Practice tests package
In this practice test, you will find 110 practice questions similar to the ones you will find in the official exams. They are based on official Google Cloud Platform: Machine learning Engineer exams and they contain a full explanation of the answers. In addition, we provide a link to the official Google cloud documentation for further research of the answer.
By buying this practice test you will get:
1. Lifetime access to updated questions based on the official Google Cloud syllabus
2. Active support from experts and a huge pool of students
3. Full explanation on the answers
A Professional Machine Learning Engineer designs builds, and productions ML models to solve business challenges using Google Cloud technologies and knowledge of proven ML models and techniques. ML Engineers consider responsible AI throughout the ML development process and collaborate closely with other job roles to ensure the long-term success of models. They should be proficient in all aspects of model architecture, data pipeline interaction, and metrics interpretation, as well as familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models, the ML Engineer designs and creates scalable solutions for optimal performance.
The Professional Machine Learning Engineer exam assesses your ability to:
Frame ML problems
Architect ML solutions
Design data preparation and processing systems
Develop ML models
Automate and orchestrate ML pipelines
Monitor, optimize, and maintain ML solutions
This learning path is designed to help you prepare for the Google Certified Professional Machine Learning Engineer exam. Even if you don't plan to take the exam, these courses will help you gain a solid understanding of how to implement machine learning on the Google Cloud Platform. Candidates who pass the exam will earn the Google Professional Machine Learning Engineer certification.
The Professional Machine Learning Engineer exam tests your knowledge of six subject areas.
Learning Objectives
Frame machine learning problems
Design a machine learning solution architecture
Prepare and process data
Develop machine learning models
Automate and orchestrate machine learning pipelines
Monitor, optimize, and maintain machine learning solutions
What does it take to earn the Google Certified Professional Machine Learning Engineer certification?
To earn this certification, you will need to enroll and pass the GCP Professional Machine Learning Engineer certification exam by securing a minimum of 70%. The exam features multiple-choice and multiple-select question formats with 2 hours of time duration. This exam is available in English.
Benefits
Cloud ML Engineer: If you wish to become a successful cloud ML engineer and provide ML-based solutions on any cloud or specifically GCP then this GCP Professional Machine Learning Engineer certification is a must-have for you.
Future Skills: You will gain enormous knowledge of cloud, ML, and AI concepts to demonstrate and provide organizations with scalable and long-term solutions by gaining expertise in these revolutionary domains.
Career Growth: You will become the most sought-after professional ML engineer and land a job role with an average of a 35% salary hike.
Sectoral Exposure: You can use the GCP ML skills to work across different job roles and different sectors such as IT, banking, healthcare, manufacturing, and so on.
What is the exam type?
Multiple Choice and Multiple Select
What is the exam Fee?
The exam costs $200.
Eligibility/Pre-Requisite
None
Exam Languages
English
Exam Duration
120 Minutes
