원하는 방식의 Google Cloud 교육을 살펴보세요.

Google Cloud에서 개발자를 대상으로 한 700개 이상의 학습 활동을 선택할 수 있는 포괄적인 카탈로그를 설계했습니다. 이 카탈로그는 개발자가 선택할 수 있는 다양한 활동 형식으로 구성되어 있습니다. 짧은 분량의 개별 실습 또는 동영상, 문서, 실습, 퀴즈로 구성된 멀티 모듈 과정 중에서 선택하세요. 실습에서는 실제 클라우드 리소스에 대한 임시 사용자 인증 정보를 제공하므로 실제 리소스를 사용하여 Google Cloud를 알아볼 수 있습니다. 이수한 과정의 배지를 획득하고 Google Cloud 성과를 정의, 추적, 측정하세요.

  • 솔루션
  • 역할
  • 배지
  • 형식
  • 수준
  • 기간
  • 언어

결과 328개

  1. 실습 추천

    Share Data using Google Data Cloud: Challenge Lab

    This challenge lab tests your skills and knowledge from the labs in the Share Data using Google Data Cloud course. Are you ready for the challenge?

  2. 실습 추천

    Visualizing Data with Google Data Studio

    This lab demonstrates how to use Google Data Studio to visualize data stored in Google BigQuery.

  3. 과정 추천

    BigQuery for Marketing Analysts

    Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost…

  4. 실습 추천

    Data Publishing on BigQuery using Authorized Views for Data Sharing Partners

    In this lab you will learn how Authorized Views in BigQuery can be used to share customer specific data from a Data Sharing Partner.

  5. 실습 추천

    Data Catalog: Qwik Start

    In this lab, you explore existing datasets with Data Catalog and mine the table and column metadata for insights.

  6. 과정 추천

    Share Data Using Google Data Cloud

    Earn a skill badge by completing the Share Data Using Google Data Cloud course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platfor…

  7. 과정 추천

    NCAA® March Madness®: Bracketology with Google Cloud

    In this series of labs you will learn how to use BigQuery to analyze NCAA basketball data with SQL. Build a Machine Learning Model to predict the outcomes of NCAA March Madness basketball tournament games.

  8. 실습 추천

    Streaming Data to Bigtable

    In this lab, you launch a Dataflow pipeline to load streaming data from Pub/Sub into Bigtable.

  9. 실습 추천

    Exploring the Lineage of Data with Cloud Data Fusion

    This lab shows how to use Cloud Data Fusion to explore data lineage - the data's origins and its movement over time.

  10. 실습 추천

    Redacting Sensitive Data with Cloud Data Loss Prevention

    In this lab, you inspect strings and files for sensitive data and then practice using the Cloud Data Loss Prevention (DLP) API to protect data.