Build Infrastructure with Terraform on Google Cloud
Earned mai 29, 2022 EDT
Integrate with Machine Learning APIs
Earned mai 29, 2022 EDT
DEPRECATED Developing Data and Machine Learning Apps with C#
Earned mai 29, 2022 EDT
Create ML Models with BigQuery ML
Earned mai 29, 2022 EDT
Develop Serverless Applications on Cloud Run
Earned mai 29, 2022 EDT
Build a Data Warehouse with BigQuery
Earned mai 27, 2022 EDT
BigQuery for Machine Learning
Earned nov. 4, 2021 EDT
API d'apprentissage automatique
Earned nov. 3, 2021 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned nov. 3, 2021 EDT
Baseline: Data, ML, AI
Earned nov. 3, 2021 EDT
Prepare Data for Looker Dashboards and Reports
Earned nov. 2, 2021 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned nov. 2, 2021 EDT
Building Codeless Pipelines on Cloud Data Fusion
Earned oct. 25, 2020 EDT
Derive Insights from BigQuery Data
Earned oct. 25, 2020 EDT
Monitor and Log with Google Cloud Observability
Earned oct. 24, 2020 EDT
Data Catalog Fundamentals
Earned oct. 23, 2020 EDT
Data Science sur la plateforme Google Cloud: Apprentissage automatique
Earned oct. 23, 2020 EDT
Google Cloud Solutions II: Data and Machine Learning
Earned oct. 22, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned oct. 21, 2020 EDT
Prepare Data for ML APIs on Google Cloud
Earned oct. 21, 2020 EDT
Intro to ML: Language Processing
Earned oct. 20, 2020 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned oct. 20, 2020 EDT
BigQuery for Data Warehousing
Earned oct. 19, 2020 EDT
Intro to ML: Image Processing
Earned oct. 18, 2020 EDT
Getting Started with Go on Google Cloud
Earned oct. 17, 2020 EDT
Google Cloud Run Serverless Workshop
Earned oct. 16, 2020 EDT
Build a Website on Google Cloud
Earned oct. 16, 2020 EDT
Perform Foundational Infrastructure Tasks in Google Cloud
Earned oct. 16, 2020 EDT
DEPRECATED Application Development - Python
Earned mai 3, 2020 EDT
DEPRECATED Application Development - Java
Earned mai 3, 2020 EDT
Google Kubernetes Engine Best Practices
Earned mai 3, 2020 EDT
Cloud Logging
Earned mai 3, 2020 EDT
[DEPRECATED] Deploying Applications
Earned mai 3, 2020 EDT
Baseline: Deploy & Develop
Earned mai 2, 2020 EDT
Cloud SQL
Earned mai 2, 2020 EDT
Optimize Your Google Cloud Costs
Earned mai 1, 2020 EDT
Security & Identity Fundamentals
Earned mai 1, 2020 EDT
Baseline: Infrastructure
Earned mai 1, 2020 EDT
DevOps Essentials
Earned mai 1, 2020 EDT
VM Migration
Earned avr. 30, 2020 EDT
Kubernetes in Google Cloud
Earned avr. 30, 2020 EDT
Understand Your Google Cloud Costs
Earned avr. 29, 2020 EDT
Google Cloud Essentials
Earned avr. 23, 2020 EDT
Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Il n’a échappé à personne que le machine learning est une technologie qui enregistre des records de croissance, et Google Cloud a joué un rôle déterminant dans son développement. Doté d’une multitude d’API, Google Cloud dispose d’un outil pour pratiquement toutes les tâches de machine learning. Dans cette quête avancée, vous vous familiarisez avec les API de machine learning grâce à des ateliers portant sur la détection d’étiquettes, de visages et de points de repère sur des images grâce à l’API Cloud Vision. Terminez cette quête et réussissez l’atelier challenge de fin pour recevoir un badge numérique Google Cloud exclusif. L’atelier challenge ne vous donne pas d’étapes à suivre. Vous devez créer des solutions à partir d’un minimum d’indications et vos compétences dans les technologies Google Cloud seront mises à l’épreuve. À la fin de cette quête, réussissez l’atelier challenge de la quête Integrate with Machine Learning APIs pour recevoir un badge numérique Google Cloud exclusif.
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C# has powered Windows .NET application development for nearly two decades and Google Cloud is committed to supporting developers getting their .NET workloads up and running on Google Cloud. In this quest, you will learn how to run C# apps in Google Cloud, and specifically how to take your apps to the next level by interfacing them with the big data and machine learning APIs that are accessible now from C#. By enrolling in this quest you will see firsthand how seamlessly Google Cloud integrates with .NET workloads and what the possibilities are for leveraging big data and ML services in your own C# projects.
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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in the following: creating and evaluating machine learning models with BigQuery ML to make data predictions. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the intermediate Develop Serverless Applications on Cloud Run skill badge 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. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge 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. 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 course, and final assessment challenge lab, to receive a digital badge that you can share with your network. For practice with BigQuery fundamentals (including working with the console and command line), complete the course titled BigQuery Basics for Data Analysts.
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Vous voulez vous familiariser avec le machine learning et créer des modèles en quelques minutes grâce à SQL, pour ne plus y consacrer des heures ? BigQuery Machine Learning est une nouvelle fonctionnalité de BigQuery qui permet aux analystes de données de créer et d'entraîner des modèles de machine learning en vue de faire des prédictions, le tout avec un minimum de codage. Dans cette série d'ateliers, vous allez essayer différents types de modèles et apprendre ce qui caractérise un bon modèle.
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Il n'a échappé à personne que le machine learning est une technologie très dynamique, et Google Cloud Platform a joué un rôle déterminant dans son développement. Doté d'une multitude d'API.
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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.
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Aujourd'hui, le big data, le machine learning et l'intelligence artificielle sont des thèmes récurrents de l'informatique, mais ces domaines sont spécialisés, et il est ardu de dénicher du matériel de référence. Heureusement, GCP fournit des services conviviaux dans ces domaines, et Qwiklabs vous y forme dans cette quête introductive. Ainsi, vous pourrez faire vos premiers pas avec des outils tels que BigQuery, l'API Cloud Speech et Cloud ML Engine. Des vidéos d'une minute résument les concepts clés de chaque atelier.
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Complete the introductory Prepare Data for Looker Dashboards and Reports skill badge 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. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
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This quest offers hands-on practice with Cloud Data Fusion, a cloud-native, code-free, data integration platform. ETL Developers, Data Engineers and Analysts can greatly benefit from the pre-built transformations and connectors to build and deploy their pipelines without worrying about writing code. This Quest starts with a quickstart lab that familiarises learners with the Cloud Data Fusion UI. Learners then get to try running batch and realtime pipelines as well as using the built-in Wrangler plugin to perform some interesting transformations on data.
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Complete the introductory Derive Insights from BigQuery Data skill badge 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, and create reports in Looker Studio by connecting to BigQuery data. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Complete the introductory Monitor and Log with Google Cloud Observability skill badge to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, understand, and manage all of their data. In this quest you will start small by learning how to search and tag data assets and metadata with Data Catalog. After learning how to build your own tag templates that map to BigQuery table data, you will learn how to build MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors.
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Il s'agit de la deuxième quête des ateliers dérivés des exercices du livre Data Science on Google Cloud Platform de Valliappa Lakshmanan, publié par O'Reilly Media, Inc. Dans cette seconde quête, qui couvre du chapitre neuf à la fin du livre, vous développez les compétences acquises lors de la première quête et exécutez des tâches de machine learning de A à Z avec des outils de pointe et des ensembles de données réels, le tout à l'aide des outils et services de Google Cloud Platform.
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In this advanced-level quest, you will learn how to harness serious Google Cloud computing power to run big data and machine learning jobs. The hands-on labs will give you use cases, and you will be tasked with implementing big data and machine learning practices utilized by Google’s very own Solutions Architecture team. From running Big Query analytics on tens of thousands of basketball games, to training TensorFlow image classifiers, you will quickly see why Google Cloud is the go-to platform for running big data and machine learning jobs.
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TensorFlow is an open source software library for high performance numerical computation that's great for writing models that can train and run on platforms ranging from your laptop to a fleet of servers in the Cloud to an edge device. This quest takes you beyond the basics of using predefined models and teaches you how to build, train and deploy your own on Google Cloud.
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API. 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 course, and the final assessment challenge lab, to receive a skill badge that you can share with your network.
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Il n'a échappé à personne que le machine learning est une technologie très dynamique, et Google Cloud Platform a joué un rôle déterminant dans son développement. Doté d'une multitude d'API, GCP dispose d'un outil pour pratiquement toutes les tâches de machine learning. Cette quête de présentation vous permet de vous familiariser avec le machine learning sur des applications de traitement du langage. Au fil des ateliers, vous apprendrez à extraire des entités d'un texte, à analyser les sentiments et la syntaxe, et à utiliser l'API de reconnaissance vocale pour la transcription.
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With Google Assistant part of over a billion consumer devices, this quest teaches you how to build practical Google Assistant applications integrated with Google Cloud services via APIs. Example apps will use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks. You will build 5 different applications that explore useful and fun tools you can extend on your own. No hardware required! These labs use the cloud-based Google Assistant simulator environment for developing and testing, but if you do have your own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy your apps to your own hardware.
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Vous voulez créer un entrepôt de données ou l'optimiser ? Découvrez les bonnes pratiques d'extraction, de transformation et de chargement des données dans Google Cloud avec BigQuery. Dans cette série d'ateliers interactifs, vous allez créer votre propre entrepôt de données et l'optimiser en utilisant différents ensembles de données publics à grande échelle de BigQuery. BigQuery est la base de données d'analyse à faible coût de Google, entièrement gérée et qui ne nécessite aucune opération (NoOps). Avec BigQuery, vous pouvez interroger des téraoctets de données sans avoir à gérer d'infrastructure ni faire appel à un administrateur de base de données. Basé sur le langage SQL et le modèle de paiement à l'usage, BigQuery vous permet de vous concentrer sur l'analyse des données pour en dégager des informations pertinentes.
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L'une des technologies de base de l'IA, que l'on retrouve des voitures autonomes à la reconnaissance faciale, repose sur l'utilisation de la puissance de calcul à grande échelle pour reconnaître des schémas et "lire" des images. La plate-forme Google Cloud offre une vitesse et une précision haut de gamme grâce à des systèmes qui peuvent être utilisés via de simples appels d'API. Doté d'une multitude d'API, GCP dispose d'un outil pour pratiquement toutes les tâches de machine learning. Cette quête de présentation vous permet de vous familiariser avec le machine learning appliqué au traitement des images. Au fil des ateliers, vous apprendrez à attribuer une étiquette aux images, à détecter les visages et les points de repère, ainsi qu'à extraire, analyser et traduire le texte dans les images.
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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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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google…
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Earn the introductory skill badge by completing the Build a Website on Google Cloud course. This course is based on the series Get Cooking in Cloud, where you learn how to: Deploy a website on Cloud Run; Host a web app on Compute Engine; Create, deploy, and scale your website on Google Kubernetes Engine; Migrate from a monolithic application to a microservices architecture using Cloud Build. 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, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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Si vous êtes un développeur cloud débutant et que vous souhaitez vous faire la main au-delà de "Getting Started - Create and Manage Cloud Resources", cette quête est faite pour vous. Elle vous permettra d'acquérir de l'expérience pratique grâce aux ateliers qui traitent en profondeur de Cloud Storage et d'autres services applicatifs clés tels que Stackdriver et Cloud Functions. En participant à cette quête, vous développerez des compétences précieuses que vous pourrez utiliser dans tous vos projets Google Cloud. Terminez cette quête, y compris le laboratoire de défi à la fin, pour recevoir un badge numérique exclusif de Google Cloud. Des vidéos d'une minute résument les concepts clés de chaque atelier.
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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Python. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Python applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Python applications straight away.
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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Java. The first labs will walk you through the basics of environment setup and application data storage with Cloud Datastore. Once you have a handle on the fundamentals, you will get hands-on practice deploying Java applications on Kubernetes and App Engine (the latter is the same framework that powers Snapchat!) With specialized bonus labs that teach user authentication and backend service development, this quest will give you practical experience so you can start developing robust Java applications straight away.
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Get Anthos Ready. Demand for Google Kubernetes Engine is growing, and customers are looking to Google and its partners to provide in-depth technical knowledge. This first Google Kubernetes Engine-centric Quest of best practices hands-on labs will get you started containerizing to modernize in place , and then managing your deployed apps and services -- with monitoring, tracing, and logging.
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Cloud Logging is a fully managed service that performs at scale. It can ingest application and system log data from thousands of VMs and, even better, analyze all that log data in real time. In this fundamental-level Quest, you learn how to store, search, analyze, monitor, and alert on log data and events from Google Cloud. The labs in the Quest give you hands-on practice using Cloud Logging to maximize your learning experience and provide insight on how you can use Cloud Logging to your own Google Cloud environment.
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The Google Cloud Platform provides many different frameworks and options to fit your application’s needs. In this introductory-level quest, you will get plenty of hands-on practice deploying sample applications on Google App Engine. You will also dive into other web application frameworks like Firebase, Wordpress, and Node.js and see firsthand how they can be integrated with Google Cloud.
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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.
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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.
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Cette quête est la deuxième d'une série en deux parties consacrée aux principes de base de la gestion des coûts et de la facturation GCP. Elle convient plus particulièrement aux personnes qui travaillent dans des services technologiques ou financiers, et qui sont chargées d'optimiser l'infrastructure cloud de leur organisation. Dans cette quête, vous allez découvrir plusieurs façons de maîtriser et d'optimiser les coûts GCP, y compris en établissant des budgets et des alertes, en gérant les limites de quota et en bénéficiant de remises sur engagement d'utilisation. Dans les ateliers pratiques, vous utiliserez divers outils pour maîtriser et optimiser vos coûts GCP, ou pour inciter vos équipes technologiques à suivre les bonnes pratiques dans ce domaine.
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Les services Google Cloud ne font pas l'impasse sur la sécurité, qui est primordiale. En ce sens, Google Cloud a développé des outils spécifiques pour garantir la sécurité et l'identité de vos projets. Dans cette quête fondamentale, vous vous familiariserez avec le service IAM (gestion de l'authentification et des accès) de GCM, la référence en matière de gestion des comptes d'utilisateur et de machine virtuelle. Vous développerez vos compétences en matière de sécurité réseau en provisionnant des VPC et des VPN, et découvrirez les outils existants pour lutter contre les menaces de sécurité et la perte de données.
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Si vous êtes un développeur cloud débutant et que vous souhaitez vous faire la main au-delà de "GCP Essentials", cette quête est faite pour vous. Elle vous permettra d'acquérir de l'expérience pratique grâce aux ateliers qui traitent en profondeur de Cloud Storage et d'autres services applicatifs clés tels que Stackdriver et Cloud Functions. En participant à cette quête, vous développerez des compétences précieuses que vous pourrez utiliser dans tous vos projets GCP. Des vidéos d'une minute résument les concepts clés de ces ateliers.
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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this quest you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out! Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google Cloud digital badge.
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La méthodologie de migration des VM de Google Cloud fournit aux utilisateurs un chemin défini et reproductible. Dans cette quête, vous vous familiariserez avec cette séquence de migration en quatre phases. Vous établirez des rapports d'évaluation avec CloudPhysics, vous utiliserez les modèles d'infrastructure en tant que code de Terraform, vous effectuerez des migrations Lift and Shift avec Cloud Endure et pour finir, vous répliquerez des applications sous la forme de charges de travail cloud natives. Inscrivez-vous à cette quête et familiarisez-vous avec les solutions Google pour la migration de VM. En prime, pour ceux qui ont besoin d'une petite révision, nous incluons un atelier de présentation de Google Kubernetes Engine.
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Kubernetes est le système d'orchestration de conteneurs le plus populaire, et Google Kubernetes Engine a été conçu spécifiquement pour être compatible avec les déploiements gérés de Kubernetes dans Google Cloud. Dans cette quête avancée, vous apprendrez à configurer et à manipuler les images et les conteneurs Docker, ainsi qu'à déployer des applications Kubernetes Engine opérationnelles. Cette quête vous fournira les compétences pratiques nécessaires pour intégrer l'orchestration de conteneurs à votre propre flux de travail.
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Cette quête s'adresse particulièrement aux personnes qui travaillent dans les technologies ou les finances et qui sont responsables de la gestion des coûts de GCP. Vous apprendrez à configurer un compte de facturation, à organiser les ressources et à gérer les autorisations d'accès à la facturation. Grâce aux ateliers pratiques, vous apprendrez à visualiser votre facture, à suivre vos coûts GCP à l'aide de rapports de facturation, à analyser vos données de facturation avec BigQuery ou Google Sheets et à créer des tableaux de bord de facturation personnalisés avec Data Studio.
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Cette quête d'introduction se compose d'ateliers pratiques qui vous permettent de vous familiariser avec les outils et services de base de Google Cloud Platform. "GCP Essentials" est la première quête recommandée pour les personnes s'intéressant à Google Cloud. Vous pouvez la suivre sans aucune connaissance (ou presque) du cloud et, une fois la quête terminée, vous disposerez de compétences pratiques qui vous seront utiles pour n'importe quel projet GCP. De l'écriture de lignes de commande Cloud Shell au déploiement de votre première machine virtuelle en passant par l'exécution d'applications sur Kubernetes Engine avec l'équilibrage de charge, "GCP Essentials" constitue une excellente introduction aux fonctionnalités de base de la plate-forme. Des vidéos d'une minute résument les concepts clés de ces ateliers.
Build Infrastructure with Terraform on Google Cloud
Earned mai 29, 2022 EDT
Integrate with Machine Learning APIs
Earned mai 29, 2022 EDT
DEPRECATED Developing Data and Machine Learning Apps with C#
Earned mai 29, 2022 EDT
Create ML Models with BigQuery ML
Earned mai 29, 2022 EDT
Develop Serverless Applications on Cloud Run
Earned mai 29, 2022 EDT
Build a Data Warehouse with BigQuery
Earned mai 27, 2022 EDT
BigQuery for Machine Learning
Earned nov. 4, 2021 EDT
API d'apprentissage automatique
Earned nov. 3, 2021 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned nov. 3, 2021 EDT
Baseline: Data, ML, AI
Earned nov. 3, 2021 EDT
Prepare Data for Looker Dashboards and Reports
Earned nov. 2, 2021 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned nov. 2, 2021 EDT
Building Codeless Pipelines on Cloud Data Fusion
Earned oct. 25, 2020 EDT
Derive Insights from BigQuery Data
Earned oct. 25, 2020 EDT
Monitor and Log with Google Cloud Observability
Earned oct. 24, 2020 EDT
Data Catalog Fundamentals
Earned oct. 23, 2020 EDT
Data Science sur la plateforme Google Cloud: Apprentissage automatique
Earned oct. 23, 2020 EDT
Google Cloud Solutions II: Data and Machine Learning
Earned oct. 22, 2020 EDT
Intermediate ML: TensorFlow on Google Cloud
Earned oct. 21, 2020 EDT
Prepare Data for ML APIs on Google Cloud
Earned oct. 21, 2020 EDT
Intro to ML: Language Processing
Earned oct. 20, 2020 EDT
![Badge pour [DEPRECATED] OK Google: Build Interactive Apps with Google Assistant](https://cdn.qwiklabs.com/iN1Y1aBXjPPUZgDdv9GtQCf%2FBp0q3U%2FJg9uWO6RMKoc%3D)
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned oct. 20, 2020 EDT
BigQuery for Data Warehousing
Earned oct. 19, 2020 EDT
Intro to ML: Image Processing
Earned oct. 18, 2020 EDT
Getting Started with Go on Google Cloud
Earned oct. 17, 2020 EDT
Google Cloud Run Serverless Workshop
Earned oct. 16, 2020 EDT
Build a Website on Google Cloud
Earned oct. 16, 2020 EDT
Perform Foundational Infrastructure Tasks in Google Cloud
Earned oct. 16, 2020 EDT
DEPRECATED Application Development - Python
Earned mai 3, 2020 EDT
DEPRECATED Application Development - Java
Earned mai 3, 2020 EDT
Google Kubernetes Engine Best Practices
Earned mai 3, 2020 EDT
Cloud Logging
Earned mai 3, 2020 EDT
![Badge pour [DEPRECATED] Deploying Applications](https://cdn.qwiklabs.com/1r8IzkgZ2ozf6jLcsKK81SdLwBzAL1f1vyuNmbXyhjE%3D)
[DEPRECATED] Deploying Applications
Earned mai 3, 2020 EDT
Baseline: Deploy & Develop
Earned mai 2, 2020 EDT
Cloud SQL
Earned mai 2, 2020 EDT
Optimize Your Google Cloud Costs
Earned mai 1, 2020 EDT
Security & Identity Fundamentals
Earned mai 1, 2020 EDT
Baseline: Infrastructure
Earned mai 1, 2020 EDT
DevOps Essentials
Earned mai 1, 2020 EDT
VM Migration
Earned avr. 30, 2020 EDT
Kubernetes in Google Cloud
Earned avr. 30, 2020 EDT
Understand Your Google Cloud Costs
Earned avr. 29, 2020 EDT
Google Cloud Essentials
Earned avr. 23, 2020 EDT