Tworzenie witryny w Google Cloud
Earned kwi 13, 2022 EDT
Google Cloud Essentials
Earned kwi 12, 2022 EDT
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud
Earned kwi 12, 2022 EDT
In this course, you learn how to develop an app using Flutter, Google's portable UI toolkit, and integrate the app with Gemini, Google's family of generative AI models. You also use Vertex AI Agent Builder, Google's platform for building and managing AI Agents and applications.
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Build AI agents that can leverage enterprise databases using the MCP Toolbox for Databases. You will define secure database interaction tools, and implement intelligent querying capabilities (leveraging vector embeddings, structured queries).
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Complete the intermediate Enhance Gemini Model Capabilities skill badge to demonstrate skills in the following: leveraging advanced features of Gemini models, including code generation and execution, grounding, controlled content generation, and synthetic data creation, to build more powerful and sophisticated AI applications.
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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.
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Earn a skill badge by completing the Kickstarting Application Development with Gemini Code Assist course, where you will learn to leverage the power of Google's AI coding assistant and multiple development tech
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Complete the introductory Monitoring in Google Cloud skill badge course to demonstrate skills in the following: using Cloud Monitoring tools to monitor resources on Google Cloud.
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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.
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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 intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.
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This video covers how to use Gemini and Apps Script to automate manual tasks across Google Workspace. You'll learn to prompt Gemini to generate Apps Script code that automatically drafts email reminders in Google Sheets for tasks not marked 'Complete.' Automate your workflow with little to no technical expertise, freeing up time for more important work and eliminating manual follow-ups.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow.
Duet AI was renamed to Gemini, our next-generation model.
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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 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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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow.
Duet AI was renamed to Gemini, our next-generation model.
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This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.
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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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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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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.
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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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This short course on integrating applications with Gemini 1.0 Pro models on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 1.0 Pro and Gemini 1.0 Pro Vision models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.
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Complete the intermediate Perform Predictive Data Analysis in BigQuery skill badge course to demonstrate skills in the following: creating datasets in BigQuery by importing CSV and JSON files; harnessing the power of BigQuery with sophisticated SQL analytical concepts, including using BigQuery ML to train an expected goals model on soccer event data and evaluate the impressiveness of World Cup goals.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
Duet AI was renamed to Gemini, our next-generation model.
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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 Analyze Sentiment with Natural Language API quest, where you learn how the API derives sentiment from text.
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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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The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.
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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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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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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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In this course you will learn how you to harness serious Google Cloud power and infrastructure. The hands-on labs will give you use cases and you will be tasked with implementing scaling practices utilized by Google’s very own Solutions Architecture team. From developing enterprise grade load balancing and autoscaling, to building continuous delivery pipelines, Google Cloud Solutions I: Scaling your Infrastructure will teach you best practices for taking your Google Cloud projects to the next level.
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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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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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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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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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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.
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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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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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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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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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This course, Google Cloud Big Data and Machine Learning Fundamentals - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Big Data and Machine Learning Fundamentals.
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on 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 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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In this course you will learn how to use several BigQuery ML features to improve retail use cases. Predict the demand for bike rentals in NYC with demand forecasting, and see how to use BigQuery ML for a classification task that predicts the likelihood of a website visitor making a purchase.
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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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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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Earn a skill badge by completing the Share Data Using Google Data Cloud skill badge course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards.
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Complete the intermediate Manage Data Models in Looker skill badge course to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies.
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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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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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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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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 introductory Build LookML Objects in Looker skill badge course to demonstrate skills in the following: building new dimensions and measures, views, and derived tables; setting measure filters and types based on requirements; updating dimensions and measures; building and refining Explores; joining views to existing Explores; and deciding which LookML objects to create based on business requirements.
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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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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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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating git repositories with Cloud Source 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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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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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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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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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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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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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.
Build Generative AI Agents with Vertex AI and Flutter
Earned mar 31, 2026 EDT
Build AI Agents with Enterprise Databases
Earned mar 30, 2026 EDT
Enhance Gemini Model Capabilities
Earned mar 29, 2026 EDT
Prompt Design in Vertex AI
Earned mar 29, 2026 EDT
Kickstarting Application Development with Gemini Code Assist
Earned mar 28, 2026 EDT
Monitoring in Google Cloud
Earned mar 27, 2026 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned mar 26, 2026 EDT
Use APIs to Work with Cloud Storage
Earned mar 25, 2026 EDT
Develop Serverless Applications on Cloud Run
Earned mar 24, 2026 EDT
AI Boost Bites: Automate tasks with Gemini and Apps Script
Earned mar 23, 2026 EDT
Gemini for DevOps Engineers
Earned mar 22, 2026 EDT
Build Serverless Applications with Cloud Run Functions
Earned mar 21, 2026 EDT
The Basics of Google Cloud Compute
Earned mar 20, 2026 EDT
Gemini for Cloud Architects
Earned mar 20, 2026 EDT
Gemini for Application Developers
Earned mar 19, 2026 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned maj 31, 2024 EDT
Manage Kubernetes in Google Cloud
Earned maj 31, 2024 EDT
Intro to ML: Image Processing
Earned maj 29, 2024 EDT
Intro to ML: Language Processing
Earned maj 29, 2024 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned maj 28, 2024 EDT
Create and Manage Cloud SQL for PostgreSQL Instances
Earned maj 24, 2024 EDT
Podstawy: infrastruktura
Earned maj 22, 2024 EDT
Integrating Applications with Gemini 1.0 Pro on Google Cloud
Earned maj 22, 2024 EDT
Perform Predictive Data Analysis in BigQuery
Earned maj 21, 2024 EDT
Gemini for Data Scientists and Analysts
Earned maj 20, 2024 EDT
Analyze Images with the Cloud Vision API
Earned maj 19, 2024 EDT
Analyze Sentiment with Natural Language API
Earned maj 19, 2024 EDT
Analyze Speech and Language with Google APIs
Earned maj 19, 2024 EDT
Generative AI Explorer - Vertex AI
Earned maj 18, 2024 EDT
Build Infrastructure with Terraform on Google Cloud
Earned cze 29, 2023 EDT
DEPRECATED BigQuery for Marketing Analysts
Earned cze 24, 2023 EDT
DEPRECATED Google Cloud Solutions II: Data and Machine Learning
Earned cze 24, 2023 EDT
Google Cloud Solutions I: Scaling Your Infrastructure
Earned cze 23, 2023 EDT
Implement Cloud Security Fundamentals on Google Cloud
Earned cze 18, 2023 EDT
NCAA® March Madness®: Bracketology with Google Cloud
Earned cze 16, 2023 EDT
Budowanie bezpiecznej sieci Google Cloud
Earned cze 15, 2023 EDT
Deploy Kubernetes Applications on Google Cloud
Earned cze 14, 2023 EDT
Konfigurowanie środowiska programistycznego w Google Cloud
Earned cze 12, 2023 EDT
Budowanie sieci w Google Cloud
Earned cze 10, 2023 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network
Earned cze 10, 2023 EDT
Inżynieria chmury
Earned cze 8, 2023 EDT
Develop Serverless Apps with Firebase
Earned cze 6, 2023 EDT
Wdrażanie równoważenia obciążenia Cloud Load Balancing w Compute Engine
Earned cze 6, 2023 EDT
Automate Data Capture at Scale with Document AI
Earned paź 22, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals - Locales
Earned paź 22, 2022 EDT
Uzyskiwanie statystyk z danych BigQuery
Earned paź 21, 2022 EDT
Prepare Data for Looker Dashboards and Reports
Earned paź 20, 2022 EDT
DEPRECATED Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications
Earned paź 17, 2022 EDT
BigQuery for Machine Learning
Earned paź 15, 2022 EDT
Podstawy: dane, uczenie maszynowe, AI
Earned paź 15, 2022 EDT
Share Data Using Google Data Cloud
Earned paź 15, 2022 EDT
Manage Data Models in Looker
Earned paź 14, 2022 EDT
DEPRECATED BigQuery for Data Warehousing
Earned paź 13, 2022 EDT
DEPRECATED BigQuery Basics for Data Analysts
Earned paź 13, 2022 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned paź 13, 2022 EDT
Create ML Models with BigQuery ML
Earned paź 12, 2022 EDT
Build LookML Objects in Looker
Earned paź 12, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned kwi 16, 2022 EDT
Data Catalog Fundamentals
Earned kwi 15, 2022 EDT
Implement DevOps Workflows in Google Cloud
Earned kwi 14, 2022 EDT
DevOps Essentials
Earned kwi 14, 2022 EDT
[DEPRECATED] Deploying Applications
Earned kwi 14, 2022 EDT
Build Apps & Websites with Firebase
Earned kwi 13, 2022 EDT
Tworzenie witryny w Google Cloud
Earned kwi 13, 2022 EDT
Google Cloud Essentials
Earned kwi 12, 2022 EDT
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud
Earned kwi 12, 2022 EDT