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Google Cloud Platform Machine Learning Engineer - Practice test: 110 Practice questions with answers and full examplanation. Reference to Google Cloud Platform documentation
A Professional Machine Learning Engineer designs, builds, and productionizes 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 collaborates closely with other job roles to ensure 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
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 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.
The Professional Machine Learning Engineer exam assesses your ability
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 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.
247 pages, Kindle Edition
Published October 28, 2021
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