one exam to earn the Google Professional Machine Learning Engineer certification and Google just calls it the Professional Machine Learning Engineer exam.
What Does the Google Professional Machine Learning Engineer Test?
The Professional Machine Learning Engineer exam has six sections designed to test your ability to train, retrain, deploy, schedule, monitor and improve ML models. The six sections of the exam are:
Section 1: Framing ML problems
Section 2: Architecting ML solutions
Section 3: Designing data preparation and processing systems
Section 4: Developing ML models
Section 5: Automating and orchestrating ML pipelines
Section 6: Monitoring, optimizing, and maintaining ML solutions
It's important to remember that the Professional Machine Learning Engineer certification isn't just from Google it's also about Google. Not only does it test you on the abstract ideas and concepts of framing, architecting, and improving ML models, but it also tests you on doing all of it with Google tools. That means it's not enough that you understand Google Cloud ML tools really well. You also have to understand the concepts behind ML and AI solutions and what Google does uniquely in that space.
How Much Does the Google Professional Machine Learning Engineer Exam Cost?
It costs $200 to take the Google Professional Machine Learning Engineer exam. Once you've paid for and passed the exam, there's no further cost. You don't have to pay to apply for the certification, it's granted to you upon completing the exam. The Google Professional Machine Learning Engineer certification remains valid for two years. After that, you'll have to retest the current exam. Google offers a 50% discount for your recertification exams, so although it costs $200 to earn the cert, it only costs $100 every two years to maintain it.
What Experience Do You Need for the Google Professional Machine Learning Engineer?
Passing the Google Professional Machine Learning Engineer test requires extensive experience with designing, building, and productionizing ML models. Additionally, you'll want to have a lot of experience using Google Cloud technologies doing those tasks.
The Google Professional Machine Learning Engineer tests your ability to translate a business challenge into machine learning use cases – and whether or not you have the judgment to decide when ML isn't the right solution. You should have experience defining business needs, ML problems, and defining the success criteria for implementing ML models.
Obviously, designing reliable, scalable, and highly available ML solutions is one of the most important parts of the exam. It shouldn't surprise you that you need to know how to choose the right Google Cloud hardware components for your ML solutions and how to design architecture that complies with technology needs as well as security concerns. Before you attempt the Google Professional Machine Learning Engineer, you should know how to explore and visualize data, build data pipelines and create input features. Experience with developing ML models, testing them, and then automating their orchestration is also a crucial part of passing the Google Professional Machine Learning Engineer.
Who Should Take the Google Professional Machine Learning Engineer?
The Google Professional Machine Learning Engineer is an advanced certification that is a capstone for many machine learning engineers. But it's also a good certification for people who aren't solely in the machine learning career – data scientists and software engineers should think about taking it too.
Is Google Professional Machine Learning Engineer Worth it for Data Scientists?
For data scientists and data analysts, the Google Professional Machine Learning Engineer is often worth it. Obviously, there are many different "flavors" of data scientists, but generally speaking, your career as an analyst will be improved with a certification that says you understand how to develop machine learning models and how to train them to do the work of dozens, hundreds, and even thousands of other analysts.
Data analysts who earn the Google Professional Machine Learning Engineer find it worth it because when you know how to visualize huge data troves and build your own data pipelines, you can use machine learning and artificial intelligence to speed up your analysis and uncover opportunities you'd never find on your own.
Is Google Professional Machine Learning Engineer Worth it for Software Engineers?
The Google Professional Machine Learning Engineer requires a solid foundation in math and computer science, which is why many software engineers are finding the Google Professional Machine Learning Engineer to be worth it. Earning the cert depends in large part on the skills and knowledge they already have to make themselves successful in software engineering, but it also lets them expand their foundation to include machine learning and artificial intelligence models.
ML and AI depend on a ton of different languages like C++, Java, Python, R, Lisp, and Prolog, and since so many software engineers are already developing in those languages, machine learning engineering is often a short step away.
Is Google Professional Machine Learning Engineer Worth it for a Machine Learning Engineer?
Yes, the Google Professional Machine Learning Engineer is definitely worth it for someone who's already working as a machine learning engineer – or someone who wants to eventually become one. Since the Professional Machine Learning Engineer exam tests you in equal parts on developing, training and improving ML models as well as the Google Cloud products and services that enhance and enable those models, it's a great certification if your network depends on Google products.
Google certainly isn't the only name in the ML/AI world, but it's one of the leaders, and with this certification you prove that you have a mastery of their tools and services that can unlock unprecedented big data solutions for unique business concerns.
Is the Google Professional Machine Learning Engineer Worth It?
Yes, for people who are already invested heavily in the machine learning world, the Google Professional Machine Learning Engineer is definitely worth it. It's too advanced of certification for newcomers to the complex math, programming, and problem-solving that goes into ML/AI, but for people looking to solidify their resume with a Google-sponsored certification or round out their skills and experience in machine learning, it's a great certification.
Using Google Professional Machine Learning Engineer to Learn Skills
The Google Professional Machine Learning Engineer tests six distinct skills that a machine learning engineer must have to be successful, and in each case, it also tests their familiarity with Google Cloud services that enhance them.
Do you know how to translate a challenge your business faces into a formal ML problem, then define its success criteria and design a reliable, scalable and highly available ML solution that will make the best use of its hardware and architecture? Are you sure you can build ML models and then train them with a wide array of different file types, then test them and scale them up and down? Are you sure your training pipelines will implement without any problems and that you can track and audit the metadata that comes off your pipeline runs?
If you feel even a little shaky on any of those skills, then preparing for the Google Professional Machine Learning Engineer exam is a perfect way to master them.
Using Google Professional Machine Learning Engineer to Validate Skills
The right company is willing to pay an arm and a leg to the IT engineer who can develop an AI that solves their problems for them and anticipates their needs. The Google Professional Machine Learning Engineer is a certification that says to an employer that as far as Google is concerned, there's nothing ML or AI that you don't know how to manage. That's a strong endorsement and can lead to jobs, promotions, and interesting jobs.
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