Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.
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Earn a skill badge by completing the Develop and Secure APIs with Apigee X skill badge course, where you learn how to modernize your APIs, use service accounts and Google Authentication to securely access backend services from Apigee API proxies, productize APIs using API products and developer portals, secure APIs using features like API keys, OAuth, private variables and fault handling, integrate Apigee with Google Cloud services like Pub/Sub and Cloud Logging, and call Google Cloud APIs like the Natural Language API and the Geocoding API.
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This course is designed for app developers and DevOps engineers who want to work smarter by using Gemini CLI, a generative AI agent made for the terminal and powered by Gemini.
This course discusses Gemini CLI installation and configuration, and introduces use cases and security best practices. It explains commands, tools, MCP servers, and extensions. With a hands-on exercise, you'll install and configure Gemini CLI and use it to analyze code and build and modify an app.
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Designed for developers of all levels, this course introduces you to the core features and functionalities of Gemini Code Assist, an AI-powered app development collaborator for Google Cloud. From intelligent code suggestions and auto-completion to real-time error detection and refactoring assistance, you'll discover how Gemini Code Assist can significantly enhance your productivity and code quality, and save valuable time to focus on more productive and enjoyable tasks.
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This short course on integrating applications with Gemini 1.0 Pro models on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 1.0 Pro and Gemini 1.0 Pro Vision models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.
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This course introduces the Cloud Run serverless platform for running applications.
In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle.
You learn about service identities, how to control access to services, and how to develop and test your
application locally before deploying it to Cloud Run. The course also teaches you how to integrate
with other services on Google Cloud so you can build full-featured applications.
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In this course, you learn about containers and how to build, and package container images. The content in this course includes best practices for creating and securing containers, and provides an introduction to Cloud Run and Google Kubernetes Engine for application developers.
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In this course, you learn about Cloud Run functions, Google's serverless, fully-managed functions as a service (FaaS) product that lets you implement single-purpose function code that reponds to HTTP requests and events from your cloud infrastructure.
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This course introduces you to event-based applications and teaches you how to use service orchestration and choreography to coordinate microservices. Using lectures and hands-on labs, you learn how to use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to build microservices applications on Google Cloud.
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In this course, you learn the fundamentals of application development on Google Cloud. You learn best practices for cloud applications, and how to select compute and data options to match your application use cases. You're introduced to generative AI and how it's used to help build applications. You learn about authentication and authorization, application deployment, continuous integration and delivery, and monitoring and performance tuning for your applications running in Google Cloud. Using lectures and hands-on labs, you learn how to get started building and running applications on Google Cloud.
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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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Earn a Introductory skill badge by completing the Build Serverless Applications with Cloud Run Functions course, where you learn how to use Cloud Run functions through the Google Cloud console and on the command line.
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Complete the introductory Monitoring in Google Cloud skill badge course to demonstrate skills in the following: using Cloud Monitoring tools to monitor resources on Google Cloud.
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Earn a skill badge by completing the App Building with AppSheet course, where you learn how to build, configure, and publish apps using AppSheet.
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Earn a skill badge by completing the Analyze Speech and Language with Google APIs quest, where you learn how to use the Natural Language and Speech APIs in real-world settings.
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Earn a skill badge by completing the Get Started with Pub/Sub skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.
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Earn a skill badge by completing the Create a Streaming Data Lake on Cloud Storage course, where you use Pub/Sub, Dataflow, and Cloud Storage together to create a streaming data lake 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 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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Earn a skill badge by completing the Get Started with Cloud Storage skill badge course, where you learn how to create a Cloud Storage bucket, how to use the Cloud Storage command line, and how to use Bucket Lock to protect objects in a bucket.
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Пройдіть вступний кваліфікаційний курс Налаштування Cloud Load Balancing для Compute Engine, щоб продемонструвати свої навички: створення й розгортання віртуальних машин у Compute Engine; налаштування мережі й розподілювачів навантаження додатків.
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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Looker Studio by connecting to BigQuery data.
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Earn a skill badge by completing the Get Started with API Gateway skill badge course, where you learn how to use API Gateway to deploy, secure, and manage APIs with a fully managed gateway.
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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
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Complete the introductory Use APIs to Work with Cloud Storage skill badge to demonstrate skills in the following: using APIs to work with Cloud Storage resources, including the Cloud Storage API.
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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge course to demonstrate skills in the following: filtering, sorting, and pivoting data; merging results from different Looker Explores; and using functions and operators to build Looker dashboards and reports for data analysis and visualization.
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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.
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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.
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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.
Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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Під час курсу ви зможете ознайомитися з продуктами й сервісами Google Cloud для роботи з масивами даних і машинним навчанням, які підтримують життєвий цикл роботи з даними для тренування моделей штучного інтелекту. У курсі розглядаються процеси, проблеми й переваги створення конвеєру масиву даних і моделей машинного навчання з Vertex AI у Google Cloud.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) 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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Google Cloud Application Programming Interfaces are the mechanism to interact with Google Cloud Services programmatically. This quest will give you hands-on practice with a variety of GCP APIs, which you will learn through working with Google’s APIs Explorer, a tool that allows you to browse APIs and run their methods interactively. By learning how to transfer data between Cloud Storage buckets, deploy Compute Engine instances, configure Dataproc clusters and much more, Exploring APIs will show you how powerful APIs are and why they are used almost exclusively by proficient GCP users. Enroll in this quest today.
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Earn a skill badge by completing the Streaming Analytics into BigQuery skill badge course, where you use Pub/Sub, Dataflow and BigQuery together to stream data for analytics.
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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.
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Complete the introductory Monitor and Manage Google Cloud Resources skill badge to demonstrate skills in the following: granting and revoking IAM permissions; installing monitoring and logging agents; creating, deploying, and testing an event-driven Cloud Run function.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.
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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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Щоб отримати кваліфікаційний значок, пройдіть курс Налаштування мережі Google Cloud. У ньому ви дізнаєтеся про різні способи розгортання й моніторингу додатків, зокрема навчитеся визначати ролі керування ідентифікацією і доступом, надавати або вилучати доступ до проектів, створювати мережі VPC, розгортати й відстежувати віртуальні машини Compute Engine, писати запити SQL, а також по-різному вводити додатки в дію за допомогою Kubernetes.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Looker Studio by connecting to BigQuery data.
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Пройдіть вступний кваліфікаційний курс Підготовка даних для інтерфейсів API машинного навчання в Google Cloud, щоб продемонструвати свої навички щодо очистки даних за допомогою сервісу Dataprep by Trifacta, запуску конвеєрів даних у Dataflow, створення кластерів і запуску завдань Apache Spark у Dataproc, а також виклику API машинного навчання, зокрема Cloud Natural Language API, Google Cloud Speech-to-Text API і Video Intelligence API.
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Щоб отримати кваліфікаційний значок, пройдіть курс Налаштування середовища для розробки додатка в Google Cloud. У ньому ви навчитеся створювати й підключати хмарну інфраструктуру, спрямовану на зберігання даних, за допомогою базових можливостей таких технологій, як Cloud Storage, система керування ідентифікацією і доступом, Cloud Functions та Pub/Sub.
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Курс "Знайомство з Google Cloud: основна інфраструктура" охоплює важливі поняття й терміни щодо використання Google Cloud. Переглядаючи відео й виконуючи практичні завдання, слухачі ознайомляться з різними сервісами Google Cloud для обчислень і зберігання даних, а також важливими ресурсами й інструментами для керування правилами. Крім того, вони зможуть їх порівнювати.
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Пройдіть вступний кваліфікаційний курс Налаштування Cloud Load Balancing для Compute Engine, щоб продемонструвати свої навички: створення й розгортання віртуальних машин у Compute Engine; налаштування мережі й розподілювачів навантаження додатків.
Develop Serverless Applications on Cloud Run
Earned бер. 25, 2026 EDT
Develop and Secure APIs with Apigee X
Earned бер. 11, 2026 EDT
Accelerate App Development with Gemini CLI
Earned бер. 7, 2026 EST
Streamline App Development with Gemini Code Assist
Earned квіт. 1, 2025 EDT
Integrating Applications with Gemini 1.0 Pro on Google Cloud
Earned квіт. 1, 2025 EDT
Developing Applications with Cloud Run on Google Cloud: Fundamentals
Earned бер. 31, 2025 EDT
Developing Containerized Applications on Google Cloud
Earned бер. 31, 2025 EDT
Developing Applications with Cloud Run Functions on Google Cloud
Earned бер. 30, 2025 EDT
Service Orchestration and Choreography on Google Cloud
Earned бер. 27, 2025 EDT
Developing Applications with Google Cloud: Foundations
Earned бер. 25, 2025 EDT
Build Streaming Data Pipelines on Google Cloud
Earned квіт. 2, 2024 EDT
Build Serverless Applications with Cloud Run Functions
Earned бер. 31, 2024 EDT
Monitoring in Google Cloud
Earned бер. 31, 2024 EDT
App Building with AppSheet
Earned бер. 31, 2024 EDT
Analyze Speech and Language with Google APIs
Earned бер. 31, 2024 EDT
Get Started with Pub/Sub
Earned бер. 31, 2024 EDT
Create a Streaming Data Lake on Cloud Storage
Earned бер. 31, 2024 EDT
Get Started with Cloud Storage
Earned бер. 31, 2024 EDT
Налаштування Cloud Load Balancing для Compute Engine
Earned бер. 30, 2024 EDT
Derive Insights from BigQuery Data
Earned бер. 30, 2024 EDT
Get Started with API Gateway
Earned бер. 30, 2024 EDT
The Basics of Google Cloud Compute
Earned бер. 30, 2024 EDT
Use APIs to Work with Cloud Storage
Earned бер. 30, 2024 EDT
Prepare Data for Looker Dashboards and Reports
Earned бер. 29, 2024 EDT
Deploy Kubernetes Applications on Google Cloud
Earned бер. 28, 2024 EDT
Manage Kubernetes in Google Cloud
Earned бер. 28, 2024 EDT
Build Batch Data Pipelines on Google Cloud
Earned лист. 26, 2023 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned лист. 19, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals - українська
Earned лист. 18, 2023 EST
Preparing for your Professional Data Engineer Journey
Earned лист. 16, 2023 EST
DEPRECATED Exploring APIs
Earned лист. 12, 2023 EST
Streaming Analytics into BigQuery
Earned лист. 1, 2023 EDT
Deploy Kubernetes Applications on Google Cloud
Earned лист. 1, 2023 EDT
Monitor and Manage Google Cloud Resources
Earned лист. 1, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Command Line
Earned лист. 1, 2023 EDT
Get Started with Dataplex
Earned лист. 1, 2023 EDT
Get Started with Looker
Earned жовт. 31, 2023 EDT
Налаштування мережі Google Cloud
Earned жовт. 31, 2023 EDT
Build a Data Warehouse with BigQuery
Earned жовт. 31, 2023 EDT
Derive Insights from BigQuery Data
Earned жовт. 31, 2023 EDT
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud
Earned жовт. 30, 2023 EDT
Налаштування середовища для розробки додатка в Google Cloud
Earned жовт. 27, 2023 EDT
Google Cloud Fundamentals: Core Infrastructure - Yкраїнська
Earned жовт. 24, 2023 EDT
Налаштування Cloud Load Balancing для Compute Engine
Earned жовт. 7, 2023 EDT