Google Professional Machine Learning Engineer exam [2023]

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New and Exclusive Preparation Course to test your knowledge and help you passing your real Google Professional Machine Learning Engineer exam On the First Try – Save your time and your money with this new and exclusive Exam. So, If you’re looking to test your knowledge, and practice the real exam questions, you are on the right place. About Google Professional Machine Learning Engineer A Professional Machine Learning Engineer builds, evaluates, productionizes, and optimizes ML models by using Google Cloud technologies and knowledge of proven models and techniques. The ML Engineer handles large, complex datasets and creates repeatable, reusable code. The ML Engineer considers responsible AI and fairness throughout the ML model development process, and collaborates closely with other job roles to ensure long-term success of ML-based applications. The ML Engineer has strong programming skills and experience with data platforms and distributed data processing tools. The ML Engineer is proficient in the areas of model architecture, data and ML pipeline creation, and metrics interpretation. The ML Engineer is familiar with foundational concepts of MLOps, application development, infrastructure management, data engineering, and data governance. The ML Engineer makes ML accessible and enables teams across the organization. By training, retraining, deploying, scheduling, monitoring, and improving models, the ML Engineer designs and creates scalable, performant solutions.*Note: The exam does not directly assess coding skill. If you have a minimum proficiency in Python and Cloud SQL, you should be able to interpret any questions with code snippets. The Professional Machine Learning Engineer exam assesses your ability to: Each Practice set contains25 questions from three categories, 60mn durationa balanced number of random questions to cover each category Questions are as per actual exam format A detailed explanation of each correct and incorrect answer Reference diagrams to explain the topic Reference links for further studies In this course, you will learn: Architect low-code ML solutions Scale prototypes into ML models Automate and orchestrate ML pipelines Collaborate within and across teams to manage data and models Serve and scale models Monitor ML solutions The content is 100% original and guaranteed to not be from other sources on the web. Are there any course requirements or prerequisites?There are no requirements. Only your willingness to learn is needed as this test will cover most of the fundamentals in depth! ZERO RISK: If you aren’t IN LOVE with this Exam , Udemy will refund your entire purchase amount within 30 days. NO questions asked! You have nothing to lose and so much to gain!. . . ENROLL NOWGood luck with your practice tests! We are confident that this course will help you achieve your goals and prepare you to pass the actual Google Professional Machine Learning Engineer exam on the first try.