Why You Should Get Google’s New Machine Learning Certificate
Google is offering a new ML Engineer certificate, geared towards professionals who want to display their competency in topics like distributed model training and scaling to production. Is it worth it?
By Frederik Bussler, Growth Marketing at Apteo
Google has just opened the gates to a new ML Engineer certificate. Before you charge in, bear in mind that this is geared towards professionals who want to display their competency in topics like distributed model training and scaling to production.
Students who don’t have practical work experience would be better served by first doing hands-on projects.
Where to Start
Getting this certificate won’t be easy. In fact, looking at the exam guide, you need very in-depth knowledge in six areas, including highly specialized topics like permission issues, dataset lineage, and data feasibility.
That’s why Google recommends you have 3+ years of experience with GCloud products. If you do fit that profile, then this certificate is extremely valuable for one simple reason. No one has it yet.
To remind you of the most basic lesson in economics: As supply increases, demand decreases.
Intuitively, if there are 1,000 job openings and 600 ML Engineer certificate holders, they’ll have a much easier time landing jobs and getting high salaries than if there were 6,000 or 60,000 certificate holders.
As beta registration just opened, there are now 0 people with this certificate. However, as Google is a leader in AI, cloud computing, and one of the world’s biggest tech companies, it won’t be long until you see these new certifications all over the place.
While it’s great to learn from those courses, and it’s possible that having a certification from them may provide a modest boost in some scenarios, they don’t have nearly the value they did a few years ago.
So, if you’re looking to get into ML Engineering, it’s best not to hesitate on Google’s new opportunity. If you want a more general data science job, check out this guide:
The Uncommon Data Science Job Guide
Data Science is hyper-competitive. Here’s how to win with “blue ocean” strategies.
Note that Google Cloud is not the most popular cloud platform — that award goes to AWS, which has a Machine Learning certificate of its own.
At first glance, career-wise, going with AWS would be the better option. However, if we head to LinkedIn and search for “AWS Certified Machine Learning” (including the quotes), we get almost 2,000 results. Those are only the certified people who (1) have a LinkedIn and (2) bothered to add its exact name to their profile.
Remember from earlier that there’s only a very limited number of ML Engineering jobs to go around, so to be competitive, you’ll want to find a less-explored niche.
With 0 current holders, getting the Google Professional Machine Learning Engineer certificate is a “blue ocean” strategy: It’s a wide, open space without competition. Getting a Coursera certificate is on the extreme other end of the spectrum, and is a “red ocean” strategy: There are millions of other sharks in the water. An AWS certificate lies somewhere in the middle.
More Than Certificates
At the end of the day, it’s important to remember that certificates aren’t everything. In fact, they shouldn’t even be the core of your application — they should be supplemental to a strong profile based on practical skills and experience.
Skip the Certificates, Do This Instead
Create insightful analyses, share your work, and get noticed.
A simple process you can use to spice up your profile is picking a topic you’re interested in, analyzing the associated data, creating insightful visuals and commentary, and sharing it with your network.
The wrong thing to do is just share certificates on social media.
Certificates aren’t the end-all-be-all, but the new Google Professional Machine Learning Engineer certificate is a great option for professionals seeking to advance their careers.
Bio: Frederik Bussler is on a missions to democratize data science. He is in Growth Marketing at Apteo, and has contributed to Forbes, Hacker Noon, Blockgeeks, Thrive Global, KDnuggets, Digital Asset Live, The Tokenizer, Blocklike, Altcoin Magazine, Decentral.news, Forkast.news, Irish Tech News, and more.
Original. Reposted with permission.
- 10 Free Top Notch Machine Learning Courses
- Free Mathematics Courses for Data Science & Machine Learning
- TensorFlow Dev Summit 2020: Top 10 Tricks for TensorFlow and Google Colab Users
Top Stories Past 30 Days