Build and edit a Hello World Flutter application using a Code Server development enviornment.

This lab walks you through writing your first Flutter app compatible for Android, iOS, and web.

Design a basic frontend for a mobile app using Material Components for Flutter.

This lab demonstrates how to use Firebase Web authentication in a Flutter application.

Explore using Dart Function Frameworks in a Flutter application. Example based on this demo.

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.

In this lab you will learn how Dart is used with data structures. Understand the utility of Maps and Lists and how these are used to reference information.

Go 및 Cloud Run으로 REST API를 빌드하는 방법 시연

In this lab you will use Eventarc for Cloud Run to listen to events from Cloud Pub/Sub and Audit Logs. At the end of this lab you will be able to deliver events from various sources to Google Cloud sinks.

In this lab you learn how to set up API Gateway to manage and secure a Cloud Run backend service with gRPC.

이 실습에서는 서버리스 서비스인 Cloud Run을 사용하여, Cloud Storage에 저장된 파일을 별도의 폴더에 저장되는 PDF로 자동 변환하는 PDF 변환기 웹 앱을 빌드합니다.

In this lab you will deploy a website to Google Kubernetes Engine, scale it out to more instances, then deploy a new version using rolling updates.

Data validation is a critical step in data warehouse, database, or data lake migration.

이 실습에서는 BigLake 테이블을 구현하는 방법을 알아봅니다.

Send an image to the Cloud Vision API and have it identify objects, faces, and landmarks

This hands-on lab uses Kubernetes and Cloud Vision API to create an example of how to use the Vision API to classify (label) images from Reddit's /r/aww subreddit and display the labelled results in a web app.

This lab will show you how to deploy a set of Cloud Run functions in order to process images and videos with the Cloud Vision API and Cloud Video Intelligence API.

이 실습에서는 Pigeon Travel 채팅 에이전트 작업을 계속합니다. 컨텍스트를 추가하고 fulfillment를 설정하여 Firestore에서 예약 항목을 조회하고 저장합니다.

Use the Cloud Vision, Natural Language, and Translation APIs to capture text strings from images, recognize characters, and analyze and translate the text strings into other languages.

In this lab, you will learn how to build a binary classification model from tabular data using Vertex AI.

이 실습에서는 BigQuery ML XGBoost 모델을 사용하여 일괄 예측과 온라인 예측을 학습, 조정, 평가, 설명, 생성해 봅니다. 실제 모바일 애플리케이션인 Flood it!의 Google 애널리틱스 4 데이터 세트를 사용하여 사용자가 애플리케이션을 다시 실행할 가능성을 판단합니다. BigQuery ML 모델을 사용하여 일괄 예측을...

이번 실습에서는 TensorFlow 모델을 학습시키고 서빙(예측)을 위해 Vertex AI에 배포합니다. 짧은 동영상인 Getting started with Notebooks for machine learning 및 Faster model training and experimentation with Vertex AI를 시청하세요.

In this lab, you will use TensorFlow's distribution strategies and the Vertex AI platform to train and deploy a custom TensorFlow image classification model to classify an image classification dataset.

In this lab you'll learn how to classify text into categories using the Natural Language API

Cloud Natural Language API를 사용하면 텍스트 블록에서 항목을 추출하고 감정 및 구문 분석을 수행할 수 있습니다. 이 실습에서는 Cloud Natural Language API를 사용하여 텍스트에서 항목과 감정을 추출하는 방법을 알아봅니다.

Learn how to use Managed Service for Prometheus in a self-deployed data collection mode. You can also utilize managed data collection as well.

This lab introduces you to the fundamentals of API Management with Google's Apigee API Management Platform. You will go through the API Lifecycle at a high level - from API design, API Security, API Consumption to API Analytics & Monitoring.

In this lab, you use an Apigee X threat protection policy and Cloud Armor to protect your APIs.

In this lab, you use the Apigee X provisioning wizard to create an Apigee X evaluation organization (org).

In this lab, you add a new environment and environment group to an Apigee X evaluation org.

In this lab, you enable a NAT IP address for the runtime instance. This static IP address is used when calling from Apigee X to backend services.

Use Migrate for Compute Engine to migrate an EC2 instance from AWS to Compute Engine on Google Cloud and verify the migration

In this lab, you migrate MySQL data from an Amazon RDS instance for MySQL to Cloud SQL for MySQL using a one-time Database Migration Service job and an IP allowlist for connectivity. After you create and run the migration job,...

In this hands-on lab, you will learn why Google Cloud is the cleanest cloud in the industry by exploring and utilizing sustainability tools..

Learn how to to create and use document processors using the Document AI API.

이 실습에서는 손상된 자동차 부품을 인식하도록 커스텀 Vertex AI 생성 이미지 분류 모델을 학습시키는 방법을 알아봅니다.

Contact Center AI를 사용하면 통화 전환율을 개선하여 고객 만족도와 운영 효율성을 높이고 처리 시간을 단축하면서도 전반적인 작업을 더 빠르고 효과적으로 진행할 수 있습니다. 이번 실습에서는 Dialogflow를 사용하여 대화형 인터페이스를 만드는 방법을 알아봅니다.

Configure an HTTP Load Balancer with global backends, stress test the Load Balancer, and add a Cloud Armor rate limiting policy to restrict based on IP.

이 실습에서는 IAP(Identity-Aware Proxy) TCP 전달을 사용하여 외부 IP 주소가 없거나 인터넷을 통한 직접 액세스를 허용하지 않는 VM 인스턴스에 대한 관리 액세스를 사용 설정하는 방법을 알아봅니다.

Redacting Sensitive Data with the DLP API

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.

In this lab, you will learn how to secure multi-cloud applications using Identity-Aware Proxy (IAP) connector.

In this lab you'll learn how to build a Google Workspace Add-on using Node.js and Cloud Run.

Learn how to use Google AppSheet to enable everyone in your organization to build and extend applications without coding.

In this lab, you use AppSheet to publish your app.

In this lab, you will use AppSheet to implement the UX components in your app.

In this lab, you use AppSheet to connect and configure data for your app.

In this lab, you create a Kubernetes cluster and deploy a simple application to that cluster. Then, you connect the application to the supplied Cloud SQL for PostgreSQL database instance and confirm that it is able to write to and...

In this lab you'll deploy the Autoscaler tool for Cloud Spanner, a companion tool to Cloud Spanner, in the per-project configuration where the autoscaler tools are located in the same project as the Cloud Spanner instance being autoscaled.

In this lab, you explore a Bigtable instance and use the Bigtable CLI (cbt CLI) to query data in Bigtable. You also design a table schema and row key using best practices for Bigtable.

In this lab you’ll learn how to use the Firebase platform to easily create Web applications and implement and deploy a chat client.

In this lab, you will configure a highly available Memorystore cluster and review the architecture of such a deployment.

Learn to migrate MySQL Databases to BigQuery using Datastream and Dataflow

Learn how to analyze key parts of a tennis serve using the Video Intelligence API. To preview, watch the short video this lab is based off of.

In this lab, you create and run a Sensitive Data Protection job using the De-identify (DeID) Findings Action to create a redacted and de-identified copy data in Cloud Storage.

In this lab, you will implement a player profile service and a game matchmaking service to work with Cloud Spanner.

In this lab, you will run BigQuery analytics on data stored in AWS S3 using BigQuery Omni.

In this lab, you will create Cloud Functions that respond to HTTP calls and get triggered by Pub/Sub messages and Cloud Audit Logs.