Sonal Awate
회원 가입일: 2022
다이아몬드 리그
39008포인트
회원 가입일: 2022
이 과정은 Google Cloud 기본 개념 과정 이상의 지식을 얻기 위해 실무형 실습을 찾는 초보 클라우드 개발자에게 도움이 됩니다. 실습을 통해 Cloud Storage와 Monitoring 및 Cloud Functions 등 기타 주요 애플리케이션 서비스를 자세히 살펴보며 실무 경험을 쌓게 됩니다. 모든 Google Cloud 이니셔티브에 적용할 수 있는 유용한 기술을 개발할 수 있습니다.
This course explores how to implement a streaming analytics solution using Pub/Sub.
This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Cloud Data Fusion.
Welcome to Migrate Workflows, where we discuss how to migrate Spark and Hadoop tasks and workflows to Google Cloud.
Initial deployment of Vertex AI Search and Google Agentspace apps takes only a few clicks, but getting the configurations right can elevate a deployment from a basic off-the-shelf app to an excellent custom search or recommendations experience. In this course, you'll learn more about the many ways you can customize and improve search, recommendations, and Google Agentspace apps.
AI Applications provides built-in analytics for your Vertex AI Search and Google Agentspace apps. Learn what metrics are tracked and how to view them in this course.
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.
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 few of the G…
In this course, we introduce you to Google Chat, Google’s chat software included with Google Workspace. You will learn about messaging individuals and groups in Google Chat. You will also discover customization options, collaboration features and how Google Chat integrates with other Google Workspace products. We will explore the use of spaces in Google Chat, showing you how to create, manage, search, and join them. Additionally, you will understand the distinctions between using a space and a group chat. You also explore Google Chat apps and learn how to search for and use apps within Google Chat. Aside from course videos, you will complete hands-on activities to practice what you’ve learned. Consider inviting a colleague or two to interact with you in Google Chat as you complete the activities.
Migration from Oracle to Cloud Spanner using HarbourBridge. This course describes an example scenario that uses sample data during the migration. This process includes using HarbourBridge for Assessment, Schema Conversion, Schema Transformation, Data Migration, and supporting tools for data validation.
This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from Oracle to Cloud SQL using the Ora2Pg. An example scenario using sample data will be used to demonstrate the migration. Learners will complete an assessment quiz that focuses on the process of transferring schema, data and related processes to corresponding Google Cloud products.
This course equips learners with skills to govern data within their Google Workspace environment. Learners will explore data loss prevention rules in Gmail and Drive to prevent data leakage. They will then learn how to use Google Vault for data retention, preservation, and retrieval purposes. Next, they will learn how to configure data regions and export settings to align with regulations. Finally, learners will discover how to classify data using labels for enhanced organization and security.
Moving to the cloud creates numerous opportunities to start working in a new way and it empowers the workforce to better collaborate and innovate. But it’s also a big change. Sometimes the success of the change hinges not on the change itself, but on how it’s managed. This course will help people managers to understand some of the key challenges associated with cloud adoption, and provide them with a verified in-the-field framework that will assist them in supporting their teams on the change journey. By addressing the human factor of moving to the cloud, organizations increase their chances of realizing business objectives and investing in their future talent.
이 과정은 입문용 마이크로 학습 과정으로, 대규모 언어 모델(LLM)이란 무엇이고, LLM을 활용할 수 있는 사용 사례로는 어떤 것이 있으며, 프롬프트 조정을 사용해 LLM 성능을 개선하는 방법은 무엇인지 알아봅니다. 또한 자체 생성형 AI 앱을 개발하는 데 도움이 되는 Google 도구에 대해서도 다룹니다.
책임감 있는 AI란 무엇이고 이것이 왜 중요하며 Google에서는 어떻게 제품에 책임감 있는 AI를 구현하고 있는지 설명하는 입문용 마이크로 학습 과정입니다. Google의 7가지 AI 원칙도 소개합니다.
Migration from MySQL to Cloud Spanner using Dataflow that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.
This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from five products hosted on Cloudera or Hortonworks to corresponding Google Cloud services and hosted products. The migration solutions addressed will be: HDFS data to Google Cloud Dataproc and Cloud Storage Hive data to Cloud Dataproc and the Cloud Dataproc Metastore Hive data to Google Cloud BigQuery Impala data to Google Cloud BigQuery HBase to Google Cloud Bigtable Sample data will be used during all five migrations. Learners will complete several labs that focus on the process of transferring schema, data and related processes to corresponding Google Cloud products.There will be one or more challenge labs that will test the learners understanding of the topics.
This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.
Actifio GO for Google Cloud is a SaaS offering which enables powerful enterprise class backup and recovery for Google Cloud resident and on-premises workloads. Actifio now supports backup, disaster recovery and rapid database cloning of Oracle on Bare Metal Solution on Google Cloud besides other enterprise workloads including SAP HANA, SQL Server, and others. This course provides a deep dive into at the preparation and deployment of the Actifio GO solution and its constituent components. Each module contains demos and explanations of each component. The Actifio GO training was originally designed for and only made available to Google Teams, however we’ve recognized how beneficial it would be for our Partners and are now offering our Partners exclusive access to the Actifio training and products, so they can benefit from the demos and best practices and bring them to their Google Cloud Customers.
This workload aims to upskill Google Cloud partners to perform specific tasks associated with priority workloads. Learners will perform the tasks of migrating data from PostgreSQL to CloudSQL using the Database Migration Service.
This course aims to upskill Google Cloud partners to perform specific tasks of migrating data from Microsoft SQL Server to CloudSQL using the built-in replication capabilities of SQL Server. Sample data will be used during the migration. Learners will complete several labs that focus on the process of transferring schema, data, and related processes to corresponding Google Cloud products. One or more challenge labs will test the learner's understanding of the topics.
Migration from MySQL to Cloud SQL using Database Migration Service that includes sample mock data and all necessary steps with initial assessment to validation including taking care of migrating users and grants.
This course discusses the key elements of Google's Data Warehouse solution portfolio and strategy.
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.
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.
이 과정은 Transformer 아키텍처와 BERT(Bidirectional Encoder Representations from Transformers) 모델을 소개합니다. 셀프 어텐션 메커니즘 같은 Transformer 아키텍처의 주요 구성요소와 이 아키텍처가 BERT 모델 빌드에 사용되는 방식에 관해 알아봅니다. 또한 텍스트 분류, 질문 답변, 자연어 추론과 같이 BERT를 활용할 수 있는 다양한 작업에 대해서도 알아봅니다. 이 과정은 완료하는 데 대략 45분이 소요됩니다.
이 과정은 기계 번역, 텍스트 요약, 질의 응답과 같은 시퀀스-투-시퀀스(Seq2Seq) 작업에 널리 사용되는 강력한 머신러닝 아키텍처인 인코더-디코더 아키텍처에 대한 개요를 제공합니다. 인코더-디코더 아키텍처의 기본 구성요소와 이러한 모델의 학습 및 서빙 방법에 대해 알아봅니다. 해당하는 실습 둘러보기에서는 TensorFlow에서 시를 짓는 인코더-디코더 아키텍처를 처음부터 간단하게 구현하는 코딩을 해봅니다.
이 과정에서는 신경망이 입력 시퀀스의 특정 부분에 집중할 수 있도록 하는 강력한 기술인 주목 메커니즘을 소개합니다. 주목 메커니즘의 작동 방식과 이 메커니즘을 다양한 머신러닝 작업(기계 번역, 텍스트 요약, 질문 답변 등)의 성능을 개선하는 데 활용하는 방법을 알아봅니다.
This course aims to introduce you to the basic concepts of Git: what it is and how it's used in Looker. You will also develop an in-depth knowledge of the caching process on the Looker platform, such as why they are used and why they work
This course provides an iterative approach to plan, build, launch, and grow a modern, scalable, mature analytics ecosystem and data culture in an organization that consistently achieves established business outcomes. Users will also learn how to design and build a useful, easy-to-use dashboard in Looker. It assumes experience with everything covered in our Getting Started with Looker and Building Reports in Looker courses.
By the end of this course, you should be able to articulate Looker's value propositions and what makes it different from other analytics tools in the market. You should also be able to explain how Looker works, and explain the standard components of successful service delivery.
This course provides an introduction to databases and summarized the differences in the main database technologies. This course will also introduce you to Looker and how Looker scales as a modern data platform. In the lessons, you will build and maintain standard Looker data models and establish the foundation necessary to learn Looker's more advanced features.
데이터 파이프라인의 두 가지 주요 구성요소는 데이터 레이크와 웨어하우스입니다. 이 과정에서는 스토리지 유형별 사용 사례를 살펴보고 Google Cloud에서 사용 가능한 데이터 레이크 및 웨어하우스 솔루션을 기술적으로 자세히 설명합니다. 또한 데이터 엔지니어의 역할, 성공적인 데이터 파이프라인이 비즈니스 운영에 가져오는 이점, 클라우드 환경에서 데이터 엔지니어링을 수행해야 하는 이유도 알아봅니다. 'Google Cloud의 데이터 엔지니어링' 시리즈의 첫 번째 과정입니다. 이 과정을 완료한 후 'Google Cloud에서 일괄 데이터 파이프라인 빌드하기' 과정에 등록하세요.