Using the Cloud SDK Command Line
Earned wrz 1, 2020 EDT
Google Cloud Essentials
Earned sie 23, 2020 EDT
Google Workspace Essentials
Earned sie 15, 2020 EDT
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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To szybkie szkolenie dla początkujących wyjaśnia, czym są duże modele językowe (LLM) oraz jakie są ich zastosowania. Przedstawia również możliwości zwiększenia ich wydajności przez dostrajanie przy użyciu promptów oraz narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.
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Celem tego szybkiego szkolenia dla początkujących jest wyjaśnienie, czym jest generatywna AI oraz jakie są jej zastosowania. Szkolenie przedstawia również różnice pomiędzy tą technologią a tradycyjnymi systemami uczącymi się, a także narzędzia Google, które pomogą Ci tworzyć własne aplikacje korzystające z generatywnej AI.
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Learn the ins and outs of Google Cloud's operations suite, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. These labs will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the challenge lab at the end of the Monitor and Log with Google Cloud Operations Suite to receive an exclusive Google Cloud digital badge.
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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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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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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.
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Complete the intermediate Optimize Costs for Google Kubernetes Engine skill badge course to demonstrate skills in the following: creating and managing multi-tenant clusters, monitoring resource usage by namespace, configuring cluster and pod autoscaling for efficiency, setting up load balancing for optimal resource distribution, and implementing liveness and readiness probes to ensure application health and cost-effectiveness.
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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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This course helps learners create a study plan for the PCA (Professional Cloud Architect) 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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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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Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on Google Cloud.
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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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Welcome to the Getting Started with Google Kubernetes Engine course. If you're interested in Kubernetes, a software layer that sits between your applications and your hardware infrastructure, then you’re in the right place! Google Kubernetes Engine brings you Kubernetes as a managed service on Google Cloud.
The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, as it’s commonly referred to, and how to get applications containerized and running in Google Cloud. The course starts with a basic introduction to Google Cloud, and is then followed by an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.
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Szkolenie Podstawy przetwarzania danych w Google Cloud pozwoli osobom z niewielkim
lub zerowym doświadczeniem z zakresu przetwarzania danych w chmurze szczegółowo
zapoznać się z najważniejszymi pojęciami z zakresu podstaw chmury, big data i systemów uczących się.
Zawiera także informacje o tym, gdzie i jak można wykorzystać Google Cloud.
Po zakończeniu szkolenia uczestnicy będą potrafili wyjaśnić pojęcia dotyczące przetwarzania danych w chmurze,
big data i systemów uczących się oraz zademonstrować wybrane umiejętności praktyczne.
To szkolenie należy do serii szkoleń o nazwie Google Cloud Computing Foundations (Podstawy usług w chmurze Google).
Szkolenia należy ukończyć w następującej kolejności:
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 Foundation…
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This is the second of two Quests of hands-on labs derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this second Quest, covering chapter 9 through the end of the book, you extend the skills practiced in the first Quest, and run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud tools and services.
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In this quest you will learn about the four Google Cloud website architectures available to ensure that your website is available and scalable. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional challenge lab at the end of this Build a Website on Google Cloud to receive an exclusive Google Cloud digital badge. This quest is based on the video series Get Cooking in Cloud.
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Aby zdobyć odznakę umiejętności potwierdzającą opanowanie podstaw, ukończ kurs wprowadzający Tworzenie witryny w Google Cloud. Jest on oparty na serii materiałów wideo Get Cooking in Cloud i obejmuje te tematy: Wdrażanie witryny w Cloud RunHostowanie aplikacji internetowej w Compute EngineTworzenie, wdrażanie i skalowanie witryny w Google Kubernetes EngineMigracja z aplikacji monolitycznej do architektury mikroserwisów przy użyciu Cloud Build
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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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This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in either of those courses. Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective.
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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.
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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, virtual machines and applications services. You will learn how to use the Google Cloud through the console and Cloud Shell. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.
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Szkolenie Google Cloud Fundamentals: Core Infrastructure wprowadza ważne pojęcia i terminologię potrzebne w pracy z Google Cloud. Za pomocą filmów i praktycznych modułów szkolenie prezentuje oraz porównuje usługi Google Cloud umożliwiające między innymi przetwarzanie i przechowywanie danych, a także zawiera ważne materiały i narzędzia do zarządzania zasadami.
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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
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Aby zdobyć odznakę umiejętności, ukończ szkolenie Budowanie bezpiecznej sieci Google Cloud, w trakcie którego poznasz różne związane z siecią zasoby do budowania, skalowania i zabezpieczania aplikacji w Google Cloud.
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Ukończ szkolenie wprowadzające Uzyskiwanie statystyk z danych BigQuery, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: pisanie zapytań SQL, tworzenie zapytań dotyczących tabel publicznych, wczytywanie przykładowych danych w BigQuery, naprawianie typowych błędów składniowych przy użyciu walidatora zapytań w BigQuery oraz tworzenie raportów w Looker Studio przez tworzenie połączenia z danymi BigQuery.
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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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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 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 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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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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Aby zdobyć odznakę umiejętności, ukończ szkolenie Konfigurowanie środowiska programistycznego w Google Cloud, w trakcie którego dowiesz się, jak utworzyć i podłączyć infrastrukturę w chmurzę do przechowywania danych przy użyciu podstawowych funkcji technologii Cloud Storage, Identity and Access Management, Cloud Functions oraz Pub/Sub.
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Aby zdobyć odznakę umiejętności, ukończ szkolenie Budowanie sieci w Google Cloud, w trakcie którego poznasz różne sposoby wdrażania i monitorowania aplikacji i dowiesz się, jak: przeglądać role uprawnień, dodawać/usuwać dostęp do projektu, tworzyć sieci VPC, wdrażać i monitorować maszyny wirtualne Compute Engine, pisać zapytania SQL oraz wdrażać aplikacje przy użyciu różnych metod w Kubernetes.
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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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In honor of the Launch of the Google Cloud Community and the Learning & Certification Hub (bit.ly/3gNtlMB), we’ve devised a fun little game to catapult your skills in BigQuery and give you a chance to win the First. Ever. Community. Learning. Challenge. (Pause for effect) Not only will participating in this game give you hands-on practice to boost key skills in BQ, but simply participating will earn you some sweet online badges. Plus, the winner of the game will be rewarded...handsomely . More details below... Complete every activity in this game and earn a Skill Badge which you can share across your network with pride. Complete every activity AND post a screenshot of your newly minted Skill Badge in the Learning Forum area of the Community (bit.ly/35LoLIB) to earn a special Community Badge which you can then flaunt over other community members shamelessly. The Community member at the top of the scoreboard at the time the game is closed will be rewarded with something objectively …
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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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Firebase is a backend-as-service (Bass) platform for creating mobile and web applications. In this quest you will learn to build serverless web apps, import data into a serverless database, and build a Google Assistant application with Firebase and its Google Cloud integrations. 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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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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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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Ukończ szkolenie wprowadzające Przygotowywanie danych do użycia z interfejsami ML w Google Cloud, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: czyszczenie danych przy użyciu usługi Dataprep firmy Trifacta, uruchamianie potoków danych w Dataflow, tworzenie klastrów i uruchamianie zadań Apache Spark w Dataproc, a także wywoływanie interfejsów API dotyczących uczenia maszynowego, w tym Cloud Natural Language API, Google Cloud Speech-to-Text API oraz Video Intelligence API.
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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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Szkolenie Podstawy przetwarzania danych w Google Cloud pozwoli osobom z niewielkim lub zerowym doświadczeniem z zakresu
przetwarzania danych w chmurze szczegółowo zapoznać się z najważniejszymi pojęciami z zakresu podstaw chmury, big data i systemów uczących się.
Zawiera także informacje o tym, gdzie i jak można wykorzystać Google Cloud.
Po zakończeniu szkolenia uczestnicy będą potrafili wyjaśnić pojęcia dotyczące przetwarzania danych w chmurze, big data i systemów uczących się oraz
zademonstrować wybrane umiejętności praktyczne.
TTo szkolenie należy do serii szkoleń o nazwie Google Cloud Computing Foundations (Podstawy usług w chmurze Google).
Szkolenia należy ukończyć w następującej kolejności:
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 Foundatio…
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In this fundamental-level course, you will learn the ins and outs of Google Cloud's operations suite running on Google Kubernetes Engine, an important service for generating insights into the health of your applications. It provides a wealth of information in application monitoring, report logging, and diagnoses. The labs in this course will give you hands-on practice with and will teach you how to monitor virtual machines, generate logs and alerts, and create custom metrics for application data. It is recommended that the students have at least earned a Badge by completing the Google Cloud Essentials course. Additional lab experience with the labs in the Baseline - Infrastructure course will also be useful. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this course, enroll in and finish the additional challenge lab at the end of this course to receive an exclusive Google Cloud digital badge.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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This course is most suitable for those working in a technology or finance role who are responsible for managing Google Cloud costs. You’ll learn how to set up a billing account, organize resources, and manage billing access permissions. In the hands-on labs, you'll learn how to view your invoice, track your Google Cloud costs with Billing reports, analyze your billing data with BigQuery or Google Sheets, and create custom billing dashboards with Looker Studio. References made to links in the videos can be accessed in this Additional Resources document.
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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.
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If you’re looking to take your Google Cloud application to the next level, look no further than Deployment Manager. By automating the creation of GCP resources and services, Deployment Manager lets you focus on developing rather than maintaining. In this advanced-level quest, you will get hands on practice with Deployment Manager by building custom templates, automating Python and Jinja application instances, and scaling custom networks.
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Ten kurs wprowadzający jest inny niż wszystkie pozostałe oferowane kursy. Jego moduły zostały wybrane tak, aby udostępnić specjalistom z branży IT praktyczne ćwiczenia w zakresie tematów i usług, znajomość których jest potrzebna do uzyskania certyfikatu Google Cloud Associate Cloud Engineer. Od uprawnień i zarządzania siecią po wdrażanie Kubernetes Engine – ten kurs składa się ze specjalnych modułów, w trakcie których sprawdzisz swoją wiedzę na temat Google Cloud. Ćwiczenia w ramach tych modułów pozwolą Ci zwiększyć swoje umiejętności i kompetencje, ale zalecamy również zapoznanie się z przewodnikiem po egzaminie i innymi dostępnymi materiałami przygotowawczymi.
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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 course 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!
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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.
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Jeśli dopiero zaczynasz programować w chmurze i szukasz praktycznych ćwiczeń wykraczających poza treści z kursu „Podstawy Google Cloud”, ten kurs jest dla Ciebie. Zdobędziesz praktyczne doświadczenie dzięki modułom poświęconym Cloud Storage i innym kluczowym usługom aplikacji, takim jak Monitoring i Cloud Functions. Zdobędziesz cenne umiejętności, które przydadzą się w każdym przedsięwzięciu z zastosowaniem Google Cloud.
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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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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model.
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This course demonstrates the power of integrating Google Cloud services and tools with Workspace applications - like using Node.js to build a survey bot, the Natural Language API to recognize sentiment in a Google Doc, and building a chat bot with Apps Script.
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It's no secret that machine learning is one of the fastest growing fields in tech, and Google Cloud has been instrumental in furthering its development. With a host of APIs, Google Cloud has a tool for just about any machine learning job. In this advanced-level course, you will get hands-on practice with machine learning APIs by taking labs like Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? 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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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory course, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.
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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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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.
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Using large scale computing power to recognize patterns and "read" images is one of the foundational technologies in AI, from self-driving cars to facial recognition. The Google Cloud Platform provides world class speed and accuracy via systems that can utilized by simply calling APIs. With these and a host of other APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to image processing by taking labs that will enable you to label images, detect faces and landmarks, as well as extract, analyze, and translate text from within images.
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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
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Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines.
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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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Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
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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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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. 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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Data Catalog is deprecated and will be discontinued on January 30, 2026. You can still complete this course if you want to. For steps to transition your Data Catalog users, workloads, and content to Dataplex Catalog, see Transition from Data Catalog to Dataplex Catalog (https://cloud.google.com/dataplex/docs/transition-to-dataplex-catalog). 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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Looking to build or optimize your data warehouse? Learn best practices to Extract, Transform, and Load your data into Google Cloud with BigQuery. In this series of interactive labs you will create and optimize your own data warehouse using a variety of large-scale BigQuery public datasets. 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. 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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This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. 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 the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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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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Want to learn the core SQL and visualization skills of a Data Analyst? Interested in how to write queries that scale to petabyte-size datasets? Take the BigQuery for Analyst Quest and learn how to query, ingest, optimize, visualize, and even build machine learning models in SQL inside of BigQuery.
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Big data, uczenie maszynowe i sztuczna inteligencja to najpopularniejsze tematy współczesnej informatyki, jednak to dość wyspecjalizowane dziedziny i trudno znaleźć materiały wprowadzające do nich. Na szczęście Google Cloud udostępnia przyjazne dla użytkownika usługi w tych obszarach, a dzięki temu kursowi dla początkujących możesz poznać podstawy narzędzi takich jak BigQuery, Cloud Speech API i Video Intelligence.
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Ukończ szkolenie wprowadzające Wdrażanie równoważenia obciążenia Cloud Load Balancing w Compute Engine, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: tworzenie i wdrażanie maszyn wirtualnych w Compute Engine oraz konfigurowanie sieciowych systemów równoważenia obciążenia i systemów równoważenia obciążenia aplikacji.
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For everyone using Google Cloud Platform for the first time, getting familar with gcloud, Google Cloud's command line, will help you get up to speed faster. In this quest, you'll learn how to install and configure Cloud SDK, then use gcloud to perform some basic operations like creating VMs, networks, using BigQuery, and using gsutil to perform operations.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
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Workspace is Google's collaborative applications platform, delivered from Google Cloud. In this introductory-level course you will get hands-on practice with Workspace’s core applications from a user perspective. Although there are many more applications and tool components to Workspace than are covered here, you will get experience with the primary apps: Gmail, Calendar, Sheets and a handful of others. Each lab can be completed in 10-15 minutes, but extra time is provided to allow self-directed free exploration of the applications.
Serverless Data Processing with Dataflow: Foundations
Earned lut 14, 2026 EST
Introduction to Large Language Models - Polski
Earned lut 14, 2026 EST
Introduction to Generative AI - Polski
Earned lut 14, 2026 EST
DEPRECATED Google Cloud's Operations Suite
Earned maj 30, 2023 EDT
Getting Started with Terraform for Google Cloud
Earned kwi 16, 2023 EDT
Cloud Architecture: Design, Implement, and Manage
Earned kwi 2, 2023 EDT
Build Infrastructure with Terraform on Google Cloud
Earned kwi 1, 2023 EDT
Optimize Costs for Google Kubernetes Engine
Earned mar 31, 2023 EDT
Logging and Monitoring in Google Cloud
Earned mar 31, 2023 EDT
Preparing for your Professional Cloud Architect Journey
Earned mar 30, 2023 EDT
Cloud Logging
Earned mar 24, 2023 EDT
Advanced ML: ML Infrastructure
Earned mar 22, 2023 EDT
DEPRECATED Application Development - Python
Earned mar 20, 2023 EDT
Getting Started with Google Kubernetes Engine
Earned mar 19, 2023 EDT
[DEPRECATED] Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Earned mar 18, 2023 EDT
Data Science on Google Cloud: Machine Learning
Earned mar 18, 2023 EDT
Website on Google Cloud
Earned lut 11, 2023 EST
Tworzenie witryny w Google Cloud
Earned wrz 23, 2022 EDT
Develop Serverless Apps with Firebase
Earned wrz 23, 2022 EDT
Reliable Google Cloud Infrastructure: Design and Process
Earned kwi 28, 2022 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned kwi 27, 2022 EDT
Essential Google Cloud Infrastructure: Core Services
Earned kwi 27, 2022 EDT
Essential Google Cloud Infrastructure: Foundation
Earned kwi 27, 2022 EDT
Google Cloud Fundamentals: Core Infrastructure - Polski
Earned kwi 27, 2022 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned kwi 24, 2022 EDT
Budowanie bezpiecznej sieci Google Cloud
Earned lut 22, 2022 EST
Uzyskiwanie statystyk z danych BigQuery
Earned lut 20, 2022 EST
Implement Cloud Security Fundamentals on Google Cloud
Earned lut 19, 2022 EST
Build a Data Warehouse with BigQuery
Earned lut 19, 2022 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned lut 19, 2022 EST
Use Machine Learning APIs on Google Cloud
Earned lut 19, 2022 EST
Deploy Kubernetes Applications on Google Cloud
Earned lut 18, 2022 EST
Konfigurowanie środowiska programistycznego w Google Cloud
Earned lut 18, 2022 EST
Budowanie sieci w Google Cloud
Earned lut 17, 2022 EST
Create ML Models with BigQuery ML
Earned wrz 17, 2021 EDT
Launch & Learn: BigQuery Game
Earned lip 7, 2021 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant
Earned maj 4, 2021 EDT
Build Apps & Websites with Firebase
Earned maj 1, 2021 EDT
[DEPRECATED] Deploying Applications
Earned kwi 20, 2021 EDT
Baseline: Deploy & Develop
Earned sty 31, 2021 EST
Set Up a Google Cloud Network
Earned gru 31, 2020 EST
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud
Earned gru 28, 2020 EST
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned gru 15, 2020 EST
[DEPRECATED]-Google Cloud Computing Foundations: Cloud Computing Fundamentals - Polski
Earned gru 15, 2020 EST
DEPRECATED Google Cloud's Operations Suite on GKE
Earned gru 11, 2020 EST
DEPRECATED Cloud Architecture
Earned gru 4, 2020 EST
Understand Your Google Cloud Costs
Earned gru 3, 2020 EST
Kubernetes in Google Cloud
Earned gru 3, 2020 EST
Deployment Manager
Earned lis 30, 2020 EST
Inżynieria chmury
Earned lis 30, 2020 EST
DevOps Essentials
Earned lis 25, 2020 EST
Security & Identity Fundamentals
Earned lis 19, 2020 EST
Podstawy: infrastruktura
Earned lis 13, 2020 EST
Intermediate ML: TensorFlow on Google Cloud
Earned paź 6, 2020 EDT
BigQuery for Machine Learning
Earned paź 2, 2020 EDT
Workspace: Add-ons
Earned paź 1, 2020 EDT
Machine Learning APIs
Earned paź 1, 2020 EDT
Intro to ML: Language Processing
Earned paź 1, 2020 EDT
DEPRECATED Exploring APIs
Earned wrz 22, 2020 EDT
Google Developer Essentials
Earned wrz 12, 2020 EDT
Intro to ML: Image Processing
Earned wrz 12, 2020 EDT
Data Science on Google Cloud
Earned wrz 12, 2020 EDT
Scientific Data Processing
Earned wrz 12, 2020 EDT
Cloud SQL
Earned wrz 11, 2020 EDT
DEPRECATED Applied Data: Blockchain
Earned wrz 11, 2020 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned wrz 9, 2020 EDT
DEPRECATED BigQuery for Marketing Analysts
Earned wrz 9, 2020 EDT
Data Catalog Fundamentals
Earned wrz 9, 2020 EDT
DEPRECATED BigQuery for Data Warehousing
Earned wrz 9, 2020 EDT
[DEPRECATED] Data Engineering
Earned wrz 9, 2020 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned wrz 7, 2020 EDT
DEPRECATED BigQuery for Data Analysis
Earned wrz 7, 2020 EDT
Podstawy: dane, uczenie maszynowe, AI
Earned wrz 3, 2020 EDT
Wdrażanie równoważenia obciążenia Cloud Load Balancing w Compute Engine
Earned wrz 2, 2020 EDT
Using the Cloud SDK Command Line
Earned wrz 1, 2020 EDT
Google Cloud Essentials
Earned sie 23, 2020 EDT
Google Workspace Essentials
Earned sie 15, 2020 EDT