원하는 방식의 Google Cloud 교육을 살펴보세요.
Google Cloud에서 개발자를 대상으로 한 980개 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.
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실습 추천 Using Elastic Stack to Monitor Google Cloud
In this lab you will learn how to use the Elastic Stack to monitor Google Cloud Platform.
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실습 추천 Google Calendar: Getting Started
Learn how to use Google Calendar to schedule meetings and events and get reminders about upcoming activities. You can also share your schedule with others and create multiple calendars that you and your team can use together.
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실습 추천 Google Chat Bot - Apps Script
Learn how to create a simple Google Chat bot—"Attendance Bot"—using Google Apps Script. The bot integrates with Gmail to set a user's vacation responder and integrates with Calendar to put a meeting on the user's calendar.
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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.
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실습 추천 Machine Learning with TensorFlow in Vertex AI
In this lab you will learn how to use Google Cloud Machine Learning and Tensorflow to develop and evaluate prediction models using machine learning.
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실습 추천 Introduction to Dart
In this lab you will learn the basics of Dart. Understand how to work with variables, flow control and functions to start your journey with Dart.
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실습 추천 Securing APIs with Apigee X
In this lab, you modify an API to require OAuth tokens for access. You use the SpikeArrest policy to limit the rate of API calls by application, and you use private variables and data masking to hide sensitive data from users who debug API traffic.
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실습 추천 Publishing APIs with Apigee X
In this lab, you use API products to package your APIs, and create a developer portal so application developers can try your APIs and sign up to use them.
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실습 추천 Build a Knowledge Based System with Vertex AI Vector Search, LangChain and Gemini
In this lab, you use Vertex AI Vector Search to index documents and create a knowledge base. The knowledge base is utilized to retrieve relevant search results to supply with a query submitted to a large language model (LLM), in this case, Gemini, as context. This technique is known as retrieval augmentation gener…