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Rubens de Almeida Zimbres

회원 가입일: 2020

실버 리그

12400포인트
Cloud Hero Kubernetes Skills 배지 Cloud Hero Kubernetes Skills Earned 9월 5, 2023 EDT
Build and Deploy Machine Learning Solutions on Vertex AI 배지 Build and Deploy Machine Learning Solutions on Vertex AI Earned 3월 24, 2023 EDT
Perform Foundational Data, ML, and AI Tasks in Google Cloud 배지 Perform Foundational Data, ML, and AI Tasks in Google Cloud Earned 3월 23, 2023 EDT
ML Pipelines on Google Cloud - 한국어 배지 ML Pipelines on Google Cloud - 한국어 Earned 3월 23, 2023 EDT
Machine Learning Operations (MLOps): Getting Started - 한국어 배지 Machine Learning Operations (MLOps): Getting Started - 한국어 Earned 2월 15, 2023 EST
Recommendation Systems on Google Cloud 배지 Recommendation Systems on Google Cloud Earned 2월 13, 2023 EST
Using the Cloud SDK Command Line 배지 Using the Cloud SDK Command Line Earned 2월 10, 2023 EST
Security & Identity Fundamentals 배지 Security & Identity Fundamentals Earned 2월 10, 2023 EST
Networking Fundamentals in Google Cloud 배지 Networking Fundamentals in Google Cloud Earned 2월 10, 2023 EST
How Google Does Machine Learning - 한국어 배지 How Google Does Machine Learning - 한국어 Earned 2월 10, 2023 EST
Natural Language Processing on Google Cloud 배지 Natural Language Processing on Google Cloud Earned 5월 3, 2022 EDT
Machine Learning in the Enterprise - 한국어 배지 Machine Learning in the Enterprise - 한국어 Earned 4월 23, 2022 EDT
Computer Vision Fundamentals with Google Cloud 배지 Computer Vision Fundamentals with Google Cloud Earned 4월 21, 2022 EDT
Production Machine Learning Systems 배지 Production Machine Learning Systems Earned 4월 12, 2022 EDT
TensorFlow on Google Cloud - 한국어 배지 TensorFlow on Google Cloud - 한국어 Earned 4월 5, 2022 EDT
End-to-End Machine Learning with TensorFlow on Google Cloud 배지 End-to-End Machine Learning with TensorFlow on Google Cloud Earned 3월 30, 2022 EDT
Feature Engineering - 한국어 배지 Feature Engineering - 한국어 Earned 3월 25, 2022 EDT
Launching into Machine Learning - 한국어 배지 Launching into Machine Learning - 한국어 Earned 3월 20, 2022 EDT
How Google Does Machine Learning - 한국어 배지 How Google Does Machine Learning - 한국어 Earned 3월 18, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals - 한국어 배지 Google Cloud Big Data and Machine Learning Fundamentals - 한국어 Earned 3월 16, 2022 EDT
Cloud Engineering 배지 Cloud Engineering Earned 1월 20, 2022 EST
Google Workspace for IT Administrators 배지 Google Workspace for IT Administrators Earned 1월 19, 2022 EST
Planning for a Google Workspace Deployment 배지 Planning for a Google Workspace Deployment Earned 1월 19, 2022 EST
Google Workspace Mail Management 배지 Google Workspace Mail Management Earned 1월 18, 2022 EST
Google Workspace Security 배지 Google Workspace Security Earned 1월 18, 2022 EST
Managing Google Workspace 배지 Managing Google Workspace Earned 1월 17, 2022 EST
Introduction to Google Workspace Administration 배지 Introduction to Google Workspace Administration Earned 1월 14, 2022 EST
Google Sheets - Advanced Topics 배지 Google Sheets - Advanced Topics Earned 1월 13, 2022 EST
Google Meet 배지 Google Meet Earned 1월 13, 2022 EST
Google Slides 배지 Google Slides Earned 1월 12, 2022 EST
Google Sheets 배지 Google Sheets Earned 1월 12, 2022 EST
Google Docs 배지 Google Docs Earned 1월 11, 2022 EST
Google Drive 배지 Google Drive Earned 1월 11, 2022 EST
Google Calendar 배지 Google Calendar Earned 1월 10, 2022 EST
Gmail 배지 Gmail Earned 1월 10, 2022 EST
Preparing for your Professional Cloud Architect Journey 배지 Preparing for your Professional Cloud Architect Journey Earned 10월 23, 2021 EDT
Deploy and Manage Cloud Environments with Google Cloud 배지 Deploy and Manage Cloud Environments with Google Cloud Earned 10월 21, 2021 EDT
Build Infrastructure with Terraform on Google Cloud 배지 Build Infrastructure with Terraform on Google Cloud Earned 10월 20, 2021 EDT
Set up and Configure a Cloud Environment in Google Cloud 배지 Set up and Configure a Cloud Environment in Google Cloud Earned 10월 19, 2021 EDT
Getting Started with Google Kubernetes Engine - 한국어 배지 Getting Started with Google Kubernetes Engine - 한국어 Earned 10월 18, 2021 EDT
Reliable Google Cloud Infrastructure: Design and Process - 한국어 배지 Reliable Google Cloud Infrastructure: Design and Process - 한국어 Earned 10월 16, 2021 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation - 한국어 배지 Elastic Google Cloud Infrastructure: Scaling and Automation - 한국어 Earned 10월 11, 2021 EDT
Essential Google Cloud Infrastructure: Core Services - 한국어 배지 Essential Google Cloud Infrastructure: Core Services - 한국어 Earned 10월 10, 2021 EDT
Essential Google Cloud Infrastructure: Foundation - 한국어 배지 Essential Google Cloud Infrastructure: Foundation - 한국어 Earned 10월 9, 2021 EDT
[DEPRECATED] Secure Workloads in Google Kubernetes Engine 배지 [DEPRECATED] Secure Workloads in Google Kubernetes Engine Earned 10월 8, 2021 EDT
Perform Foundational Infrastructure Tasks in Google Cloud 배지 Perform Foundational Infrastructure Tasks in Google Cloud Earned 10월 5, 2021 EDT
Implement Cloud Security Fundamentals on Google Cloud 배지 Implement Cloud Security Fundamentals on Google Cloud Earned 10월 3, 2021 EDT
Mitigating Security Vulnerabilities on Google Cloud 배지 Mitigating Security Vulnerabilities on Google Cloud Earned 10월 3, 2021 EDT
Security Best Practices in Google Cloud 배지 Security Best Practices in Google Cloud Earned 10월 3, 2021 EDT
Managing Security in Google Cloud 배지 Managing Security in Google Cloud Earned 9월 28, 2021 EDT
Build a Secure Google Cloud Network 배지 Build a Secure Google Cloud Network Earned 9월 27, 2021 EDT
Networking in Google Cloud: Hybrid Connectivity and Network Management 배지 Networking in Google Cloud: Hybrid Connectivity and Network Management Earned 9월 25, 2021 EDT
Networking in Google Cloud: Defining and Implementing Networks 배지 Networking in Google Cloud: Defining and Implementing Networks Earned 9월 24, 2021 EDT
Implement Load Balancing on Compute Engine 배지 Implement Load Balancing on Compute Engine Earned 9월 22, 2021 EDT
Google Cloud Fundamentals: Core Infrastructure - 한국어 배지 Google Cloud Fundamentals: Core Infrastructure - 한국어 Earned 9월 21, 2021 EDT

Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.

자세히 알아보기

Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions with Vertex AI course, where you will learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models. This skill badge course is for professional Data Scientists and Machine Learning Engineers. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.

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이 퀘스트를 완료하고 나면 어떤 Google Cloud 이니셔티브에도 적용할 수 있는 유용한 기술을 얻을 수 있습니다. 마지막에 제시되는 챌린지 실습을 포함해 이 퀘스트를 완료하면 특별한 Google Cloud 디지털 배지가 주어집니다. 1분 정도의 동영상을 통해 실습의 주요 개념을 알아볼 수 있습니다.

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이 과정에서는 Google Cloud에서 최신 ML 파이프라인 개발을 담당하는 ML 엔지니어와 트레이너로부터 유익한 지식을 배웁니다. 초반에 진행되는 몇 개 모듈에서는 Google의 TensorFlow 기반 프로덕션 머신러닝 플랫폼으로서 ML 파이프라인과 메타데이터를 관리할 수 있는 TensorFlow Extended(TFX)에 대해 다룹니다. 파이프라인 구성요소와 TFX를 사용한 파이프라인 조정을 알아봅니다. 지속적 통합과 지속적 배포를 통해 파이프라인을 자동화하는 방법과 ML 메타데이터를 관리하는 방법도 배웁니다. 그런 다음 주제를 전환하여 TensorFlow, PyTorch, scikit-learn, xgboost 등 여러 ML 프레임워크에서 ML 파이프라인을 자동화하고 재사용하는 방법을 설명합니다. 또한 Google Cloud의 또 다른 도구인 Cloud Composer를 사용하여 지속적 학습 파이프라인을 조정하는 방법도 알아봅니다. 마지막으로 MLflow를 사용하여 머신러닝의 전체 수명 주기를 관리하는 방법을 살펴봅니다.

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이 과정에서는 Google Cloud에서 프로덕션 ML 시스템 배포, 평가, 모니터링, 운영을 위한 MLOps 도구와 권장사항을 소개합니다. MLOps는 프로덕션에서 ML 시스템을 배포, 테스트, 모니터링, 자동화하는 방법론입니다. 머신러닝 엔지니어링 전문가들은 배포된 모델의 지속적인 개선과 평가를 위해 도구를 사용합니다. 이들이 협력하거나 때론 그 역할을 하는 데이터 과학자는 고성능 모델을 빠르고 정밀하게 배포할 수 있도록 모델을 개발합니다.

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In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

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For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.

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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.

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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This quest will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Networking Fundamentals in the Google Cloud will give you the practical experience needed so you can start building robust networks right away.

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Google Cloud에서 머신러닝을 구현하기 위한 권장사항에는 어떤 것이 있을까요? Vertex AI란 무엇이고, 이 플랫폼을 사용하여 코드는 한 줄도 작성하지 않고 AutoML 머신러닝 모델을 빠르게 빌드, 학습, 배포하려면 어떻게 해야 할까요? 머신러닝이란 무엇이며 어떤 종류의 문제를 해결할 수 있을까요? Google은 머신러닝을 조금 다른 방식으로 바라봅니다. Google이 머신러닝과 관련하여 중요하게 생각하는 것은 관리형 데이터 세트를 위한 통합 플랫폼과 특징 저장소를 제공하고, 코드를 작성하지 않고도 머신러닝 모델을 빌드, 학습, 배포할 방법을 제공하고, 데이터에 라벨을 지정하고, TensorFlow, scikit-learn, Pytorch, R 등과 같은 프레임워크를 사용하여 Workbench 노트북을 만들 수 있도록 지원하는 것입니다. Google의 Vertex AI 플랫폼에는 커스텀 모델을 학습시키고, 구성요소 파이프라인을 빌드하고, 온라인 및 일괄 예측을 실행하는 기능이 포함되어 있습니다. 후보 사용 사례를 머신러닝으로 구동되도록 변환하는 5단계를 살펴보고, 단계를 건너뛰지 않는 것이 중요한 이유를 알아봅니다. 마지막으로, 머신러닝이 증폭시킬 수 있는 편향과 이를 인식할 방법을 살펴봅니다.

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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.

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이 과정에서는 다양한 ML 비즈니스 요구사항과 사용 사례를 다루는 ML팀의 우수사례를 중심으로 ML 워크플로에 대한 실용적이고 현실적인 접근 방식을 포괄적으로 소개합니다. 이 팀은 데이터 관리 및 거버넌스에 필요한 도구를 이해하고, Dataflow 및 Dataprep에 대한 개괄적인 지식과 BigQuery를 사용한 사전 처리 작업 등을 바탕으로 데이터 사전 처리를 위한 가장 효과적인 접근 방식을 검토해야 합니다. 팀은 두 가지 구체적인 사용 사례에 맞는 머신러닝 모델을 빌드하는 세 가지 옵션을 제공합니다. 이 과정에서는 팀이 목표 달성을 위해 AutoML, BigQuery ML 또는 커스텀 학습을 사용해야 하는 이유를 설명합니다. 커스텀 학습에 대해서도 자세히 설명합니다. 학습 코드 구조, 스토리지, 대용량 데이터 세트 로드에서 학습된 모델 내보내기에 이르기까지 커스텀 학습 요구사항을 설명합니다. Docker에 대한 지식이 거의 없어도 컨테이너 이미지를 빌드할 수 있는 커스텀 학습 머신러닝 모델을 빌드합니다. 우수사례팀에서 Vertex Vizier를 사용한 초매개변수 조정과 모델 성능을 개선하는 데 이를 어떻게 활용할 수 있는지 연구합니다. 모델 개선에 대한 이해를 높이기 위해 정규화와 희소성 처리, 그 외 많은 중요한 개념과 원칙 등 이론적인 내용도 자세히 살펴봅니다. 마지막으로 예측 및 모델 모니터링을 개략적으로 설명하고 Vertex AI를 사용하여 ML 모델을 관리하는 방법을 알아봅니다.

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This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models. The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data. The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models. Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.

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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

자세히 알아보기

이 과정에서는 TensorFlow 2.x 입력 데이터 파이프라인 빌드, TensorFlow 2.x 및 Keras를 사용한 ML 모델 빌드, ML 모델의 정확성 개선, 사용 사례 확장을 위한 ML 모델 작성, 전문 ML 모델 작성에 대해 다룹니다.

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One of the best ways to review something is to work with the concepts and technologies that you have learned. So, this course is set up as a workshop and in this workshop, you will do End-to-End Machine Learning with TensorFlow on Google Cloud Platform. It involves building an end-to-end model from data exploration all the way to deploying an ML model and getting predictions from it. This is the first course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Production Machine Learning Systems course.

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Vertex AI Feature Store에 관해 알고 싶으신가요? ML 모델의 정확성을 개선할 방법을 알고 싶으신가요? 어떤 데이터 열에서 가장 유용한 특성이 나오는지 파악하려면 어떻게 해야 할까요? 특성 추출 과정에서는 좋은 특성과 나쁜 특성을 살펴보고 모델에서 이러한 특성을 적절하게 활용할 수 있도록 사전 처리하고 변환하는 방법을 알아봅니다. 이 과정은 BigQuery ML, Keras, TensorFlow를 사용한 특성 추출에 관한 콘텐츠와 실습이 포함되어 있습니다.

자세히 알아보기

이 과정에서는 먼저 데이터에 관해 논의하면서 데이터 품질을 개선하고 탐색적 데이터 분석을 수행하는 방법을 알아봅니다. Vertex AI AutoML과 코드를 한 줄도 작성하지 않고 ML 모델을 빌드하고, 학습시키고, 배포하는 방법을 설명합니다. 학습자는 Big Query ML의 이점을 이해할 수 있습니다. 그런 다음, 머신러닝(ML) 모델 최적화 방법과 일반화 및 샘플링으로 커스텀 학습용 ML 모델 품질을 평가하는 방법을 다룹니다.

자세히 알아보기

Google Cloud에서 머신러닝을 구현하기 위한 권장사항에는 어떤 것이 있을까요? Vertex AI란 무엇이고, 이 플랫폼을 사용하여 코드는 한 줄도 작성하지 않고 AutoML 머신러닝 모델을 빠르게 빌드, 학습, 배포하려면 어떻게 해야 할까요? 머신러닝이란 무엇이며 어떤 종류의 문제를 해결할 수 있을까요? Google은 머신러닝을 조금 다른 방식으로 바라봅니다. Google이 머신러닝과 관련하여 중요하게 생각하는 것은 관리형 데이터 세트를 위한 통합 플랫폼과 특징 저장소를 제공하고, 코드를 작성하지 않고도 머신러닝 모델을 빌드, 학습, 배포할 방법을 제공하고, 데이터에 라벨을 지정하고, TensorFlow, scikit-learn, Pytorch, R 등과 같은 프레임워크를 사용하여 Workbench 노트북을 만들 수 있도록 지원하는 것입니다. Google의 Vertex AI 플랫폼에는 커스텀 모델을 학습시키고, 구성요소 파이프라인을 빌드하고, 온라인 및 일괄 예측을 실행하는 기능이 포함되어 있습니다. 후보 사용 사례를 머신러닝으로 구동되도록 변환하는 5단계를 살펴보고, 단계를 건너뛰지 않는 것이 중요한 이유를 알아봅니다. 마지막으로, 머신러닝이 증폭시킬 수 있는 편향과 이를 인식할 방법을 살펴봅니다.

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이 과정에서는 데이터-AI 수명 주기를 지원하는 Google Cloud 빅데이터 및 머신러닝 제품과 서비스를 소개합니다. Google Cloud에서 Vertex AI를 사용하여 빅데이터 파이프라인 및 머신러닝 모델을 빌드하는 프로세스, 문제점 및 이점을 살펴봅니다.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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In this quest, you will gain hands-on experience on several topics in Google Workspace Administration including security, provisioning users and groups, managing applications, and managing Google Meet.

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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series. In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area. You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training. This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.

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Google Workspace Mail Management is the fourth course in the Google Workspace Administration series. In this course you will learn how to protect your organization against spam, spoofing, phishing and malware attacks. You will configure email compliance and learn how to implement data loss prevention (DLP) for your organization. You will gain an understanding of the mail routing options available and learn how to allowlist and block senders. You will also become familiar with other mail options such as inbound and outbound gateways, 3rd party email archiving, and journaling to Vault.

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Google Workspace Security is the third course in the Google Workspace Administration series. In this course you will focus on the various aspects of Google Workspace Security including user password policies and how to enable and enforce two step verification (2SV) for your users. You will learn about application security and understand how to whitelist and block API access to your account. You will see how Google Workspace can easily be integrated with a number of predefined 3rd party applications. You will also become familiar with the SSO options in Google Workspace. Finally you will understand how to spot potential security risks within your organization and learn how to address them using the tools available in the admin console.

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Managing Google Workspace is the second course in the Google Workspace Administration series. This course focuses on the Google Workspace core services such as Gmail, Calendar, and Drive & Docs. You will become familiar with the various service settings, and learn how to enable them for all or just a subset of your users. You will gain an understanding of Google Vault, Google’s ediscovery service. You will understand the various admin console reports that are available and be able to search and filter the information in these reports. Finally you will see how multiple domains can be used with Google Workspace and learn how to add a new domain to your account.

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Introduction to Google Workspace Administration is the first course in the Google Workspace Administration series of courses. This series will serve as the starting place for any new Google Workspace admin as they begin their journey of managing and establishing Google Workspace best practices for their organization. These courses together will leave you feeling confident to utilize the basic functions of the admin console to manage users, control access to services, configure security settings, and much more. Through a series of readings and step-by-step hands-on exercises, and knowledge checks, learners can expect to leave this training with all of the skills they need to get started as Google Workspace administrators. In this course you will sign up for a Google Workspace account and configure your DNS records for Google Workspace. You will learn how to provision and manage your users, and will create groups and calendar resources for your organization. You will be introduced to …

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This course builds on some of the concepts covered in the earlier Google Sheets course. In this course, you will learn how to apply and customize themes In Google Sheets, and explore conditional formatting options. You will learn about some of Google Sheets’ advanced formulas and functions. You will explore how to create formulas using functions, and you will also learn how to reference and validate your data in a Google Sheet. Spreadsheets can hold millions of numbers, formulas, and text. Making sense of all of that data can be difficult without a summary or visualization. This course explores the data visualization options in Google Sheets, such as charts and pivot tables. Google Forms are online surveys used to collect data and provide the opportunity for quick data analysis. You will explore how Forms and Sheets work together by connecting collected Form data to a spreadsheet, or by creating a Form from an existing spreadsheet.

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In this course, we introduce you to Google Meet, Google’s video conference software included with Google Workspace. You learn how to create and manage video conference meetings using Google Meet. You explore different ways to open Google Meet and add people to a video conference. You also learn how to join meetings from different sources like calendar events or meeting links. We discuss how Google Meet can help you better communicate, exchange ideas, and share resources with your team wherever they are. You learn how to customize the Google Meet environment to fit your needs and how to effectively use chat messages during a video conference. You also explore different ways to share resources, such as by using calendar invites or attachments. You learn about using host controls in Google Meet to manage participants and utilize interactive moderation features. You also learn how to record and live stream video conferences.

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With Google Slides, you can create and present professional presentations for sales, projects, training modules, and much more. Google Slides presentations are stored safely in the cloud. You build presentations right in your web browser—no special software is required. Even better, multiple people can work on your slides at the same time, you can see people’s changes as they make them, and every change is automatically saved. You will learn how to open Google Slides, create a blank presentation, and create a presentation from a template. You will explore themes, layout options, and how to add and format content, and speaker notes in your presentations. You will learn how to enhance your slides by adding tables, images, charts, and more. You will also learn how to use slide transitions and object animations in your presentation for visual effects. We will discuss how to organize slides and explore some of the options, including duplicating and ordering your slides, importi…

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In this course we will introduce you to Google Sheets, Google’s cloud-based spreadsheet software, included with Google Workspace. With Google Sheets, you can create and edit spreadsheets directly in your web browser—no special software is required. Multiple people can work simultaneously, you can see people’s changes as they make them, and every change is saved automatically. You will learn how to open Google Sheets, create a blank spreadsheet, and create a spreadsheet from a template. You will add, import, sort, filter and format your data using Google Sheets and learn how to work across different file types. Formulas and functions allow you to make quick calculations and better use your data. We will look at creating a basic formula, using functions, and referencing data. You will also learn how to add a chart to your spreadsheet. Google Sheets spreadsheets are easy to share. We will look at the different ways you can share with others. We will also discuss how to track changes…

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With Google Docs, your documents are stored in the cloud, and you can access them from any computer or device. You create and edit documents right in your web browser; no special software is required. Even better, multiple people can work at the same time, you can see people’s changes as they make them, and every change is saved automatically. In this course, you will learn how to open Google Docs, create and format a new document, and apply a template to a new document. You will learn how to enhance your documents using a table of contents, headers and footers, tables, drawings, images, and more. You will learn how to share your documents with others. We will discuss your sharing options and examine collaborator roles and permissions. You will learn how to manage versions of your documents. Google Docs allows you to work in real time with others on the same document. You will learn how to create and manage comments and action items in your documents. We will review a fe…

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Google Drive is Google’s cloud-based file storage service. Google Drive lets you keep all your work in one place, view different file formats without the need for additional software, and access your files from any device. In this course, you will learn how to navigate your Google Drive. You will learn how to upload files and folders and how to work across file types. You will also learn how you can easily view, arrange, organize, modify, and remove files in Google Drive. Google Drive includes shared drives. You can use shared drives to store, search, and access files with a team. You will learn how to create a new shared drive, add and manage members, and manage the shared drive content. Google Workspace is synonymous with collaboration and sharing. You will explore the sharing options available to you in Google Drive, and you will learn about the various collaborator roles and permissions that can be assigned. You’ll also explore ways to ensure consistency and save time…

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With Google Calendar, you can quickly schedule meetings and events and create tasks, so you always know what’s next. Google Calendar is designed for teams, so it’s easy to share your schedule with others and create multiple calendars that you and your team can use together. In this course, you’ll learn how to create and manage Google Calendar events. You will learn how to update an existing event, delete and restore events, and search your calendar. You will understand when to apply different event types such as tasks and appointment slots. You will explore the Google Calendar settings that are available for you to customize Google Calendar to suit your way of working. During the course you will learn how to create additional calendars, share your calendars with others, and access other calendars in your organization.

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Gmail is Google’s cloud based email service that allows you to access your messages from any computer or device with just a web browser. In this course, you’ll learn how to compose, send and reply to messages. You will also explore some of the common actions that can be applied to a Gmail message, and learn how to organize your mail using Gmail labels. You will explore some common Gmail settings and features. For example, you will learn how to manage your own personal contacts and groups, customize your Gmail Inbox to suit your way of working, and create your own email signatures and templates. Google is famous for search. Gmail also includes powerful search and filtering. You will explore Gmail’s advanced search and learn how to filter messages automatically.

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This course helps learners create a study plan for the PCA (Professional Cloud Architect) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

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이 기본 수준의 퀘스트는 다른 Qwiklab 퀘스트 중에서도 특별합니다. IT 전문가가 Google Cloud 공인 프로페셔널 클라우드 설계자 자격증에 나오는 주제 및 서비스를 직접 실습해 볼 수 있도록 선별된 실습이 제공됩니다. 이 퀘스트는 IAM, 네트워킹, Kubernetes 엔진 배포 등 Google Cloud에 관한 지식을 시험하기 위한 실습으로 구성되어 있습니다. 마지막에 제시되는 챌린지 실습을 포함해 이 퀘스트를 완료하면 특별한 Google Cloud 디지털 배지가 주어집니다. 실습을 통한 연습으로 기술과 능력이 증진되겠지만, 시험 가이드 및 제공되는 다른 준비용 리소스도 검토하는 것이 좋습니다.

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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge course and the final assessment challenge lab to receive a skill badge that you can share with your network.

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이 기본 수준의 퀘스트는 다른 Qwiklab 퀘스트 중에서도 특별합니다. IT 전문가가 Google Cloud 공인 어소시에이트 클라우드 엔지니어 자격증에 나오는 주제 및 서비스를 직접 실습해 볼 수 있도록 선별된 실습이 제공됩니다. 이 퀘스트는 IAM, 네트워킹, Kubernetes 엔진 배포 등 Google Cloud에 관한 지식을 시험하기 위한 실습으로 구성되어 있습니다. 마지막에 제시되는 챌린지 실습을 포함해 이 퀘스트를 완료하면 특별한 Google Cloud 디지털 배지가 주어집니다. 실습을 통한 연습으로 기술과 능력이 증진되겠지만, 시험 가이드 및 제공되는 다른 준비용 리소스도 검토하는 것이 좋습니다.

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Getting Started with Google Kubernetes Engine 과정에 오신 것을 환영합니다. 애플리케이션과 하드웨어 인프라 사이에 위치하는 소프트웨어 레이어인 Kubernetes에 관심이 있으시다면 잘 찾아오셨습니다. Google Kubernetes Engine을 사용하면 Kubernetes를 Google Cloud에서 관리형 서비스로 사용할 수 있습니다. 이 과정의 목표는 흔히 GKE로 불리는 Google Kubernetes Engine의 기본사항을 소개하고 Google Cloud에서 애플리케이션을 컨테이너화하고 실행하는 방법을 설명하는 것입니다. 이 과정에서는 먼저 Google Cloud에 대해 기본적인 사항을 소개한 후 이어서 컨테이너 및 Kubernetes, Kubernetes 아키텍처, Kubernetes 작업에 대해 간략히 설명합니다.

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이 과정에서는 검증된 설계 패턴을 사용하여 Google Cloud에서 고도로 안정적이고 효율적인 솔루션을 빌드하는 데 필요한 역량을 키워줍니다. 'Google Compute Engine을 이용한 아키텍처 설계' 또는 'Google Kubernetes Engine을 이용한 아키텍처 설계' 과정과 이어지는 내용이며, 학습자가 두 과정에서 다루는 기술을 실무에서 사용해 본 경험이 있다는 전제로 진행됩니다. 학습자는 프레젠테이션, 설계 활동, 실습을 통해 고도로 안정적이고 안전하고 비용 효율적이며 가용성이 높은 Google Cloud 배포를 설계하는 데 필요한 비즈니스 요구사항과 기술 요구사항을 정의하고 이 사이의 적절한 균형을 유지하는 방법을 알아봅니다.

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이 속성 주문형 과정에서는 참가자에게 Google Cloud에서 제공하는 포괄적이고 유연한 인프라 및 플랫폼 서비스를 소개합니다. 참가자는 동영상 강의, 데모, 실무형 실습이 결합된 이 과정을 통해 안전한 네트워크 상호 연결, 부하 분산, 자동 확장, 인프라 자동화, 관리형 서비스가 포함된 솔루션 요소를 살펴보고 배포할 수 있습니다.

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이 속성 주문형 과정은 참가자에게 Google Cloud에서 제공하는 포괄적이고 유연한 인프라 및 플랫폼 서비스를 Compute Engine을 중심으로 소개합니다. 참가자는 동영상 강의, 데모, 실무형 실습을 통해 네트워크, 시스템, 애플리케이션 서비스와 같은 인프라 구성요소를 포함한 솔루션 요소를 탐색하고 배포해 볼 수 있습니다. 또한 이 과정에서는 고객 제공 암호화 키, 보안 및 액세스 관리, 할당량 및 요금 청구, 리소스 모니터링 등 실용적인 솔루션을 배포하는 방법에 대해서도 설명합니다.

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이 속성 주문형 과정은 참가자에게 Google Cloud에서 제공하는 포괄적이고 유연한 인프라 및 플랫폼 서비스를 Compute Engine을 중심으로 소개합니다. 참가자는 동영상 강의, 데모, 실무형 실습을 통해 네트워크, 가상 머신, 애플리케이션 서비스와 같은 인프라 구성요소를 포함한 솔루션 요소를 탐색하고 배포해 볼 수 있습니다. Console과 Cloud Shell을 통해 Google Cloud를 사용하는 방법을 학습합니다. 또한 클라우드 설계자의 역할, 인프라 설계 접근 방식은 물론 Virtual Private Cloud(VPC), 프로젝트, 네트워크, 서브네트워크, IP 주소, 경로, 방화벽 규칙을 사용한 가상 네트워킹 구성에 대해 알아봅니다.

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Earn a skill badge by completing the Secure Workloads in Google Kubernetes Engine quest, where you learn about security at scale on Google Kubernetes Engine (GKE) including how to: migrate containers from virtual machines to Google Kubernetes Engine, restrict network connections in GKE using firewalls and Network Policies, use role-based access controls (RBAC) in GKE, use Binary Authorization for security controls of your images, secure applications in GKE using 3 access levels: host, network, Kubernetes API, and harden GKE cluster configurations. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge quest, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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‘시작하기 - 클라우드 리소스 만들기 및 관리하기’ 후에 완료할 실습을 찾고 있는 초보 클라우드 개발자라면 이 퀘스트가 안성맞춤입니다. Cloud Storage 및 Stackdriver와 Cloud Functions와 같은 핵심 애플리케이션 서비스를 자세히 살펴보는 실습을 통해 실무 경험을 쌓게 됩니다. 이 퀘스트를 완료하고 나면 어떤 Google Cloud 이니셔티브에도 적용할 수 있는 유용한 기술을 얻을 수 있습니다. 마지막에 제시되는 챌린지 실습을 포함해 이 퀘스트를 완료하면 특별한 Google Cloud 디지털 배지가 주어집니다. 1분 정도의 동영상을 통해 실습의 주요 개념을 알아볼 수 있습니다.

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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge course, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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In this self-paced training course, participants learn mitigations for attacks at many points in a Google Cloud-based infrastructure, including Distributed Denial-of-Service attacks, phishing attacks, and threats involving content classification and use. They also learn about the Security Command Center, cloud logging and audit logging, and using Forseti to view overall compliance with your organization's security policies.

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Storage access control technologies, Security Keys, Customer-Supplied Encryption Keys, API access controls, scoping, shielded VMs, encryption, and signed URLs. It also covers securing Kubernetes environments.

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This self-paced training course gives participants broad study of security controls and techniques on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy the components of a secure Google Cloud solution, including Cloud Identity, Resource Manager, Cloud IAM, Virtual Private Cloud firewalls, Cloud Load Balancing, Cloud Peering, Cloud Interconnect, and VPC Service Controls. This is the first course of the Security in Google Cloud series. After completing this course, enroll in the Security Best Practices in Google Cloud course.

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Earn a skill badge by completing the Build and Secure Networks in Google Cloud course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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This self-paced training course builds on the Networking in Google Cloud: Defining and Implementing Networks course and enhances the study of networking options on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, you explore and deploy Google Cloud networking technologies, such as common network design patterns, connectivity to Google Cloud VPC networks, and private connection options. The course also covers optimizing network performance and cost by using Network Service Tiers. You will also learn about billing and pricing. The course concludes by covering monitoring and logging features that can help you troubleshoot your Google Cloud network infrastructure.

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This self-paced training course gives participants broad study of networking options on Google Cloud. Through recorded lectures, demonstrations, and hands-on labs, participants explore and deploy Google Cloud networking technologies, such as Google Cloud Virtual Private Cloud (VPC) networks, subnets and firewalls. The course also covers access control to networks, sharing networks and load balancing.

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입문 Implement Load Balancing on Compute Engine 기술 배지 과정을 완료하여 gcloud 명령어 작성 및 Cloud Shell 사용, Compute Engine에서 가상 머신 만들기 및 배포, 네트워크 및 HTTP 부하 분산기 구성에 관한 본인의 기술을 입증하세요. 기술 배지는 Google Cloud 제품 및 서비스에 대한 개인의 숙련도를 인정하기 위해 Google Cloud에서 단독 발급하는 디지털 배지로서 대화형 실습 환경을 통해 지식을 적용하는 역량을 테스트합니다. 이 기술 배지 과정과 최종 평가 챌린지 실습을 완료하면 네트워크에 공유할 수 있는 기술 배지를 받게 됩니다.

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Google Cloud Fundamentals: Core Infrastructure 과정은 Google Cloud 사용에 관한 중요한 개념 및 용어를 소개합니다. 이 과정에서는 동영상 및 실무형 실습을 통해 중요한 리소스 및 정책 관리 도구와 함께 Google Cloud의 다양한 컴퓨팅 및 스토리지 서비스를 살펴보고 비교합니다.

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