Businesses are increasingly relying upon machine learning to develop statistical models to make data-informed decisions. As the reliance upon this technology grows, employers will seek out professionals who have a deep understanding of machine learning. The Professional Machine Learning Engineer certification validates an individual’s ability to create and deploy models and algorithms that address real-world business problems.
Candidate Qualification
Candidates for the exam are expected to have at least three years of experience working hands-on with Machine Learning. Candidates are also expected to have at least one year of experience working with Google Cloud Solutions.
Although Machine Learning and generative AI share similar training paths, the exam does not cover any generative AI information. Additionally, candidates are not tested directly on their skill in coding. Still, candidates should have the basic skills required for Python and Cloud SQL in order to do well on the exam.
About the Exam
The exam may take up to two hours to complete. Candidates may only complete the exam in English, and they must answer up to 60 questions. The exam may be taken onsite at a testing center or online, though both options are proctored.
Exam Subjects
The exam covers the building, evaluation, and optimization of Machine Learning models through the use of Google Cloud technology. Specific topics on the exam include:
The Professional Machine Learning Engineer certification will only grow in importance as businesses continue to unlock the potential of Machine Learning. Employers will seek out certified engineers to help direct and deploy AI solutions that foster business growth and encourage greater adaptability. This makes obtaining the certification a valuable asset in the modern job market.
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