Святослав Павлов
Учасник із 2023
Діамантова ліга
Кількість балів: 59130
Essential Google Cloud Infrastructure: Core Services
Earned бер. 31, 2024 EDT
Essential Google Cloud Infrastructure: Foundation
Earned бер. 30, 2024 EDT
Build a Certification Study Guide: ACE Exam Prep
Earned бер. 27, 2024 EDT
Build Google Cloud Infrastructure for AWS Professionals
Earned бер. 26, 2024 EDT
Deploy and Monitor in Google Cloud for AWS Professionals
Earned бер. 25, 2024 EDT
Google Cloud Storage and Containers for AWS Professionals
Earned бер. 24, 2024 EDT
Google Cloud Compute and Scalability for AWS Professionals
Earned бер. 23, 2024 EDT
Google Cloud IAM and Networking for AWS Professionals
Earned бер. 20, 2024 EDT
DEPRECATED Cloud Operations and Service Mesh with Anthos
Earned бер. 16, 2024 EDT
Logging and Monitoring in Google Cloud
Earned бер. 13, 2024 EDT
Monitor and Log with Google Cloud Observability
Earned бер. 10, 2024 EDT
Build Infrastructure with Terraform on Google Cloud
Earned бер. 8, 2024 EST
Using DevSecOps in your Google Cloud Environment
Earned бер. 7, 2024 EST
Google Cloud Architecture: Design Principles
Earned бер. 7, 2024 EST
Getting Started with Terraform for Google Cloud
Earned бер. 5, 2024 EST
Implement DevOps Workflows in Google Cloud
Earned бер. 4, 2024 EST
App Building with AppSheet
Earned бер. 3, 2024 EST
Implement Cloud Storage and Data Protection Solutions
Earned бер. 3, 2024 EST
Implement Event-Driven Messaging and Automation Workflows
Earned бер. 3, 2024 EST
Build Serverless Applications with Cloud Run Functions
Earned бер. 2, 2024 EST
Store, Process, and Manage Data on Google Cloud - Command Line
Earned лют. 26, 2024 EST
Store, Process, and Manage Data on Google Cloud - Console
Earned лют. 25, 2024 EST
Deploy and Manage Applications on Google App Engine
Earned лют. 25, 2024 EST
Developing a Google SRE Culture
Earned лют. 25, 2024 EST
Google Cloud Fundamentals: Core Infrastructure - Yкраїнська
Earned лют. 25, 2024 EST
Build LookML Objects in Looker
Earned лют. 24, 2024 EST
Automate Data Capture at Scale with Document AI
Earned лют. 21, 2024 EST
Implement Speech and Language Solutions with Pre-trained APIs
Earned лют. 18, 2024 EST
Analyze Sentiment with Natural Language API
Earned лют. 18, 2024 EST
Analyze Speech and Language with Google APIs
Earned лют. 18, 2024 EST
Prepare Data for Looker Dashboards and Reports
Earned лют. 17, 2024 EST
Migrate MySQL Data to Cloud SQL Using Database Migration Service
Earned жовт. 15, 2023 EDT
Use Machine Learning APIs on Google Cloud
Earned жовт. 9, 2023 EDT
Deploy Kubernetes Applications on Google Cloud
Earned жовт. 8, 2023 EDT
Implement Cloud Collaboration and Productivity Workflows
Earned жовт. 8, 2023 EDT
[Deprecated] Get Started with Looker
Earned жовт. 7, 2023 EDT
Create and Manage Bigtable Instances
Earned жовт. 7, 2023 EDT
Create and Manage Cloud Spanner Instances
Earned жовт. 5, 2023 EDT
Share Data Using Google Data Cloud
Earned жовт. 4, 2023 EDT
Perform Predictive Data Analysis in BigQuery
Earned жовт. 3, 2023 EDT
DEPRECATED Detect Manufacturing Defects Using Visual Inspection AI
Earned жовт. 1, 2023 EDT
Build a Data Warehouse with BigQuery
Earned вер. 30, 2023 EDT
Create ML Models with BigQuery ML
Earned вер. 28, 2023 EDT
Derive Insights from BigQuery Data
Earned вер. 27, 2023 EDT
Create and Manage Cloud SQL for PostgreSQL Instances
Earned вер. 24, 2023 EDT
Налаштування середовища для розробки додатка в Google Cloud
Earned вер. 20, 2023 EDT
Generative AI Fundamentals - Українська
Earned вер. 19, 2023 EDT
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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Learn how to use Gemini Notebook to create a personalized study guide for the Associate Cloud Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook , and learn how to use a study guide to practice for a certification exam.
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Earn a skill badge by completing the Build Google Cloud Infrastructure for AWS Professionals course, where you learn how to configure IAM permission, orchestrate workloads using Kubernetes, host a web application using compute engine, and configure load balancing.
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This is the fourth course of a four-course series for cloud architects and engineers with existing AWS knowledge. It compares Google Cloud and AWS solutions and guides professionals on their use.
This course focuses on deploying and monitoring applications in Google Cloud. The learners apply the knowledge of monitoring and application deployment processes in AWS to explore the differences with Google Cloud. Learners get hands-on practice building and managing Google Cloud resources.
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This is the third course of a four-course series for cloud architects and engineers with existing AWS knowledge, and it compares Google Cloud and AWS solutions and guides professionals on their use.
This course focuses on Storage Options and containers in Google Cloud. The learners apply the knowledge of storage and containers in AWS to explore the similarities and differences with storage and containers in Google Cloud. Learners get hands-on practice building and managing Google Cloud resources.
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This is the second course of a four-course series for cloud architects and engineers with existing AWS knowledge. It aims to compare Google Cloud and AWS solutions and guide professionals on their use.
This course focuses on compute resources and load balancing in Google Cloud. The learner will apply the knowledge of using virtual machines and load balancers in AWS to explore the similarities and differences with configuring and managing compute resources and load balancers in Google Cloud. Learners will get hands-on practice building and managing Google Cloud resources.
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This is the first course of a four-course series for cloud architects and engineers with existing AWS knowledge, and it compares Google Cloud and AWS solutions and guides professionals on their use.
This course focuses on Identity and Access Management (IAM) and networking in Google Cloud. The learners apply the knowledge of access management and networking in AWS to explore the similarities and differences with access management and networking in Google Cloud. Learners get hands-on practice building and managing Google Cloud resources.
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Course two of the Architecting Hybrid Cloud with Anthos series prepares students to operate and observe Anthos environments. Through presentations and hands-on labs, participants explore adjusting existing clusters, setting up advanced traffic routing policies, securing communication across workloads, and observing clusters in Anthos. This course is a continuation of course one, Multi-Cluster, Multi-Cloud with Anthos, and assumes direct experience with the topics covered in that course.
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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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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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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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In this course, you will learn the basic skills to implement secure and efficient DevSecOps practices on Google Cloud. You'll learn how to secure your development pipeline with Google Cloud services like Artifact Registry, Cloud Build, Cloud Deploy, and Binary Authorization. This enables you to build, test, and deploy containerized applications with security controls throughout the CI/CD pipeline.
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In this course, you’ll learn how to apply the Google Cloud Well-Architected Framework to design resilient, production-grade cloud environments. You’ll analyze real-world challenges across six distinct industries to balance competing priorities like low-latency performance, ironclad security, and carbon efficiency. By the end, you'll possess a practical architectural playbook and the critical thinking skills needed to lead reviews and optimize cloud workloads in the field.
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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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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 App Building with AppSheet course, where you learn how to build, configure, and publish apps using AppSheet.
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Earn a Skill Badge by completing the Implement Cloud Storage and Data Protection Solutions course. Learn to create a Cloud Storage bucket, use the command line, and protect objects with Bucket Lock.
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Earn a skill badge by completing the Implement Event-Driven Messaging and Automation Workflows skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.
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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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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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Cloud Storage, Cloud Functions, and Cloud Pub/Sub are all Google Cloud Platform services that can be used to store, process, and manage data. All three services can be used together to create a variety of data-driven applications. In this skill badge you use Cloud Storage to store images, Cloud Functions to process the images, and Cloud Pub/Sub to send the images to another application.
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Earn a Skill Badge by completing the Deploy and Manage Applications on Google App Engine course, where you learn how to use App Engine with Python, Go, and PHP.
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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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Курс "Знайомство з Google Cloud: основна інфраструктура" охоплює важливі поняття й терміни щодо використання Google Cloud. Переглядаючи відео й виконуючи практичні завдання, слухачі ознайомляться з різними сервісами Google Cloud для обчислень і зберігання даних, а також важливими ресурсами й інструментами для керування правилами. Крім того, вони зможуть їх порівнювати.
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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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Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
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Earn the Introductory Skill Badge by completing the Implement Speech and Language Solutions with Pre-trained APIs course, where you learn how to use speech related API tools to synthesise and transcribe speech.
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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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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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Complete the introductory Migrate MySQL Data to Cloud SQL Using Database Migration Service skill badge course to demonstrate skills in the following: migrating MySQL data to Cloud SQL using different job types and connectivity options available in Database Migration Service and migrating MySQL user data when running Database Migration Service jobs.
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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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Earn an introductory skill badge by completing the Implement Cloud Collaboration and Productivity Workflows course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.
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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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Complete the introductory Create and Manage Bigtable Instances skill badge to demonstrate skills in the following: creating instances, designing schemas, querying data, and performing administrative tasks in Bigtable including monitoring performance and configuring node autoscaling and replication.
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Complete the introductory Create and Manage Cloud Spanner Instances skill badge to demonstrate skills in the following: creating and interacting with Cloud Spanner instances and databases; loading Cloud Spanner databases using various techniques; backing up Cloud Spanner databases; defining schemas and understanding query plans; and deploying a Modern Web App connected to a Cloud Spanner instance.
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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 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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Earn a skill badge by completing the Detect Manufacturing Defects using Visual Inspection AI course, where you learn how to use Visual Inspection AI to deploy a solution artifact and test that it can successfully identify defects in a manufacturing process.
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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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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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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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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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Щоб отримати кваліфікаційний значок, пройдіть курси "Introduction to Generative AI", "Introduction to Large Language Models" й "Introduction to Responsible AI". Пройшовши завершальний тест, ви підтвердите, що засвоїли основні поняття, які стосуються генеративного штучного інтелекту.
Кваліфікаційний значок – це цифровий значок від платформи Google Cloud, який свідчить, що ви знаєтеся на продуктах і сервісах Google Cloud. Щоб опублікувати кваліфікаційний значок, зробіть свій профіль загальнодоступним, а також додайте значок у профіль у соціальних мережах.
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