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Magda Krupka

Учасник із 2021

Золота ліга

Кількість балів: 16170
Scaling with Google Cloud Operations Earned груд. 11, 2023 EST
Modernize Infrastructure and Applications with Google Cloud Earned груд. 11, 2023 EST
Introduction to Generative AI - Українська Earned груд. 8, 2023 EST
Exploring Data Transformation with Google Cloud Earned груд. 8, 2023 EST
Digital Transformation with Google Cloud Earned груд. 7, 2023 EST
Build a Website on Google Cloud Earned черв. 22, 2021 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned черв. 22, 2021 EDT
Prepare Data for Looker Dashboards and Reports Earned черв. 22, 2021 EDT
Website on Google Cloud Earned черв. 21, 2021 EDT
Cloud Architecture: Design, Implement, and Manage Earned трав. 23, 2021 EDT
Monitor and Log with Google Cloud Observability Earned трав. 16, 2021 EDT
DEPRECATED Google Cloud's Operations Suite Earned трав. 16, 2021 EDT
Implement DevOps Workflows in Google Cloud Earned трав. 15, 2021 EDT
DEPRECATED Explore Machine Learning Models with Explainable AI Earned трав. 14, 2021 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned трав. 12, 2021 EDT
Deploy Kubernetes Applications on Google Cloud Earned трав. 12, 2021 EDT
Build a Data Warehouse with BigQuery Earned трав. 12, 2021 EDT
Create ML Models with BigQuery ML Earned трав. 11, 2021 EDT
DevOps Essentials Earned трав. 10, 2021 EDT
Kubernetes in Google Cloud Earned трав. 10, 2021 EDT
BigQuery for Machine Learning Earned трав. 8, 2021 EDT
DEPRECATED BigQuery for Data Warehousing Earned трав. 8, 2021 EDT
[DEPRECATED] Data Engineering Earned трав. 8, 2021 EDT
Scientific Data Processing Earned трав. 8, 2021 EDT
DEPRECATED Applied Data: Blockchain Earned трав. 4, 2021 EDT
Derive Insights from BigQuery Data Earned квіт. 25, 2021 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned квіт. 25, 2021 EDT
Data Science on Google Cloud Earned квіт. 25, 2021 EDT
Розробка хмарних технологій Earned квіт. 20, 2021 EDT
Налаштування мережі Google Cloud Earned квіт. 20, 2021 EDT
DEPRECATED Cloud Architecture Earned квіт. 19, 2021 EDT
Set Up a Google Cloud Network Earned квіт. 19, 2021 EDT
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud Earned квіт. 18, 2021 EDT
Початок роботи з даними, машинним навчанням і штучним інтелектом Earned квіт. 17, 2021 EDT
Налаштування середовища для розробки додатка в Google Cloud Earned квіт. 16, 2021 EDT
Початок роботи з інфраструктурою Earned квіт. 16, 2021 EDT
Налаштування Cloud Load Balancing для Compute Engine Earned квіт. 7, 2021 EDT
Основи Google Cloud Earned бер. 29, 2021 EDT

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

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

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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке генеративний штучний інтелект, як він використовується й чим відрізняється від традиційних методів машинного навчання. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучногоінтелекту.

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

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

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Earn the introductory skill badge by completing the Build a Website on Google Cloud skill badge course. This course is based on the Get Cooking in Cloud series and covers`:`Deploying a website on Cloud RunHosting a web app on Compute EngineCreating, deploying, and scaling your website on Google Kubernetes EngineMigrating from a monolithic application to a microservices architecture using Cloud Build

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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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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 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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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 introductory Monitor and Log with Google Cloud Observability skill badge course 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.

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

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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. 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 quest 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 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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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.

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Complete the intermediate 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 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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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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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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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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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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Big data, machine learning, and scientific data? It sounds like the perfect match. In this course, you will get hands-on practice with GCP services like BigQuery, Managed Service for Apache Spark, 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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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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Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Data Studio by connecting to BigQuery data.

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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 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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Цей вступний курс унікальний серед інших курсів. Практичні заняття розроблено так, щоб ІТ-фахівці могли опрацювати теми й сервіси, які ввійдуть до сертифікації Google Cloud Certified Associate Cloud Engineer. У цей курс входять спеціально розроблені практичні заняття, зокрема присвячені керуванню ідентифікацією і доступом, організації мереж і розгортанню Kubernetes Engine, щоб ви могли перевірити свої знання про Google Cloud. Майте на увазі, що хоча виконання цих практичних занять покращить ваші навички й уміння, радимо також переглянути посібник із підготовки до іспиту й інші доступні ресурси.

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Щоб отримати кваліфікаційний значок, пройдіть курс Налаштування мережі Google Cloud. У ньому ви дізнаєтеся про різні способи розгортання й моніторингу додатків, зокрема навчитеся визначати ролі керування ідентифікацією і доступом, надавати або вилучати доступ до проектів, створювати мережі VPC, розгортати й відстежувати віртуальні машини Compute Engine, писати запити SQL, а також по-різному вводити додатки в дію за допомогою Kubernetes.

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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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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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Пройдіть вступний кваліфікаційний курс Підготовка даних для інтерфейсів API машинного навчання в Google Cloud, щоб продемонструвати свої навички щодо очистки даних за допомогою сервісу Dataprep by Trifacta, запуску конвеєрів даних у Dataflow, створення кластерів і запуску завдань Apache Spark у Managed Service for Apache Spark, а також виклику API машинного навчання, зокрема Cloud Natural Language API, Google Cloud Speech-to-Text API і Video Intelligence API.

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Зараз усі говорять про масиви даних, машинне навчання й штучний інтелект, але це досить вузькоспеціалізовані теми, про які важко знайти матеріали, зрозумілі не лише спеціалістам. На щастя, Google Cloud пропонує зручні сервіси в цих галузях, а завдяки цьому вступному курсу ви зможете ознайомитися з такими інструментами, як BigQuery, Cloud Speech API і Video Intelligence.

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Щоб отримати кваліфікаційний значок, пройдіть курс Налаштування середовища для розробки додатка в Google Cloud. У ньому ви навчитеся створювати й підключати хмарну інфраструктуру, спрямовану на зберігання даних, за допомогою базових можливостей таких технологій, як Cloud Storage, система керування ідентифікацією і доступом, Cloud Functions та Pub/Sub.

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Якщо ви лише пробуєте розробляти хмарні рішення й шукаєте практичні заняття на додаток до кваліфікаційного курсу "Знайомство з Google Cloud", тоді цей курс саме для вас. Ви отримаєте прикладний досвід завдяки практичним заняттям, присвяченим Cloud Storage і іншим ключовим сервісам додатків, як-от Monitoring і Cloud Functions. Ви отримаєте цінні навички, які можна застосовувати в будь-яких проєктах Google Cloud.

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Пройдіть вступний кваліфікаційний курс Налаштування Cloud Load Balancing для Compute Engine, щоб продемонструвати свої навички: створення й розгортання віртуальних машин у Compute Engine; налаштування мережі й розподілювачів навантаження додатків.

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На цьому вступному курсі ви отримаєте практичний досвід роботи з основними інструментами й сервісами Google Cloud. Також вам доступні додаткові відео, які допоможуть краще зрозуміти контекст і закріпити знання щодо тем, розглянутих у практичних заняттях. Google Cloud "Основи" – це рекомендований початковий курс для тих, хто починає вивчати Google Cloud. Ви можете розпочати навчання, маючи мінімальні знання про хмарні технології або взагалі не маючи їх, і отримати практичний досвід, який зможете застосувати у своєму першому хмарному проєкті Google Cloud. "Основи Google Cloud" дають вичерпне уявленні про ключові функції платформи – від написання команд у Cloud Shell і розгортання першої віртуальної машини до запуску додатків на Kubernetes Engine і використання розподілу навантаження.

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