Spilios Theodoratos
Member since 2021
Silver League
4360 points
Build Infrastructure with Terraform on Google Cloud
Earned Kas 11, 2022 EST
Google Cloud Architecture: Design Principles
Earned Kas 11, 2022 EST
Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma
Earned Kas 9, 2022 EST
Compute Engine İçin Cloud Load Balancing'i Uygulama
Earned Kas 9, 2022 EST
Google Cloud'un Temel Özellikleri
Earned Kas 8, 2022 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned Nis 17, 2022 EDT
Elastic Google Cloud Infrastructure: Scaling and Automation
Earned Ara 27, 2021 EST
DEPRECATED Cloud Architecture
Earned Kas 3, 2021 EDT
Big Data on AWS
Earned Nis 10, 2021 EDT
Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama
Earned Mar 14, 2021 EDT
Cloud Architecture: Design, Implement, and Manage
Earned Mar 10, 2021 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned Mar 4, 2021 EST
BigQuery Verilerinden Analiz Elde Etme
Earned Şub 20, 2021 EST
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’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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Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma kursunu tamamlayarak beceri rozeti kazanın. Bu kursta Cloud Storage, Identity and Access Management, Cloud Functions ve Pub/Sub gibi teknolojilerin temel özelliklerini kullanarak depolama odaklı bulut altyapısı oluşturma ve bu altyapıyla bağlantı kurmayı öğreneceksiniz.
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Giriş düzeyindeki Compute Engine İçin Cloud Load Balancing'i Uygulama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Compute Engine'de sanal makineler oluşturma ve dağıtma. Ağ ve uygulama yük dengeleyicileri yapılandırma.
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Bu giriş düzeyindeki kursta, Google Cloud'un temel araçları ve hizmetleri hakkında uygulamalı alıştırmalar yapacaksınız. Laboratuvarlarda işlenen kavramlara ilişkin daha fazla bağlam bilgisi ve inceleme sunmak amacıyla isteğe bağlı videolar paylaşılmaktadır. Google Cloud'un Temel Özellikleri, Google Cloud'u kullanmayı öğrenenler için önerilen ilk kurslardandır. Bulut teknolojisi konusunda çok az bilginiz olsa ya da hiç bilginiz olmasa bile bu kursa katılabilir ve ilk Google Cloud projenizde uygulayabileceğiniz pratik deneyimler kazanabilirsiniz. Cloud Shell komutları yazmak ve ilk sanal makinenizi dağıtmaktan Kubernetes Engine üzerinde veya yük dengelemeyi kullanarak uygulama çalıştırmaya kadar birçok konuyu kapsayan Google Cloud'un Temel Özellikleri, platformun temel özelliklerine dair mükemmel bir giriş niteliğindedir.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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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 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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Scientists, developers, and other technologists from many different industries are taking advantage of AWS to perform big data analytics and meet the challenges of the increasing volume, variety, and velocity of digital information. AWS offers a portfolio of cloud computing services to help you manage big data by reducing costs, scaling to meet demand, and increasing the speed of innovation. In this quest, you’ll learn to work with advanced services for Big Data.
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Giriş düzeyindeki Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Dataprep by Trifacta ile veri temizleme, Dataflow'da veri ardışık düzenleri çalıştırma, Managed Service for Apache Spark'ta küme oluşturma ve Apache Spark işleri çalıştırma ve makine öğrenimi API'lerini (Cloud Natural Language API, Google Cloud Speech-to-Text API ve Video Intelligence API dahil olmak üzere) çağırma.
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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 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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Giriş düzeyindeki BigQuery Verilerinden Analiz Elde Etme beceri rozetini alarak şu konulardaki becerilerinizi gösterin: SQL sorguları yazma, herkese açık tabloları sorgulama, örnek verileri BigQuery'ye yükleme, BigQuery'deki sorgu doğrulayıcı ile yaygın söz dizimi sorunlarını giderme ve BigQuery verilerine bağlanarak Data Studio'da rapor oluşturma.
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