Google Developer Program 프리미엄으로 더 앞서 나가세요. Google을 통해 학습, 빌드, 성장하는 데 도움이 되는 독점 리소스에 액세스하고 기회를 얻을 수 있습니다.
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Professional Machine Learning Engineer
Professional Machine Learning Engineer는 Google Cloud 기능과 기존 ML 접근방식에 대한 지식을 활용하여 AI 솔루션을 빌드, 평가, 프로덕션화, 최적화합니다.
ML Engineer는 크고 복잡한 데이터 세트를 처리하고 반복 가능하며 재사용 가능한 코드를 만듭니다. ML Engineer는 파운데이션 모델을 기반으로 생성형 AI 솔루션을 설계하고 운영합니다. ML Engineer는 책임감 있는 AI 관행을 고려하고 다른 직무 역할과 긴밀히 협력하여 AI 기반 애플리케이션의 장기적인 성공을 보장합니다.
ML Engineer는 강력한 프로그래밍 기술과 데이터 플랫폼 및 분산 데이터 처리 도구에 대한 경험을 보유하고 있습니다.
ML Engineer는 모델 아키텍처, 데이터 및 ML 파이프라인 생성, 생성형 AI, 측정항목 해석 분야에 능숙합니다.
ML Engineer는 MLOps, 애플리케이션 개발, 인프라 관리, 데이터 엔지니어링, 데이터 거버넌스의 기본 개념에 익숙합니다. ML Engineer는 조직 전반의 팀이 AI 솔루션을 사용할 수 있도록 지원합니다. ML Engineer는 모델을 학습, 재학습, 배포, 예약, 모니터링, 개선하여 확장 가능하고 성능이 우수한 솔루션을 설계하고 만듭니다.
*참고: 이 시험은 코딩 기술을 직접적으로 평가하지 않습니다.
Python과 Cloud SQL에 대한 최소한의 숙련도를 갖추고 있다면 코드 스니펫이 포함된 문제를 해석할 수 있습니다.
Professional Machine Learning Engineer 시험은 다음과 같은 능력을 평가합니다.
Machine Learning Engineer 시험에 응시하기 전에 Google Cloud 제품 및 솔루션에 대한 3년 이상의 실무 경험이 있는 것이 좋습니다.
실무 경험을 쌓을 준비가 되셨나요? 일부 제품의 무료 사용량(월 한도 내)을 제공하는 Google Cloud 무료 등급을 살펴보세요.
Google Cloud의 개념 및 중요 구성요소에 대한 심층적인 논의를 위해 Google Cloud 문서를 살펴보세요.
Google Cloud 공인 Professional Machine Learning Engineer 학습 가이드를 사용하여 Google Cloud에서 안전한 ML 애플리케이션을 설계, 학습, 빌드, 배포, 운영하는 방법을 알아보세요.
이 가이드에서는 실제 시나리오를 사용하여 TensorFlow, Kubeflow, AutoML과 같은 Vertex AI 플랫폼 및 기술을 사용하는 방법과 사전 학습된 모델 또는 커스텀 모델을 선택해야 하는 경우에 대한 권장사항을 보여줍니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],[],[],[],null,["# Professional ML Engineer Certification\n\nGo further with Google Developer Program premium tier. Gain access to exclusive resources and opportunities to help you learn, build, and grow with Google. [Explore all benefits](https://developers.google.com/profile/u/me/plans-and-pricing?continue=https%3A%2F%2Fwww.cloudskillsboost.google%2Fsubscriptions). \n- [Back to Google Cloud Certification](/certification) \n\nProfessional Machine\nLearning Engineer\n======================================\n\nA Professional Machine Learning Engineer builds, evaluates,\nproductionizes, and optimizes AI solutions by using\nGoogle Cloud capabilities and knowledge of conventional ML approaches.\nThe ML Engineer handles large, complex datasets and creates repeatable,\nreusable code. The ML Engineer designs and operationalizes generative\nAI solutions based on foundational models. The ML Engineer considers\nresponsible AI practices, and collaborates closely with other\njob roles to ensure the long-term success of AI-based applications.\nThe ML Engineer has strong programming skills and experience with data\nplatforms and distributed data processing tools.\nThe ML Engineer is proficient in the areas of model architecture,\ndata and ML pipeline creation, generative AI, and metrics interpretation.\nThe ML Engineer is familiar with foundational concepts of MLOps,\napplication development, infrastructure management, data engineering,\nand data governance. The ML Engineer enables teams across the organization\nto use AI solutions. By training, retraining, deploying, scheduling, monitoring,\nand improving models, the ML Engineer designs and creates scalable, performant solutions.\n\n\\*Note: The exam does not directly assess coding skill.\nIf you have a minimum proficiency in Python and Cloud\nSQL, you should be able to interpret any questions with\ncode snippets.\n\nThe Professional Machine Learning Engineer exam\nassesses your ability to: \n- Architect low-code AI solutions\n- Collaborate within and across teams to manage data and models\n- Scale prototypes into ML models\n- Serve and scale models\n- Automate and orchestrate ML pipelines\n- Monitor AI solutions \n[Register](https://webassessor.com/googlecloud) [View FAQs](https://support.google.com/cloud-certification/#topic=9433215) \n[Register](https://webassessor.com/googlecloud) [View FAQs](https://support.google.com/cloud-certification/#topic=9433215)\nThis version of the Professional Machine Learning Engineer exam covers tasks related to generative AI, including building AI solutions using Model Garden and Vertex AI Agent Builder, and evaluating generative AI solutions.\n\n\u003cbr /\u003e\n\nTo learn more about Google Cloud's generative AI services,\ngo to Google Cloud Skills Boost to see the\n[Introduction to Generative AI Learning Path](https://www.cloudskillsboost.google/journeys/118)\n(all audiences) or the\n[Generative AI for Developers Learning Path](https://www.cloudskillsboost.google/journeys/183?utm_source=cgc&utm_medium=blog&utm_campaign=learngenai)\n(technical audience). If you are a partner, refer to the Gen\nAI partner courses:\n[Introduction to Generative AI Learning Path](https://partner.cloudskillsboost.google/journeys),\n[Generative AI for ML Engineers](https://partner.cloudskillsboost.google/journeys/164),\nand\n[Generative AI for Developers](https://partner.cloudskillsboost.google/journeys/165).\nFor additional learning, refer to product-specific Gen AI\nlearning offerings, such as\n[Explore and Evaluate Models using Model Garden](https://www.cloudskillsboost.google/focuses/71938?catalog_rank=%7B%22rank%22%3A1%2C%22num_filters%22%3A0%2C%22has_search%22%3Atrue%7D&parent=catalog&search_id=40286199),\n[Vertex AI Agent Builder path](https://partner.cloudskillsboost.google/paths/615)\n(partners), and\n[Integrate Search in Applications using Vertex AI Agent Builder](https://www.cloudskillsboost.google/focuses/71943?parent=catalog). \n\nQuick links\n-----------\n\n- [Train for the exam](https://www.cloudskillsboost.google/paths/17)\n- [Review sample questions](https://docs.google.com/forms/d/e/1FAIpQLSeYmkCANE81qSBqLW0g2X7RoskBX9yGYQu-m1TtsjMvHabGqg/viewform)\n- [View exam guide](https://services.google.com/fh/files/misc/professional_machine_learning_engineer_exam_guide_english.pdf)\n- [Partner training for the exam](https://partner.cloudskillsboost.google/paths/84?utm_source=cgc&utm_medium=website&utm_campaign=evergreen&utm_content=partnertrainingpmle)\n- [Join the learning community](https://www.googlecloudcommunity.com/gc/Learning-Certification-Hub/ct-p/cloud-learning-cert-forums)\n\n*** ** * ** ***\n\nAbout this certification exam\n-----------------------------\n\n**Length**: Two hours\n\n**Registration fee**: $200 (plus tax where\napplicable)\n\n**Languages**: English, Japanese\n\n**Exam format:** 50-60 multiple choice and multiple select\nquestions\n\n**Exam delivery method**:\n\na. Take the online-proctored exam from a remote location,\nreview the online testing\n[requirements](https://www.webassessor.com/wa.do?page=certInfo&branding=GOOGLECLOUD&tabs=13).\n\nb. Take the onsite-proctored exam at a testing center,\n[locate a test center near you](https://www.kryteriononline.com/Locate-Test-Center) \n**Prerequisites**: None\n\n**Recommended experience**: 3+ years of industry\nexperience including 1 or more years designing and managing\nsolutions using Google Cloud.\n\n**Certification renewal:** Candidates may renew their certification\nwithin the renewal eligibility period. For more information about the renewal\nprocess, eligibility period, and certification validity timeline, please refer to\nthe Renewal FAQs below.\n\n\n[Renewal FAQs](https://support.google.com/cloud-certification/answer/9907853?sjid=10159424711448208692-NC) \n\nExam overview\n-------------\n\n#### Step 1: Get real world\nexperience\n\nBefore attempting the Machine Learning Engineer exam,\nit's recommended that you have 3+ years of hands-on\nexperience with Google Cloud products and solutions.\nReady to start building? Explore the Google Cloud Free\nTier for free usage (up to monthly limits) of select\nproducts.\n\n\n[Try the Google Cloud Free Tier](/free)\n\n\u003cbr /\u003e\n\n#### Step 2: Understand what's\non the exam\n\nThe exam guide contains a complete list of topics that\nmay be included on the exam. Review the exam guide to\ndetermine if your skills align with the topics on the\nexam.\n\n\n[See current exam guide](https://services.google.com/fh/files/misc/professional_machine_learning_engineer_exam_guide_english_3.1_final.pdf)\n\n\u003cbr /\u003e\n\n#### Step 3: Review the sample\nquestions\n\nFamiliarize yourself with the format of questions and\nexample content that may be covered on the Machine\nLearning Engineer exam.\n\n\n[Review sample questions](https://docs.google.com/forms/d/e/1FAIpQLSeYmkCANE81qSBqLW0g2X7RoskBX9yGYQu-m1TtsjMvHabGqg/viewform)\n\n\u003cbr /\u003e\n\n#### Step 4: Round out your\nskills with training\n\n\u003cbr /\u003e\n\nPrepare for the exam by following the Machine\nLearning Engineer learning path. Explore online\ntraining, in-person classes, hands-on labs, and\nother resources from Google Cloud.\n\n\u003cbr /\u003e\n\n[Start preparing](https://www.cloudskillsboost.google/paths/17) \n\nPrepare for the exam with Googlers and certified\nexperts. Get valuable exam tips and tricks, as well\nas insights from industry experts.\n\n\u003cbr /\u003e\n\n[Sign up](https://cloudonair.withgoogle.com/events/machine-learning-certification?utm_source=google_owned_website&utm_medium=et&utm_campaign=-&utm_content=cgc-cert-mle) \n\nExplore\n[Google Cloud documentation](/docs)\nfor in-depth discussions on the concepts and\ncritical components of Google Cloud.\n\nLearn about designing, training, building,\ndeploying, and operationalizing secure ML\napplications on Google Cloud using the\n[Official Google Cloud Certified Professional Machine Learning Engineer Study Guide](https://www.wiley.com/en-us/Official+Google+Cloud+Certified+Professional+Machine+Learning+Engineer+Study+Guide-p-9781119944461).\nThis guide uses real-world scenarios to demonstrate\nhow to use the Vertex AI platform and technologies\nsuch as TensorFlow, Kubeflow, and AutoML, as well as\nbest practices on when to choose a pretrained or a\ncustom model.\n\n\u003cbr /\u003e\n\n#### Step 5: Schedule an exam\n\n\n[Register and select](https://webassessor.com/googlecloud)\nthe option to take the exam remotely or at a nearby\ntesting center.\n\n\u003cbr /\u003e\n\nReview exam\n[terms and conditions](https://cloud.google.com/certification/terms)\nand\n[data sharing policies](https://cloud.google.com/certification/data-sharing-policy).\n\n\u003cbr /\u003e\n\n### Take the next step\n\nFollow\nthe learning path \n[Start Learning](https://www.cloudskillsboost.google/paths/17) \n\n### Take the next step\n\nFollow\nthe learning path \n[Start Learning](https://www.cloudskillsboost.google/paths/17) \n- Earn a skill badge in machine learning\n [Start now](https://www.cloudskillsboost.google/catalog?keywords=machine+learning&locale=&skill-badge%5B%5D=skill-badge&format%5B%5D=any&language%5B%5D=any)\n- New to Google Cloud?\n [Get started](/training/getstarted)\n- Take a cert prep webinar\n[Watch Cloud OnAir](https://cloudonair.withgoogle.com/events/machine-learning-certification?utm_source=google_owned_website&utm_medium=et&utm_campaign=-&utm_content=cgc-cert-mle) \n- Earn a skill badge in machine learning\n [Start now](https://www.cloudskillsboost.google/catalog?keywords=machine+learning&locale=&skill-badge%5B%5D=skill-badge&format%5B%5D=any&language%5B%5D=any)\n- New to Google Cloud?\n [Get started](/training/getstarted)\n- Take a cert prep webinar\n [Watch Cloud OnAir](https://cloudonair.withgoogle.com/events/machine-learning-certification?utm_source=google_owned_website&utm_medium=et&utm_campaign=-&utm_content=cgc-cert-mle)"]]
