Partecipa Accedi

Nilay Saraf

Membro dal giorno 2021

Campionato Argento

72920 punti
Explore Generative AI in Agent Platform Earned mag 6, 2025 EDT
Develop Gen AI Apps with Gemini and Streamlit Earned mag 5, 2025 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG Earned mag 5, 2025 EDT
Build Real World AI Applications with Gemini and Imagen Earned apr 18, 2025 EDT
Prompt Design in Agent Platform Earned apr 17, 2025 EDT
Monitor and Manage Google Cloud Resources Earned set 5, 2023 EDT
Qwiklabs Trivia August 2023 Earned ago 22, 2023 EDT
Automate Interactions with Contact Center AI Earned ago 17, 2023 EDT
Build Event-Driven Applications with Eventarc Earned ago 17, 2023 EDT
Store, Process, and Manage Data on Google Cloud - Console Earned ago 15, 2023 EDT
Use APIs to Work with Cloud Storage Earned ago 12, 2023 EDT
Prepare Data for Looker Dashboards and Reports Earned ago 12, 2023 EDT
Build Serverless Applications with Cloud Run Functions Earned ago 11, 2023 EDT
Automate Data Capture at Scale with Document AI Earned ago 11, 2023 EDT
Using the Google Cloud Speech API Earned ago 10, 2023 EDT
App Building with AppSheet Earned ago 10, 2023 EDT
Analyze BigQuery Data in Connected Sheets Earned ago 10, 2023 EDT
Analyze Sentiment with Natural Language API Earned ago 10, 2023 EDT
Level 3: GenAI Earned ago 9, 2023 EDT
Analyze Speech and Language with Google APIs Earned ago 9, 2023 EDT
Use Machine Learning APIs on Google Cloud Earned ago 9, 2023 EDT
Streaming Analytics into BigQuery Earned ago 8, 2023 EDT
Implement Cloud Storage and Data Protection Solutions Earned ago 8, 2023 EDT
Level 2: Apps Script and Networks Earned ago 8, 2023 EDT
Implement Speech and Language Solutions with Pre-trained APIs Earned ago 7, 2023 EDT
Crea un sito web su Google Cloud Earned ago 7, 2023 EDT
Creazione di una rete Google Cloud sicura Earned ago 7, 2023 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned ago 7, 2023 EDT
Develop with Apps Script and AppSheet Earned ago 5, 2023 EDT
Integrate BigQuery Data and Google Workspace using Apps Script Earned ago 5, 2023 EDT
Configure Service Accounts and IAM Roles for Google Cloud Earned ago 5, 2023 EDT
Prepara i dati per le API ML su Google Cloud Earned ago 5, 2023 EDT
Cloud Architecture: Design, Implement, and Manage Earned ago 5, 2023 EDT
Level 1: BigQuery ML, Cloud Architecture and Devops Skills Earned ago 5, 2023 EDT
Implement DevOps Workflows in Google Cloud Earned ago 4, 2023 EDT
Develop Serverless Apps with Firebase Earned ago 4, 2023 EDT
Create ML Models with BigQuery ML Earned ago 3, 2023 EDT
Implement Cloud Security Fundamentals on Google Cloud Earned ago 3, 2023 EDT
Qwiklabs Trivia July 2023 Earned lug 25, 2023 EDT
Genera insight dai dati BigQuery Earned lug 19, 2023 EDT
Secure Lakehouse Data Earned lug 18, 2023 EDT
Level 2: Data Deep Dive Earned lug 18, 2023 EDT
Enrich Metadata and Discovery of Lakehouse Data Earned lug 17, 2023 EDT
Implement Sensitive Data Protection on Google Cloud Earned lug 16, 2023 EDT
Analyze Images with the Cloud Vision API Earned lug 15, 2023 EDT
Set Up a Google Cloud Network Earned lug 15, 2023 EDT
Deploy and Manage Applications on Google App Engine Earned lug 12, 2023 EDT
Level 1: AppDev and Infrastructure Earned lug 12, 2023 EDT
The Basics of Google Cloud Compute Earned lug 12, 2023 EDT
DEPRECATED Networking Fundamentals on Google Cloud Earned lug 12, 2023 EDT
Machine Learning Operations (MLOps): Getting Started Earned lug 11, 2023 EDT
Getting Started with Go on Google Cloud Earned lug 11, 2023 EDT
Preparing for the Professional Cloud Architect Exam - Italiano Earned gen 16, 2023 EST
Infrastruttura Google Cloud affidabile: progetto e processo Earned gen 16, 2023 EST
Manage Security in Google Cloud Earned gen 9, 2023 EST
Application Development with Cloud Run Earned gen 5, 2023 EST
App Deployment, Debugging, and Performance Earned gen 5, 2023 EST
Networking in Google Cloud: Fundamentals Earned gen 4, 2023 EST
Networking in Google Cloud: Routing and Addressing Earned dic 30, 2022 EST
Build a Certification Study Guide: PCNE Exam Prep Earned dic 30, 2022 EST
Scaling with Google Cloud Operations Earned dic 28, 2022 EST
Modernize Infrastructure and Applications with Google Cloud Earned dic 28, 2022 EST
Exploring Data Transformation with Google Cloud Earned dic 28, 2022 EST
Digital Transformation with Google Cloud Earned dic 28, 2022 EST
Google Cloud Fundamentals for AWS Professionals Earned dic 27, 2022 EST
Anthos on Bare Metal Earned dic 25, 2022 EST
DEPRECATED Cloud Operations and Service Mesh with Anthos Earned dic 25, 2022 EST
Multi-Cluster, Multi-Cloud with Anthos Earned dic 25, 2022 EST
Hybrid Cloud Modernizing Applications with Anthos Earned dic 25, 2022 EST
Hybrid Cloud Service Mesh with Anthos Earned dic 25, 2022 EST
Hybrid Cloud Multi-Cluster with Anthos Earned dic 25, 2022 EST
Architecting with Google Kubernetes Engine: Production - Italiano Earned dic 25, 2022 EST
Architecting with Google Kubernetes Engine: Workloads - Italiano Earned dic 22, 2022 EST
Hybrid Cloud Infrastructure Foundations with Anthos Earned dic 20, 2022 EST
Progettazione dell'architettura con Google Kubernetes Engine: fondamenti Earned dic 20, 2022 EST
Building No-Code Apps with AppSheet: Automation Earned dic 20, 2022 EST
Building No-Code Apps with AppSheet: Implementation Earned dic 20, 2022 EST
Building No-Code Apps with AppSheet: Foundations Earned dic 18, 2022 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned dic 17, 2022 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud Earned dic 16, 2022 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Earned dic 16, 2022 EST
[DEPRECATED]- Google Cloud Computing Foundations: Cloud Computing Fundamentals - Italiano Earned dic 16, 2022 EST
Recommendation Systems on Google Cloud Earned dic 15, 2022 EST
Natural Language Processing on Google Cloud Earned dic 15, 2022 EST
Computer Vision Fundamentals with Google Cloud Earned dic 14, 2022 EST
Production Machine Learning Systems Earned dic 13, 2022 EST
Launching into Machine Learning - Italiano Earned dic 13, 2022 EST
Crea, addestra ed esegui il deployment di modelli ML tramite Keras su Google Cloud Earned dic 12, 2022 EST
[DEPRECATED] Feature engineering Earned dic 11, 2022 EST
How Google Does Machine Learning Earned dic 10, 2022 EST
Machine learning in azienda Earned dic 10, 2022 EST
Google Cloud Big Data and Machine Learning Fundamentals - Italiano Earned dic 9, 2022 EST
Crea l'infrastruttura con Terraform su Google Cloud Earned dic 8, 2022 EST
Sviluppa la tua rete Google Cloud Earned dic 7, 2022 EST
Configura un ambiente di sviluppo di app su Google Cloud Earned dic 5, 2022 EST
Implementazione di Cloud Load Balancing per Compute Engine Earned dic 4, 2022 EST
Logging and Monitoring in Google Cloud Earned dic 4, 2022 EST
Introduzione a Google Kubernetes Engine Earned dic 2, 2022 EST
Getting Started with Terraform for Google Cloud Earned nov 30, 2022 EST
Infrastruttura Google Cloud elastica: scalabilità e automazione Earned nov 30, 2022 EST
Infrastruttura Google Cloud di base: fondamenti Earned nov 28, 2022 EST
Infrastruttura Google Cloud di base: servizi principali Earned nov 28, 2022 EST
Google Cloud Fundamentals: Core Infrastructure - Italiano Earned nov 21, 2022 EST
Build a Certification Study Guide: ACE Exam Prep Earned nov 17, 2022 EST

Complete the intermediate Explore Generative AI in Agent Platform skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Google Cloud Agent Platform. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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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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Welcome to Qwiklabs Trivia for August! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the August badge.

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Earn a skill badge by completing the Automate Interactions with Contact Center AI quest, where you will learn about the features of Contact Center AI, including how to Build a virtual agent, Design conversation flows for your virtual agent; Add a phone gateway to your virtual agent; Use Dialogflow for troubleshooting; Review logs and debug your virtual agent. 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 the skill badge quest, and 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 Build Event-Driven Applications with Eventarc course. In this course, you use Eventarc to create event triggers for different resources, including Pub/Sub topics and Cloud Storage buckets.

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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 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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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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Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.

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Earn a skill badge by completing the Using the Google Cloud Speech API skill badge course, where you learn how create a Speech-to-Text API request, transcribe audio speech to text, and transcribe speech.

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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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Complete the Analyze BigQuery Data in Connected Sheets skill badge to demonstrate that you can use Connected Sheets to access, analyze, visualize, and share billions of rows of BigQuery data from your Google Sheets spreadsheet.

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Earn a skill badge by completing the Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.

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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!

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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 the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.

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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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Earn a Skill Badge by completing the Implement Cloud Storage and Data Protection Solutions course. Learn to create a Cloud Storage bucket, use the command line, and protect objects with Bucket Lock.

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For organisations to thrive in the digital world, it is important for them to have secured networks to protect sensitive data, prevent cyber threats and maintain customer trust. Learn the principles of network design, security and management and integrating BigQuery Data and Google Workspace using Apps Script. Gain hands-on experience with labs carefully designed to nurture and assess your tech skills and set you on a course to earn your first Google Cloud credential.

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Earn the Introductory Skill Badge by completing the Implement Speech and Language Solutions with Pre-trained APIs course, where you learn how to use speech related API tools to synthesise and transcribe speech.

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Ottieni il badge delle competenze introduttivo completando il corso con badge delle competenze Crea un sito web su Google Cloud. Questo corso si basa sulla serie Get Cooking in Cloud e tratta i seguenti argomenti:Deployment di un sito web su Cloud RunHosting di un'app web su Compute EngineCreazione, deployment e scalabilità del tuo sito web su Google Kubernetes EngineMigrazione da un'applicazione monolitica a un'architettura di microservizi utilizzando Cloud Build

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Guadagna un badge delle competenze completando il corso Creazione di una rete Google Cloud sicura, in cui scoprirai più risorse di networking per creare, scalare e proteggere le tue applicazioni su Google Cloud.

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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.

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Earn a skill badge by completing the Develop with Apps Script and AppSheet skill badge course, where you learn how to build chat bots and how to use the script editor in any document.

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Complete the introductory Integrate BigQuery Data and Google Workspace using Apps Script skill badge course to demonstrate skills in connecting Workspace products with BigQuery via AppSheet.

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Earn the Introductory skill badge by completing the Configure Service Accounts and IAM Roles for Google Cloud course, where you learn about service accounts, custom roles, and how to set permissions using gcloud .

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Ottieni il corso intermedio con badge delle competenze Prepara i dati per le API ML su Google Cloud per dimostrare le tue competenze nei seguenti ambiti: pulizia dei dati con Dataprep di Trifacta, esecuzione delle pipeline di dati in Dataflow, creazione dei cluster ed esecuzione dei job Apache Spark in Managed Service for Apache Spark e richiamo delle API ML tra cui l'API Cloud Natural Language, l'API Google Cloud Speech-to-Text e l'API Video Intelligence.

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Earn a skill badge by completing the Cloud Architecture: Design, Implement, and Manage to demonstrate skills in the following: deploy a publicly accessible website using Apache web servers, configure a Compute Engine VM using startup scripts, configure secure RDP using a Windows Bastion host and firewall rules, build and deploy a Docker image to a Kubernetes cluster and then update it, and create a CloudSQL instance and import a MySQL database. This skill badge is a great resource for understanding topics that will appear in the Google Cloud Certified Professional Cloud Architect certification exam.

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The world around us is changing and mastering future-driven technologies is the key to success. We want you to get started by learning a little of everything! Discover machine learning in data analysis, build scalable cloud solutions and accelerate software development that will shape the future. The possibilities in the Arcade are endless and all of those will lead you towards earning your first Google Cloud Credential. No prior experience required.

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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating and managing Git repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.

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Complete the intermediate Develop Serverless Apps with Firebase skill badge course to demonstrate skills in the following: architecting and building serverless web applications with Firebase, utilizing Firestore for database management, automating deployment processes using Cloud Build, and integrating Google Assistant functionality into your applications.

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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.

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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.

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Welcome to Qwiklabs Trivia for July! Each week, we will release a new set of questions to test your knowledge. You will have opportunities to play throughout the month. Give your career a boost with hands-on experience on GCP and partner services and earn the July badge.

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Completa il corso introduttivo con badge delle competenze Genera insight dai dati BigQuery per dimostrare le tue competenze nei seguenti ambiti: scrivere query SQL, eseguire query su tabelle pubbliche, caricare dati di esempio in BigQuery, risolvere i problemi di sintassi comuni con lo strumento di convalida query in BigQuery e creare report in Data Studio collegando ai dati di BigQuery.

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Complete the introductory Secure Lakehouse Data skill badge course to demonstrate skills with IAM, BigQuery, Lakehouse, and Knowledge Catalog to create and secure Lakehouse tables.

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The demand for data skills is growing rapidly, and we want you to get ahead! According to a report by the McKinsey Global Institute, the demand for data scientists and analysts is expected to grow by 150% by 2025. There are a lot of different aspects to any data role, so it's important to start with the basics - and we’ve got you covered. Learn how to tap into ML APIs, dive into your first data lake, and learn how the experts think about securing data. No experience required.

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Complete the Enrich Metadata and Discovery of Lakehouse Data skill badge course to demonstrate skills in BigQuery, Lakehouse, and Knowledge Catalog. You create Lakehouse tables and enrich metadata management and discovery of the table data.

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Complete the Implement Sensitive Data Protection on Google Cloud Skill Badge course to demonstrate skills in the following: using Sensitive Data Protection services (including the Cloud Data Loss Prevention API) to inspect, redact, and de-identify sensitive data in Google Cloud.

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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.

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Earn a skill badge by completing the Set Up a Google Cloud Network skill badge course, where you will learn how to perform basic networking tasks on Google Cloud Platform - create a custom network, add subnets firewall rules, then create VMs and test the latency when they communicate with each other.

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Earn a Skill Badge by completing the Deploy and Manage Applications on Google App Engine course, where you learn how to use App Engine with Python, Go, and PHP.

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Demand for cloud-skilled workers is rising. According to a report by Indeed, cloud computing jobs are expected to grow by 22% over the next five years, much faster than the average for all occupations. Play now to get hands-on experience building with Google Cloud's powerful coding and infrastructure management tools. Each lab teaches and tests your growing tech skills, and sets you on the path to your first Google Cloud credential.

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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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Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers 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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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.

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Get started with Go (Golang) by reviewing Go code, and then creating and deploying simple Go apps on Google Cloud. Go is an open source programming language that makes it easy to build fast, reliable, and efficient software at scale. Go runs native on Google Cloud, and is fully supported on Google Kubernetes Engine, Compute Engine, App Engine, Cloud Run, and Cloud Functions. Go is a compiled language and is faster and more efficient than interpreted languages. As a result, Go requires no installed runtime like Node, Python, or JDK to execute.

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Lo scopo di questo corso è aiutare coloro che sono qualificati ad avere confidenza per tentare l'esame e aiutare le persone non ancora qualificate a sviluppare il proprio piano per la preparazione.

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Questo corso spiega agli studenti come creare soluzioni efficienti e ad alta affidabilità su Google Cloud utilizzando pattern di progettazione comprovati. È la continuazione del corso Progettazione dell'architettura con Google Compute Engine o Progettazione dell'architettura con Google Kubernetes Engine e presuppone che si abbia esperienza pratica con le tecnologie esaminate in uno dei due corsi. Attraverso una combinazione di presentazioni, attività di progettazione e lab pratici, i partecipanti impareranno a definire e bilanciare i requisiti aziendali e tecnici per progettare deployment Google Cloud estremamente affidabili, sicuri, economicamente convenienti e ad alta disponibilità.

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This course provides foundational knowledge for securing your Google Cloud environment. You will learn Google Cloud's security model, including Zero Trust principles and the Shared Fate model. You will configure identity services like Cloud Identity and Workforce Identity Federation, manage access control using Identity and Access Management (IAM) roles, conditions, and policies, and implement network security controls such as VPCs, Cloud Firewall tiers, and VPC Service Controls to build a secure perimeter. As the foundation of the Security in Google Cloud learning path, this course establishes the core principles required for two subsequent specialized tracks: the five-course Security Best Practices in Google Cloud series and the four-course Mitigate Threats in Google Cloud series.

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This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to on Google Cloud using Cloud Run.design, implement, deploy, secure, manage, and scale applications

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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate components from the Google Cloud ecosystem. Through a combination of presentations, demos, and hands-on labs, participants learn how to create repeatable deployments by treating infrastructure as code, choose the appropriate application execution environment for an application, and monitor application performance. Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer.

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Networking in Google cloud is a 6 part course series. Welcome to the first course of our six part course series, Networking in Google Cloud: Fundamentals.  This course provides a comprehensive overview of core networking concepts, including networking fundamentals, virtual private clouds (VPCs), and the sharing of VPC networks. Additionally, the course covers network logging and monitoring techniques. 

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Welcome to the second course in the networking and Google Cloud series routing and addressing. In this course, we'll cover the central routing and addressing concepts that are relevant to Google Cloud's networking capabilities. Module one will lay the foundation by exploring network routing and addressing in Google Cloud, covering key building blocks such as routing IPv4, bringing your own IP addresses and setting up cloud DNS. In Module two will shift our focus to private connection options, exploring use cases and methods for accessing Google and other services privately using internal IP addresses. By the end of this course, you'll have a solid grasp of how to effectively route and address your network traffic within Google Cloud.

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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Network Engineer certification exam. You'll review Gemini Notebook features, add sources to your notebook, and learn how to personalize your Gemini Notebook experience to study for the exam.

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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. This course explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Many traditional enterprises use legacy systems and apps that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems and investing in new products and services. This course explores these challenges and offers solutions to overcome them by using cloud technology. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Cloud technology is a powerful asset, and when paired with data, it becomes a catalyst for innovation and enhanced customer experiences. Exploring Data Transformation with Google Cloud examines how organizations can leverage the cloud to make their data more accessible, actionable, and valuable. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Digital transformation is a critical journey for modern organizations, and establishing a strong baseline in cloud computing is the first step toward driving meaningful innovation. Digital Transformation with Google Cloud introduces the core technologies and strategic frameworks that help organizations modernize their operations. This course explores fundamental cloud concepts, global network infrastructure, and the shared responsibility model to help leaders navigate their path to the cloud with confidence. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Google Cloud Fundamentals for AWS Professionals introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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Course three of the Anthos series prepares students to run Anthos in a customer’s on-premises environment, on bare metal.Through presentations and hands-on labs, participants explore deploying and running Anthos applications on bare metal, creating the Anthos infrastructure, deploying applications, and performing monitoring, logging, and tracing. This course is a continuation of course two, Cloud Operations and Service Mesh with Anthos, and assumes direct experience with the topics covered in that course.

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Course two of the Architecting Hybrid Cloud with Anthos series prepares students to operate and observe Anthos environments. Through presentations and hands-on labs, participants explore adjusting existing clusters, setting up advanced traffic routing policies, securing communication across workloads, and observing clusters in Anthos. This course is a continuation of course one, Multi-Cluster, Multi-Cloud with Anthos, and assumes direct experience with the topics covered in that course.

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Course one of the Architecting Hybrid Cloud with Anthos series introduces participants to manage multi-cloud and hybrid Kubernetes deployments using Anthos. Through presentations and hands-on labs, participants explore planning and creating Anthos environments and building manageable and reliable multi-cluster Kubernetes infrastructure environments centered around Anthos and containers. This course is a continuation of Architecting with GKE and assumes direct experience with the technologies covered in that course.

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Course four of the Anthos series prepares students to consider multiple approaches for modernizing applications and services within Anthos environments. Topics include optimizing workloads on serverless platforms and migrating workloads to Anthos. This course is a continuation of course three, Anthos on Bare Metal, and assumes direct experience with the topics covered in that course.

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This on-demand course equips students to understand and adopt Istio-based service-mesh with Anthos for centralized observability, traffic management, and service-level security. This is the second course of the Architecting Hybrid Cloud Infrastructure with Anthos series. After completing this course, learners should continue to the Hybrid Cloud Multi-Cluster with Anthos course. Completion of the Architecting with Google Kubernetes Engine path is a prerequisite for this course.

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This on-demand course equips students to understand, configure, and maintain multi-cluster Kubernetes infrastructures using Anthos GKE, and Istio-based service mesh, whether deployed with Anthos on Google Cloud or with Anthos deployed on VMware. This is the third, and final, course of the Architecting Hybrid Cloud Infrastructure with Anthos series. Completion of the Architecting with Google Kubernetes Engine path is a prerequisite for this course.

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In questo corso, "Architecting with Google Kubernetes Engine: Production", imparerai a conoscere la sicurezza di Kubernetes e Google Kubernetes Engine (GKE), logging e monitoraggio e a utilizzare i servizi di archiviazione e database gestiti di Google Cloud dall'interno di GKE. Si tratta del corso finale della serie Architecting with Google Kubernetes Engine. Dopo il completamento di questo corso, iscriviti al corso Reliable Google Cloud Infrastructure: Design and Process o al corso Hybrid Cloud Infrastructure Foundations with Anthos.

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In questo corso, "Architecting with Google Kubernetes Engine: Workloads", imparerai come eseguire le operazioni Kubernetes, creare e gestire i deployment, quali sono gli strumenti di networking di GKE e come fornire archiviazione permanente ai tuoi carichi di lavoro Kubernetes. Questo è il secondo corso della serie Architecting with Google Kubernetes Engine. Dopo il completamento di questo corso, iscriviti al corso Reliable Google Cloud Infrastructure: Design and Process o al corso Hybrid Cloud Infrastructure Foundations with Anthos.

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Welcome to Hybrid Cloud Infrastructure Foundations with Anthos! This is the first course of the Architecting Hybrid Cloud Infrastructure with Anthos path. Anthos enables you to build and manage modern applications, and gives you the freedom to choose where to run them. Anthos gives you one consistent experience in both your on-premises and cloud environments. During this course, you will be presented with modules that will take you through skills that you will use as an architect or administrator running Anthos environments. The modules in this course include videos, hands-on labs, and links to helpful documentation.

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In questo corso, "Progettazione dell'architettura con Google Kubernetes Engine: fondamenti", troverai un ripasso del layout e dei principi di Google Cloud, seguito da un'introduzione alla creazione e alla gestione dei container software, nonché all'architettura di Kubernetes.

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This course helps you recognize the need to implement business process automation in your organization. You learn about automation patterns and use cases, and how to use AppSheet constructs to implement automation in your app. You learn about the various features of AppSheet automation, and integrate your app with Google Workspace products. You also learn how to send email, push notifications and text messages from your app, parse documents and generate reports with AppSheet automation.

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This course teaches you how to implement various capabilities that include data organization and management, application security, actions and integrations in your app using AppSheet. The course also includes topics on managing and upgrading your app, improving performance and troubleshooting issues with your app.

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In this course you will learn the fundamentals of no-code app development and recognize use cases for no-code apps. The course provides an overview of the AppSheet no-code app development platform and its capabilities. You learn how to create an app with data from spreadsheets, create the app’s user experience using AppSheet views and publish the app to end users.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This third course covers cloud automation and management tools and building secure networks.

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Il corso Google Cloud Computing Foundations fornirà a chi ha poca o nessuna esperienza di cloud computing una panoramica dettagliata dei concetti relativi alle nozioni di base del cloud, ai big data e al machine learning, oltre che a dove e come Google Cloud si inserisce. Alla fine del corso, i partecipanti saranno in grado di descrivere i concetti relativi al cloud computing, ai big data e al machine learning e dimostrare delle competenze pratiche. Questo corso fa parte della serie di corsi Google Cloud Computing Foundations. I corsi dovrebbero essere completati nel seguente ordine: Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales Questo secondo corso esamina l'implementazione di modelli …

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Il corso Google Cloud Computing Foundations fornirà a chi ha poca o nessuna esperienza di cloud computing una panoramica dettagliata dei concetti relativi alle nozioni di base del cloud, ai big data e al machine learning, oltre che a dove e come Google Cloud si inserisce. Alla fine del corso, i partecipanti saranno in grado di descrivere questi concetti e dimostrare delle competenze pratiche. Questo corso fa parte della serie di corsi Google Cloud Computing Foundations. I corsi dovrebbero essere completati nel seguente ordine: Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales Questo primo corso fornisce una panoramica del cloud computing, dei modi per utilizzare Google Cloud e diverse opzio…

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In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.

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This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models. The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data. The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models. Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.

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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

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Il corso inizia con una discussione sui dati: come migliorare la qualità dei dati ed eseguire analisi esplorative dei dati. Descriveremo Vertex AI AutoML e come creare, addestrare ed eseguire il deployment di un modello di ML senza scrivere una sola riga di codice. Comprenderai i vantaggi di Big Query ML. Discuteremo quindi di come ottimizzare un modello di machine learning (ML) e di come la generalizzazione e il campionamento possano aiutare a valutare la qualità dei modelli di ML per l'addestramento personalizzato.

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Questo corso tratta la creazione di modelli ML con TensorFlow e Keras, il miglioramento dell'accuratezza dei modelli ML e la scrittura di modelli ML per l'uso su larga scala.

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Questo corso illustra i vantaggi dell'utilizzo di Vertex AI Feature Store, come migliorare l'accuratezza dei modelli di ML e come trovare le colonne di dati che forniscono le caratteristiche più utili. Il corso include inoltre contenuti e lab sul feature engineering utilizzando BigQuery ML, Keras e TensorFlow.

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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.

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Questo corso adotta un approccio pratico reale al flusso di lavoro ML attraverso un case study. Un team ML è chiamato a rispondere a numerosi requisiti aziendali e ad affrontare vari casi d'uso ML. Deve comprendere gli strumenti necessari per la gestione e la governance dei dati e considerare l'approccio migliore per la pre-elaborazione dei dati. Al team vengono presentate tre opzioni per creare modelli ML per due casi d'uso. Il corso spiega perché il team utilizzerà AutoML, BigQuery ML o l'addestramento personalizzato per raggiungere i propri obiettivi.

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Questo corso presenta i prodotti e i servizi per big data e di machine learning di Google Cloud che supportano il ciclo di vita dai dati all'IA. Esplora i processi, le sfide e i vantaggi della creazione di una pipeline di big data e di modelli di machine learning con Vertex AI su Google Cloud.

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Completa il corso intermedio con badge delle competenze Crea l'infrastruttura con Terraform su Google Cloud per dimostrare le tue competenze nei seguenti ambiti: principi di Infrastructure as Code (IaC) utilizzando Terraform, provisioning e gestione di risorse Google Cloud con configurazioni Terraform, gestione efficace dello stato (locale e remoto) e modularizzazione del codice Terraform per la riusabilità e l'organizzazione.

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Guadagna un badge delle competenze completando il corso Sviluppa la tua rete Google Cloud, in cui apprenderai diversi modi per eseguire il deployment e il monitoraggio delle applicazioni, tra cui: esplorare i ruoli IAM e aggiungere/rimuovere l'accesso ai progetti, creare reti VPC, eseguire il deployment e il monitoraggio delle VM di Compute Engine, scrivere query SQL, eseguire il deployment e il monitoraggio delle VM in Compute Engine ed eseguire il deployment delle applicazioni utilizzando Kubernetes con più approcci al deployment.

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Ottieni un badge delle competenze completando il corso Configura un ambiente di sviluppo di app su Google Cloud, in cui imparerai a creare e connettere un'infrastruttura cloud incentrata sull'archiviazione utilizzando le funzionalità di base delle seguenti tecnologie: Cloud Storage, Identity and Access Management, Cloud Functions e Pub/Sub.

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Completa il corso introduttivo con badge delle competenze Implementazione di Cloud Load Balancing per Compute Engine per dimostrare le tue competenze nei seguenti ambiti: creazione ed esecuzione del deployment di macchine virtuali in Compute Engine e configurazione di bilanciatori del carico di rete e delle applicazioni.

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Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.

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Ti diamo il benvenuto nel corso Introduzione a Google Kubernetes Engine. Se ti interessa Kubernetes, un livello software che si trova tra le tue applicazioni e la tua infrastruttura hardware, allora sei nel posto giusto. Google Kubernetes Engine ti offre Kubernetes come servizio gestito su Google Cloud. L'obiettivo di questo corso è illustrare le nozioni di base di Google Kubernetes Engine, o GKE, come viene comunemente chiamato, e come containerizzare le applicazioni e farle funzionare su Google Cloud. Il corso inizia con un'introduzione di base a Google Cloud, seguita da una panoramica dei container e di Kubernetes, dell'architettura di Kubernetes e delle operazioni di Kubernetes.

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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building and managing Google Cloud resources using Terraform.

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Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura completa e flessibile e i servizi di piattaforma forniti da Google Cloud. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui interconnessione sicura delle reti, bilanciamento del carico, scalabilità automatica, automazione dell'infrastruttura e servizi gestiti.

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Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura e i servizi di piattaforma flessibili e completi di Google Cloud con particolare attenzione a Compute Engine. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui i componenti dell'infrastruttura come reti, macchine virtuali e servizi per applicazioni, ed eseguirne il deployment. Imparerai a utilizzare Google Cloud mediante la console e Cloud Shell. Scoprirai inoltre il ruolo del Cloud Architect, gli approcci alla progettazione dell'infrastruttura e la configurazione del networking virtuale con VPC (Virtual Private Cloud), progetti, reti, subnet, indirizzi IP, route e regole firewall.

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Questo corso accelerato on demand illustra ai partecipanti l'infrastruttura e i servizi di piattaforma flessibili e completi di Google Cloud con particolare attenzione a Compute Engine. Attraverso una combinazione di videolezioni, demo e lab pratici, i partecipanti potranno esplorare gli elementi delle soluzioni, tra cui i componenti dell'infrastruttura come reti, sistemi e servizi per applicazioni, ed eseguirne il deployment. Questo corso tratta inoltre del deployment di soluzioni pratiche quali, ad esempio, chiavi di crittografia fornite dal cliente, gestione di sicurezza e accessi, quote e fatturazione, monitoraggio delle risorse.

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Google Cloud Fundamentals: Core Infrastructure introduce concetti e terminologia importanti per lavorare con Google Cloud. Attraverso video e lab pratici, questo corso presenta e confronta molti dei servizi di computing e archiviazione di Google Cloud, insieme a importanti strumenti di gestione delle risorse e dei criteri.

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Learn how to use Gemini Notebook to create a personalized study guide for the Associate Cloud Engineer certification exam. You'll review Gemini Notebook features, create a notebook in Gemini Notebook , and learn how to use a study guide to practice for a certification exam.

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