Google Machine Learning Engineer Certification: A Guide to Exam Preparation and Career Advancement

Nowadays, organizations and businesses choose to hire individuals who automate complex processes and tasks, increase productivity, and reduce costs. 

If you are interested in starting in this field of data science and automated programs, the Google Machine Learning Engineer certification is the first step. 

A complete overview of the Google Machine Learning Engineer Certification

The Google Machine Learning Engineer certification allows you to validate your knowledge and skills as a developer of automated programs to solve business-level problems and challenges with Google Cloud technology and AI techniques.

a. What are the prerequisites of this exam?

  • At least 3 years of industry experience in machine learning or a related field.

  • Proficiency in programming with Python and experience with at least one machine learning framework, such as TensorFlow or PyTorch.

  • Knowledge of machine learning concepts and techniques, such as supervised and unsupervised learning, neural networks, and deep learning.

  • Familiarity with data preprocessing and feature engineering techniques.

  • Understanding of cloud computing platforms and familiarity with Google Cloud Platform tools and services, such as BigQuery, Cloud Storage, and Cloud AI Platform.

It's worth noting that certification requirements may change over time, so it's important to check the official Google Cloud website for the most up-to-date information.

b. What is the structure of this exam?

The exam has a structure of 50-60 multiple-choice questions that will evaluate how you develop AI models, design solutions, frame AI problems, automate and organize pipelines, and how you optimize AI solutions.

c. What does the practice exam version include?

The practice exam includes questions designed to simulate the real exam and thus have a more accurate view of what the exam will be like. These questions are made by IT professionals and are based on the official documentation of the real exam.

d. What does the actual exam version include?

The actual version of the exam includes verified and updated questions every month by IT experts. Google documents are used to manage the actual content of the exam to ensure the trust and updating of the questions. 

e. How to register for the certification exam?

  1. 1

    Log in to Google Cloud website and access your account.

  2. 2

    Search for the Google Machine Learning Engineer certification and click on "Register".

  3. 3

    Select the option to take the exam, either online or in-person at a testing center.

  4. 4

    Choose a date, time, and testing center (if in-person) and confirm payment for the exam.

  5. 5

    Upon completing registration, Kryterion will send you a unique authorization code to take the exams.

f. How much does this certification exam cost? 

The Google Machine Learning Engineer certification exam costs $200 plus applicable taxes.

What are the benefits of eating the Google Machine Learning Engineer Certification?

  • Skill validation 

    You'll be able to demonstrate that you have skills and knowledge about machine learning and process automation. 

  • Job opportunities 

    Having a certification from a recognized company like Google validating your skills, you can apply for high-level positions in companies looking for machine learning engineers. 

  • Knowledge 

    Preparing for your certification will require researching and reinforcing your knowledge, allowing you to grow professionally and acquire new knowledge to put into practice in real-world situations.

  • Curriculum

    Obtaining this certification will help you grow professionally and potentially enhance your curriculum, allowing you more job opportunities.

How to get started with Google Machine Learning Engineer Certification?

  1. 1

    Basic Knowledge 

    To start, you must have a solid foundation and understand the Machine Learning concepts correctly. Investigate everything you need to know about Machine Learning and familiarize yourself with those concepts.

  2. 2

    Statistics and Linear Algebra

    All Machine Learning algorithms are based on these, so it is essential to have knowledge about statistics and linear algebra. If you already have prior knowledge, all you need to do is refresh them and put them into practice.

  3. 3

    Programming Language 

    Having prior or basic knowledge of programming languages used by Google will help you progress faster. It’s recommended to start with Python, as it is easy to understand and is one of the programming languages used by Google.

  4. 4

    Courses and Guides 

    Take online courses and use guides will provide you with a foundation to start with and help you acquire new knowledge or reinforce what you already know.

Great study guides and materials for beginners 

To obtain your Google Machine Learning Engineer certification, there are various online resources available, both free and paid, that will help you expand your knowledge, reinforce your skills, and have a solid foundation to take the exam.

1. Best online courses to further your knowledge

Coursera | Google Cloud Certification: Machine Learning Engineer

With this course, you will learn the necessary skills as a machine learning engineer, understand how to design, build, and deploy ML models and solve challenges using Google Cloud technologies.

This course is 7 months long, with 5 hours per week, and you will receive a certification upon completion.

Google | Fundamentals of Google Cloud Big Data and Machine Learning

This course explores the key processes and components of Google Cloud, introducing you to the big data and machine learning products and services.

You will learn through explanatory videos, official documents, exercises, and tests that will evaluate your acquired knowledge.

2. Helpful Practice Exams to test your skills

Udemy | Google Professional Machine Learning Engineer

It provides you with practice questions and answers that are created to closely match the questions on the real exam. 

When you purchase this course, you'll have lifetime access to 3 practice exams, consisting of 2 exams with 50 questions each and 1 exam with 15 questions, for a total of 115 questions.

Whizlabs | Google Cloud Certified Professional Machine Learning Engineer

You will gain the necessary skills to become a machine learning engineer, learn the framework for AI problem-solving, AI solution architecture, data preparation and processing, and everything that can be presented in the certification exam.

Whizlabs offers you 52 video conferences of 8 hours of content, 1 free 15-question test, and 2 practice exams of 55 questions.

3. Easy to follow Youtube tutorials to watch in 2023


This video tutorial covers what it means to be a machine learning engineer, the roles and responsibilities, mathematics for machine learning, logistic regression, and a series of questions at the end of the video.


This video tutorial covers what machine learning is, how to become a machine learning engineer, machine learning algorithms, the skills of a machine learning engineer, and all the concepts you need to know about this topic.

Strategies to further improve your skills and knowledge of Google Machine Learning

  • Real-world Jobs

    Apply your knowledge and skills in real-world projects and jobs, which will help you assess your knowledge level.

  • Vertex AI Workbench notebooks

    Use Vertex AI notebooks for experimentation and development, including writing code, starting jobs, running queries, and checking status.

  • Online communities

    Join online communities where you can discuss and clarify doubts with people from around the world who have been working in this field for some time.

  • Programming languages

    Learning the programming languages used by Google will give you an advantage when starting as a Google machine learning engineer.

What is the future outlook for Machine Learning Engineers at Google?

Artificial intelligence and process automation have been one of the major advances in technology in recent years, but there is still much to be done.

It is expected that the evolution of technology will change the market and increase the demand for these services. 

As one of the leading technology companies, Google will continue to develop more automation services, so it is expected that the company will offer great job opportunities for Machine Learning engineers, which is promising if you are in this field.


Getting your Google Machine Learning Engineer certification will help you grow professionally and advance faster in this field. It will allow you to apply for high-level jobs. 

Keep in mind that organizations are increasingly implementing automated processes, so many job opportunities will arise. With your certification, you will have a higher chance of securing these opportunities.


Is Google machine learning engineer certification worth it?

Yes, certification is worth it if you are interested in entering this field of data science and automated programs.

How do I get into Google Machine Learning?

Learn the basics of Machine Learning, understand statistics and linear algebra, learn programming languages like Python, and learn data processing.

What language does Google use for machine learning?

Google uses Java, C/C++, C#, Python, JavaScript, or Go as languages for machine learning.

What does a Google Machine Learning Engineer do?

A machine learning engineer at Google is responsible for designing, creating, and researching automated systems that perform specific, accurate, and effective tasks.

What is the salary of a Google Certified Machine Learning Engineer?

The salary varies from $85,000 per year in any company, up to $170,000 per year in large companies such as Google, Facebook or Apple.

What is the future of Google Machine Learning?

The future of Google's machine learning is promising, as many organizations are opting to hire machine learning engineers to facilitate complex tasks, increase productivity, and reduce costs.

About the author


Youssef is a Senior Cloud Consultant & Founder of

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