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Manoj Patil

Member since 2020

Build Your First Agent with Agent Development Kit (ADK) Earned Eyl 1, 2026 EDT
Liftoff with Google Antigravity: Build a Video Game with AI Earned Eyl 1, 2026 EDT
Deploy Multi-Agent Systems with Gemini Enterprise Agent Platform Earned Kas 5, 2025 EST
Gemini for Application Developers Earned Eki 10, 2025 EDT
Üretken Yapay Zeka: Chatbot'tan Daha Fazlası Earned Eyl 30, 2025 EDT
Sorumlu Yapay Zeka: Google Cloud ile Yapay Zeka İlkelerini Uygulama Earned Eyl 30, 2025 EDT
Çoklu Format Destekli Gemini ve Çok Formatlı RAG ile Zengin Belgeleri İnceleme Earned Eyl 30, 2025 EDT
Develop Gen AI Apps with Gemini and Streamlit Earned Eyl 30, 2025 EDT
Explore Generative AI in Agent Platform Earned Eyl 26, 2025 EDT
Agent Platform'da İstem Tasarımı Earned Eyl 22, 2025 EDT
Create Generative AI Apps on Google Cloud Earned Eyl 4, 2025 EDT
Natural Language Processing on Google Cloud Earned Eyl 4, 2025 EDT
[DEPRECATED] Google Cloud: Prompt Engineering Guide Earned Eyl 3, 2025 EDT
Gemini for end-to-end SDLC Earned Ağu 25, 2025 EDT
Generative AI Explorer - Agent Platform Earned May 7, 2024 EDT
Trust and Security with Google Cloud Earned May 7, 2024 EDT
Innovating with Google Cloud Artificial Intelligence Earned May 7, 2024 EDT
DEPRECATED Build and Deploy Machine Learning Solutions on Vertex AI Earned May 5, 2024 EDT
Production Machine Learning Systems Earned May 5, 2024 EDT
Machine Learning in the Enterprise Earned May 4, 2024 EDT
[Depricated] Build, Train and Deploy ML Models with Keras on Google Cloud Earned May 4, 2024 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned May 4, 2024 EDT
[Deprecated] Classify Images with TensorFlow on Google Cloud Earned May 4, 2024 EDT
[Deprecated] Classify Images with TensorFlow on Google Cloud Earned May 3, 2024 EDT
Machine Learning Operations (MLOps): Getting Started Earned May 2, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud Earned Mar 4, 2024 EST
Dönüştürücü Modelleri ve BERT Modeli Earned Ağu 2, 2023 EDT
Dikkat Mekanizması Earned Ağu 2, 2023 EDT
Görüntülere Altyazı Ekleme Modelleri Oluşturma Earned Ağu 2, 2023 EDT
Automate Interactions with Contact Center AI Earned Tem 11, 2023 EDT
Vertex AI Earned Tem 11, 2023 EDT
Cloud Hero DocAI Earned Tem 6, 2023 EDT
Kodlayıcı-Kod Çözücü Mimarisi Earned Tem 4, 2023 EDT
Vertex AI Studio'ya Giriş Earned Haz 29, 2023 EDT
BigQuery for Data Analysis II Earned Haz 26, 2023 EDT
Görüntü Üretmeye Giriş Earned Haz 23, 2023 EDT
Generative AI Fundamentals Earned Haz 22, 2023 EDT
[DEPRECATED] Sorumlu Yapay Zekaya Giriş Earned Haz 21, 2023 EDT
Büyük Dil Modellerine Giriş Earned Haz 20, 2023 EDT
Üretken Yapay Zekaya Giriş Earned Haz 15, 2023 EDT
Essential Google Cloud Infrastructure: Foundation Earned Eki 20, 2022 EDT
Build a Certification Study Guide: ACE Exam Prep Earned Eki 18, 2022 EDT
Intro to BigQuery: Analytics & Machine Learning Earned Eki 6, 2022 EDT
Cloud Hero Network Skills Earned Eyl 27, 2022 EDT
Modernize Infrastructure and Applications with Google Cloud Earned Eyl 25, 2022 EDT
Exploring Data Transformation with Google Cloud Earned Eyl 25, 2022 EDT
Cloud Hero IAM & Security Skills Earned Eyl 20, 2022 EDT
Scaling with Google Cloud Operations Earned Eyl 19, 2022 EDT
Digital Transformation with Google Cloud Earned Eyl 19, 2022 EDT
Serverless Data Processing with Dataflow: Foundations Earned Eyl 11, 2022 EDT
Terraform by HashiCorp Game Earned Eyl 6, 2022 EDT
Build a Certification Study Guide: PDE Exam Prep Earned Ağu 24, 2022 EDT
API Design and Fundamentals with the Apigee API Platform Earned Ağu 12, 2022 EDT
Google Cloud Fundamentals: Core Infrastructure Earned Ağu 7, 2022 EDT
Create ML Models with BigQuery ML Earned Ağu 1, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned Tem 28, 2022 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud Earned Tem 23, 2022 EDT
Google Cloud Architecture: Design Principles Earned Tem 15, 2022 EDT
Developing a Google SRE Culture Earned Tem 11, 2022 EDT
Build a Data Warehouse with BigQuery Earned Tem 10, 2022 EDT
BigQuery for Machine Learning Earned Tem 10, 2022 EDT
DEPRECATED BigQuery for Data Warehousing Earned Tem 7, 2022 EDT
Build Streaming Data Pipelines on Google Cloud Earned Tem 4, 2022 EDT
Build Batch Data Pipelines on Google Cloud Earned Tem 2, 2022 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned Haz 25, 2022 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals Earned Haz 24, 2022 EDT
[DEPRECATED] Deploying Applications Earned May 14, 2022 EDT
[DEPRECATED] Data Engineering Earned Nis 29, 2022 EDT
Flutter Essentials Earned Şub 10, 2022 EST
BigQuery Verilerinden Analiz Elde Etme Earned Eyl 10, 2021 EDT
DEPRECATED BigQuery Basics for Data Analysts Earned Eyl 9, 2021 EDT
Cloud Hero: Scalable ML Earned Eyl 9, 2021 EDT
Manage and Observe with Anthos Service Mesh Earned Tem 5, 2021 EDT
Optimize Costs for Google Kubernetes Engine Earned Tem 1, 2021 EDT
Getting Started with Apache Kafka and Confluent Platform on Google Cloud Earned Haz 25, 2021 EDT
VM Migration Earned Haz 22, 2021 EDT
Cloud Architecture: Design, Implement, and Manage Earned Haz 20, 2021 EDT
Advanced Cloud Architecture v(1) Earned Haz 20, 2021 EDT
Cloud Architecture - Design, Implement, and Manage Earned Haz 20, 2021 EDT
DEPRECATED Google Cloud's Operations Suite on GKE Earned Haz 20, 2021 EDT
Google Kubernetes Engine Best Practices Earned Haz 19, 2021 EDT
Google Developer Essentials Earned Haz 18, 2021 EDT
Google Cloud Solutions I: Scaling Your Infrastructure Earned Haz 11, 2021 EDT
Deprecated Kubernetes Solutions Earned Haz 10, 2021 EDT
[Deprecated] Cloud Logging Earned Haz 7, 2021 EDT
Monitor and Log with Google Cloud Observability Earned Haz 5, 2021 EDT
DEPRECATED Google Cloud's Operations Suite Earned Haz 5, 2021 EDT
[DEPRECATED] Build Interactive Apps with Google Assistant Earned May 28, 2021 EDT
[DEPRECATED] OK Google: Build Interactive Apps with Google Assistant Earned May 28, 2021 EDT
Use Machine Learning APIs on Google Cloud Earned May 27, 2021 EDT
Machine Learning APIs Earned May 26, 2021 EDT
DEPRECATED Anthos Service Mesh Earned May 23, 2021 EDT
Anthos: Service Mesh Earned May 23, 2021 EDT
Anthos Earned May 20, 2021 EDT
DEPRECATED Exploring APIs Earned May 17, 2021 EDT
Implement Cloud Security Fundamentals on Google Cloud Earned May 16, 2021 EDT
Using the Cloud SDK Command Line Earned May 16, 2021 EDT
Develop Serverless Applications on Cloud Run Earned May 9, 2021 EDT
Google Cloud Run Serverless Workshop Earned May 9, 2021 EDT
Build Infrastructure with Terraform on Google Cloud Earned May 3, 2021 EDT
[DEPRECATED] Secure Workloads in Google Kubernetes Engine Earned Nis 8, 2021 EDT
Google Kubernetes Engine Best Practices: Security Earned Nis 8, 2021 EDT
Develop Serverless Apps with Firebase Earned Nis 3, 2021 EDT
Build Apps & Websites with Firebase Earned Nis 3, 2021 EDT
Kubernetes in Google Cloud Earned Mar 31, 2021 EDT
Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama Earned Mar 30, 2021 EDT
Managing Cloud Infrastructure with Terraform Earned Mar 18, 2021 EDT
Google Cloud'da web sitesi Earned Ara 28, 2020 EST
Google Cloud'da Web Sitesi Derleme Earned Ara 28, 2020 EST
Temel: Veri, Makine Öğrenimi, Yapay Zeka Earned Ara 25, 2020 EST
DevJam App Dev Challenge Earned Ara 21, 2020 EST
Security & Identity Fundamentals Earned Ara 19, 2020 EST
Set Up a Google Cloud Network Earned Ara 12, 2020 EST
Implement DevOps Workflows in Google Cloud Earned Ara 12, 2020 EST
DevJam Infrastructure Challenge Earned Ara 12, 2020 EST
Bulut Mühendisliği Earned Ara 11, 2020 EST
Intro to ML: Image Processing Earned Ara 11, 2020 EST
Intro to ML: Language Processing Earned Ara 8, 2020 EST
Automate Deployment and Manage Traffic on a Google Cloud Network Earned Ara 6, 2020 EST
Cloud Development Earned Ara 2, 2020 EST
DEPRECATED Application Development - Java Earned Ara 2, 2020 EST
DevOps Essentials Earned Kas 30, 2020 EST
DEPRECATED Cloud Architecture Earned Kas 30, 2020 EST
Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma Earned Kas 28, 2020 EST
Temel: Altyapı Earned Kas 28, 2020 EST
Deploy Kubernetes Applications on Google Cloud Earned Kas 27, 2020 EST
Güvenli Bir Google Cloud Ağı Oluşturma Earned Kas 25, 2020 EST
Google Cloud Ağınızı Geliştirme Earned Kas 21, 2020 EST
Compute Engine İçin Cloud Load Balancing'i Uygulama Earned Kas 15, 2020 EST
Google Cloud Essentials Earned Kas 15, 2020 EST

Turn your understanding of agents into practical reality by building, configuring, and running your first AI agent using Google’s Agent Development Kit (ADK). In this hands-on course, you’ll set up a complete ADK development environment, create agents with both Python code and YAML configuration, and run them through multiple interfaces. You’ll also learn the core parameters that define agent behavior, taking what you learned in course 1 and applying it to working code. Explore other content in the Gemini Agent Ready (GEAR) program.

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In this course, you'll learn to build software at a propulsive speed by orchestrating agents in Google Antigravity. This hands-on course will first guide you to install and get started with Antigravity by making a Hello, World(s)! app. Next, you'll use Firebase to deploy that app. Finally, you'll build a video game, Voyager, by orchestrating agents in Antigravity to work in parallel. Explore other content in the Gemini Agent Ready (GEAR) program.

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In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Agent Runtime on Gemini Enterprise Agent Platform to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Runtime. Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.

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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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Üretken Yapay Zeka: Chatbot'tan Daha Fazlası, Gen AI Leader öğrenme rotasının ilk kursudur ve ön koşul gerektirmez. Bu kurs, chatbot'larla ilgili temel bilgilerin ötesine geçerek üretken yapay zekanın kuruluşunuza sağlayabileceği gerçek potansiyeli keşfetmeyi amaçlamaktadır. Üretken yapay zekanın gücünden yararlanmak için çok önemli olan temel modeller ve istem mühendisliği gibi kavramları keşfedeceksiniz. Kurs ayrıca kuruluşunuz için başarılı bir üretken yapay zeka stratejisi geliştirirken dikkate almanız gereken önemli noktalar hakkında size rehberlik edecek.

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Kurumsal yapay zeka ve makine öğreniminin kullanımı arttıkça, bu teknolojileri sorumlu bir şekilde geliştirmenin önemi de artıyor. Birçok kişi için sorumlu yapay zeka hakkında konuşmak, bunu uygulamaya geçirmekten daha kolaydır. Kuruluşunuzda sorumlu yapay zekayı nasıl hayata geçireceğinizi öğrenmek istiyorsanız bu kurs tam size göre. Bu kursta, kendi sorumlu yapay zeka yaklaşımınızı geliştirirken size rehberlik edecek bir çerçeve oluşturmak adına Google Cloud'un bu süreci günümüzde nasıl yürüttüğünü, en iyi uygulama örneklerini ve edindiğimiz tecrübeleri keşfedeceksiniz.

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Orta düzeydeki Çoklu Format Destekli Gemini ve Çok Formatlı RAG ile Zengin Belgeleri İnceleme beceri rozetini tamamlayarak şu konulardaki becerilerinizi kanıtlayabilirsiniz: Çok formatlı istemler kullanarak metin ve görsel formatlarındaki verilerden bilgi elde etme, video açıklaması oluşturabilme ve Gemini ile çok formatlılıktan yararlanarak videonun kapsamındaki bilgilerden çok daha fazlasına ulaşabilme; metin ve görüntü içeren dokümanların meta verilerini oluşturma, gerekli tüm metin parçalarına ulaşma ve Gemini'ın Çok Formatlı Almayla Artırılmış Üretim (RAG) mimarisini kullanarak alıntıları yazdırma.

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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. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Complete the intermediate Explore Generative AI in Agent Platform skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Agent Platform'da istem mühendisliği, görüntü analizi ve çok modlu üretken teknikler gibi becerileri göstermek için Agent Platform'da İstem Tasarımı beceri rozetini tamamlayın. Etkili istemlerin nasıl oluşturulacağını, üretken yapay zeka çıktılarına nasıl rehberlik edileceğini ve Gemini modellerinin gerçek dünyadaki pazarlama senaryolarına nasıl uygulanacağını keşfedin.

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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud? In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application. Explore other content in the Gemini Agent Ready (GEAR) program.

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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.

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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you use Google products and services to develop, test, deploy, and manage applications. With help from Gemini, you learn how to develop and build a web application, fix errors in the application, develop tests, and query data. Using a hands-on lab, you experience how Gemini improves the software development lifecycle (SDLC). Duet AI was renamed to Gemini, our next-generation model.

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The Generative AI Explorer - Agent Platform course 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 Gemini models in Agent Platform. 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 custom training in Agent Platform and deploy it to an endpoint in Agent Platform.

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As organizations move their data and applications to the cloud, they must address a rapidly evolving landscape of security challenges. This course explores the foundations of cloud security, the value of Google Cloud’s secure-by-design infrastructure, and the defense-in-depth strategy, while highlighting how AI-driven operations and compliance tools help organizations meet strict global regulatory requirements. 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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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. Innovating with Google Cloud Artificial Intelligence explores how organizations can use AI and ML to transform their business processes. 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 intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.

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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.

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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 intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.

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Earn the intermediate Skill Badge by completing the Classify Images with TensorFlow on Google Cloud skill badge course where you learn how to use TensorFlow and Vertex AI to create and train machine learning models. You primarily interact with Vertex AI Workbench user-managed notebooks.

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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.

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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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Bu kurs, dönüştürücü mimarisini ve dönüştürücülerden çift yönlü kodlayıcı temsilleri (BERT - Encoder Representations from Transformers) modelini tanıtmaktadır. Kursta, öz dikkat mekanizması gibi dönüştürücü mimarisinin ana bileşenlerini ve BERT modelini oluşturmak için dönüştürücünün nasıl kullanıldığını öğreneceksiniz. Ayrıca sınıflandırma, soru yanıtlama ve doğal dil çıkarımı gibi BERT'in kullanılabileceği çeşitli görevler hakkında da bilgi sahibi olacaksınız. Kursun tahmini süresi 45 dakikadır.

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Bu kursta nöral ağların, giriş sırasının belirli bölümlerine odaklanmasına olanak tanıyan güçlü bir teknik olan dikkat mekanizması tanıtılmaktadır. Kursta, dikkat mekanizmasının çalışma şeklini ve makine öğrenimi, metin özetleme ve soru yanıtlama gibi çeşitli makine öğrenimi görevlerinin performansını artırmak için nasıl kullanılabileceğini öğreneceksiniz.

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Bu kurs, derin öğrenmeyi kullanarak görüntülere altyazı ekleme modeli oluşturmayı öğretmektedir. Kurs sırasında görüntülere altyazı ekleme modelinin farklı bileşenlerini (ör. kodlayıcı ve kod çözücü) ve modelinizi eğitip değerlendirmeyi öğreneceksiniz. Bu kursu tamamlayan öğrenciler, kendi görüntülere altyazı ekleme modellerini oluşturabilecek ve bu modelleri görüntülere altyazı oluşturmak için kullanabilecek.

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Welcome Gamers! Add context to your virtual agent, add a phone gateway to allow users to call into your virtual agent, all while having fun! Use Dialogflow to create a conversational interface and design the end-user's intention. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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Welcome Gamers! Learn Google Cloud's Vertex AI, all while having fun! Vertex AI is Google Cloud's unified ML platform for solving your tough business problems. You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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In this game you will create and use document processors using the Document AI API, automatically extract information from digitally scanned paper forms, use the Document AI API with Python to create various processors, and create an end-to-end document processing pipeline.

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Bu kursta, kodlayıcı-kod çözücü mimarisi özet olarak anlatılmaktadır. Bu mimari; makine çevirisi, metin özetleme ve soru yanıtlama gibi "sıradan sıraya" görevlerde yaygın olarak kullanılan, güçlü bir makine öğrenimi mimarisidir. Kursta, kodlayıcı-kod çözücü mimarisinin ana bileşenlerini ve bu modellerin nasıl eğitilip sunulacağını öğreneceksiniz. Laboratuvarın adım adım açıklamalı kılavuz bölümünde ise sıfırdan şiir üretmek için TensorFlow'da kodlayıcı-kod çözücü mimarisinin basit bir uygulamasını yazacaksınız.

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Bu kursta Vertex AI Studio tanıtılmaktadır. Bu araç, üretken yapay zeka modelleriyle etkileşime geçmek, kurumsal fikirlerin prototipini oluşturmak ve bunları gerçek hayatta uygulamak için kullanılır. Gerçek hayattan kullanım alanları, etkileşimli dersler ve uygulamalı laboratuvarlar aracılığıyla, ilk istemden son ürüne uzanan yaşam döngüsünü keşfedecek ve çoklu format destekli Gemini uygulamaları, istem tasarımı, istem mühendisliği ve model ayarlama konularında Vertex AI Studio'dan nasıl yararlanabileceğinizi öğreneceksiniz. Bu kursun amacı, Vertex AI Studio'yu kullanarak projelerinizde üretken yapay zekadan yararlanabilmenizi sağlamaktır.

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Welcome Gamers! Test your skills and learn BigQuery, all while having fun! You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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Bu kursta, görüntü üretme alanında gelecek vadeden bir makine öğrenimi modelleri ailesi olan "difüzyon modelleri" tanıtılmaktadır. Difüzyon modelleri fizikten, özellikle de termodinamikten ilham alır. Geçtiğimiz birkaç yıl içinde, gerek araştırma gerekse endüstri alanında difüzyon modelleri popülerlik kazandı. Google Cloud'daki son teknoloji görüntü üretme model ve araçlarının çoğu, difüzyon modelleri ile desteklenmektedir. Bu kursta, difüzyon modellerinin ardındaki teori tanıtılmakta ve bu modellerin Vertex AI'da nasıl eğitilip dağıtılacağı açıklanmaktadır.

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Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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Giriş seviyesindeki bu mikro öğrenme kursu, sorumlu yapay zekanın ne olduğunu, neden önemli olduğunu ve Google'ın sorumlu yapay zekayı ürünlerinde nasıl uyguladığını açıklamayı amaçlamaktadır. Ayrıca Google'ın 3 yapay zeka ilkesini de tanıtır.

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Giriş seviyesindeki bu mikro öğrenme kursunda; büyük dil modellerinin (LLM) ne olduğu, hangi kullanım alanlarında kullanılabilecekleri ve istem ayarlama ile LLM performansını nasıl artırabileceğiniz ele alınmaktadır. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirebileceğiniz Google araçları da yer almaktadır.

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Bu giriş seviyesi mikro öğrenme kursu, üretken yapay zekanın ne olduğunu, nasıl kullanıldığını ve geleneksel makine öğrenimi yöntemlerinden farkını açıklamayı amaçlamaktadır. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirebileceğiniz Google araçları da ele alınmaktadır.

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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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Welcome Gamers! Today's game is all about experimenting with Big Query for Machine Learning! Use real life case studies to learn various concepts of BQML and have fun. Take labs to earn points. The faster you complete the lab objectives, the higher your score.

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Cloud Hero is played around the world, in person and online. Today, you have the opportunity to become one of the Cloud Heroes! Today's game is all about Networking skills. Earn the most points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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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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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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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.

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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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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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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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The experienced user of Google Cloud will learn how to describe build, change, provision, and destroy infrastructure, using Terraform in the cloud environment. In these hands-on labs, you will learn how to import existing infrastructure, write Terraform configuration that matches that infrastructure, and manipulate state storage with Terraform. You will demonstrate provider installation and versioning. Build, change, provision, and destroy basic infrastructure and review the Terraform plan to ensure the configuration matches the expected state and infrastructure.

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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data 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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In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API lifecycle, and how the Apigee API platform helps you manage all aspects of the lifecycle. You learn how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers. Through a combination of lessons, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the first course of the Developing APIs with the Apigee API Platform series. After completing this course, enroll in the API Security with the Apigee API Platform course.

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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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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 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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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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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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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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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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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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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.

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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

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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 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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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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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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Flutter is Google's UI toolkit for building beautiful, natively compiled applications for mobile, web, and desktop from a single codebase. In this quest you will learn how to create a Flutter app using generated template code. Be sure to tag #flutterfestival in your social posts!

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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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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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Machine Learning is essential to many modern applications nowadays. At the same time, expectations towards ML capabilities and thus complexity & size of ML models and datasets grows rapidly. In this game, you’ll experiment hands-on with how to scale ML “like Google” to iterate quickly on complex ML challenges and take your ML tasks to the next level.

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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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Organizations around the world rely on Apache Kafka to integrate existing systems in real time and build a new class of event streaming applications that unlock new business opportunities. Google and Confluent are in a partnership to deliver the best event streaming service based on Apache Kafka and to build event driven applications and big data pipelines on Google Cloud Platform. In this course, you will first learn how to deploy and create a streaming data pipeline with Apache Kafka, then try out the different functionalities of the Confluent Platform.

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Google Cloud’s four step structured Cloud Migration Path Methodology provides a defined and repeatable path for users to follow when migrating and modernizing Virtual Machines. In this quest, you will get hands-on practice with Google’s current solution set for VM assessment, planning, migration, and modernization. You will start by analyzing your lab environment and building assessment reports with CloudPhysics and StratoZone, then build a landing zone within Google Cloud leveraging Terraform’s infrastructure-as-code templates, next you will manually transform a two-tier application into a cloud-native workload running on Kubernetes, and finally, transform a VM workload into Kubernetes with Migrate for Anthos and migrate a VM between cloud environments.

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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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This quest of "Challenge Labs" gives the student preparing for the Google Cloud Certified Professional Cloud Architect certification hands-on practice with common business/technology solutions using Google Cloud architectures. Challenge Labs do not provide the "cookbook" steps, but require solutions to be built with minimal guidance, across many Google Cloud technologies. All labs have activity tracking, and in order to earn this badge you must score 100% in each lab. This quest is not easy and will put your Google Cloud technology skills to the test! Be aware that while practice with these labs will increase your knowledge and abilities, additional study, experience, and background in cloud architecture is recommended to prepare for this certification.

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This quest of "Challenge Labs" gives the student preparing for the Google Cloud Certified Professional Cloud Architect certification hands-on practice with common business/technology solutions using Google Cloud architectures. Challenge Labs do not provide the "cookbook" steps, but require solutions to be built with minimal guidance, across many Google Cloud technologies. All labs have activity tracking, and in order to earn this badge you must score 100% in each lab. This quest is not easy and will put your Google Cloud technology skills to the test! Be aware that while practice with these labs will increase your knowledge and abilities, additional study, experience, and background in cloud architecture is recommended to prepare for this certification. Complete this quest to receive an exclusive Google Cloud digital badge.

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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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Get Anthos Ready. Demand for Google Kubernetes Engine is growing, and customers are looking to Google and its partners to provide in-depth technical knowledge. This first Google Kubernetes Engine-centric Quest of best practices hands-on labs will get you started containerizing to modernize in place , and then managing your deployed apps and services -- with monitoring, tracing, and logging.

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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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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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Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 8 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.

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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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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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Earn a skill badge by completing the Build Interactive Apps with Google Assistant quest, where you will learn how to build Google Assistant applications, including how to: create an Actions project, integrate Dialogflow with an Actions project, test your application with Actions simulator, build an Assistant application with flash cards template, integrate customer MP3 files with your Assistant application, add Cloud Translation API to your Assistant application, and use APIs and integrate them into your applications. 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 the skill badge quest, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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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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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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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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This intermediate-level quest is unique among Qwiklabs quests. These labs have been curated to give operators hands-on practice with Anthos—a new, open application modernization platform on Google Cloud. Anthos enables you to build and manage modern hybrid applications. Tasks include: installing service mesh, collecting telemetry, and securing your microservices with service mesh policies. This quest is composed of labs targeted to teach you everything you need to know to introduce service mesh, and Anthos, into your next hybrid cloud project.

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This intermediate-level quest is unique among Qwiklabs quests. These labs have been curated to give operators hands-on practice with Anthos—a new, open application modernization platform on GCP. Anthos enables you to build and manage modern hybrid applications. Tasks include: installing service mesh, collecting telemetry, and securing your microservices with service mesh policies. This quest is composed of labs targeted to teach you everything you need to know to introduce service mesh, and Anthos, into your next hybrid cloud project.

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Welcome to Cloud Hero, Gamers! Click "Join this Game" to start this game. To modify your player name or avatar, go to your My Account page at https://google.qwiklabs.com. Points are earned by completing the steps in the lab.... and bonus points are earned for speed....

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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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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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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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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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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. 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…

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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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Earn a skill badge by completing the Secure Workloads in Google Kubernetes Engine quest, where you learn about security at scale on Google Kubernetes Engine (GKE) including how to: migrate containers from virtual machines to Google Kubernetes Engine, restrict network connections in GKE using firewalls and Network Policies, use role-based access controls (RBAC) in GKE, use Binary Authorization for security controls of your images, secure applications in GKE using 3 access levels: host, network, Kubernetes API, and harden GKE cluster configurations. 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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Get Anthos Ready. This Google Kubernetes Engine-centric quest of best practice hands-on labs focuses on security at scale when deploying and managing production GKE environments -- specifically role-based access control, hardening, VPC networking, and binary authorization.

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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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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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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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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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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.

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Bu kursta, web sitenizin kullanılabilir ve ölçeklenebilir olmasını sağlamak için dört Google Cloud web sitesi mimarisi hakkında bilgi edineceksiniz. Bu kursu tamamladıktan sonra, kursun sonundaki Google Cloud'da Web Sitesi Oluşturma adlı ek Yarışma Laboratuvarı'nı tamamlayarak özel bir Google Cloud dijital rozeti kazanın. Bu kurs, Get Cooking in Cloud adlı video serisini temel alır.

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Google Cloud'da Web Sitesi Derleme beceri rozeti kursunu tamamlayarak giriş düzeyindeki beceri rozetini kazanın. Get Cooking in Cloud serisine dayanan bu kursta şu konular ele alınır:Cloud Run'da web sitesi dağıtmaCompute Engine'de web uygulaması barındırmaGoogle Kubernetes Engine'de web sitenizi oluşturma, dağıtma ve ölçeklendirmeCloud Build'i kullanarak monolitik bir uygulamadan mikro hizmetler mimarisine geçiş

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Büyük veri, makine öğrenimi ve yapay zeka bilişim alanında günümüzün popüler konularıdır. Ancak bu alanlar yüksek uzmanlık gerektirir ve giriş seviyesi eğitim materyalleri zor bulunur. Neyse ki Google Cloud, bu alanlarda kullanıcı dostu hizmetler sunuyor ve bu giriş seviyesi kurs sayesinde BigQuery, Cloud Speech API ve Video Intelligence gibi araçlarla ilk adımlarınızı atmanıza imkan tanıyor.

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Get hands-on practice with Google Cloud’s app dev tools and services. You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points. All players who complete all of the labs will be awarded with this game badge. The access code for this game will be- "5a-devjam-app"

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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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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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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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Get hands-on practice with Google Cloud’s infrastructure tools and services. You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points. All players who complete all of the labs will be awarded with this game badge. The access code for this game will be- "5a-devjam-infra".

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Bu giriş seviyesi kurs, diğer kurs teklifleri arasında benzersiz bir yere sahiptir. Laboratuvarlar, BT profesyonellerine Google Cloud Certified Associate Cloud Engineer sertifikasında geçen konular ve hizmetlerle ilgili uygulamalı alıştırma imkanı tanımak üzere tasarlandı. Bu kurs; IAM, ağ iletişimi ve Kubernetes Engine dağıtımı gibi alanlarda Google Cloud bilginizi test edecek özel laboratuvarlardan oluşur. Bu tür laboratuvarlarda yapacağınız alıştırmalarla becerilerinizi geliştirebilirsiniz ancak sınav kılavuzunu ve diğer mevcut hazırlık kaynaklarını da incelemenizi öneririz.

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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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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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The hands-on labs in this Quest are structured to give experienced app developers hands-on practice with the state-of-the-art developing applications in Google Cloud. The topics align with the Google Cloud Certified Professional Cloud Developer Certification. These labs follow the sequence of activities needed to create and deploy an app in Google Cloud from beginning to end. Be aware that while practice with these labs will increase your skills and abilities, it is recommended that you also review the exam guide and other available preparation resources.

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In this advanced-level quest, you will learn the ins and outs of developing GCP applications in Java. 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 Java 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 Java applications straight away.

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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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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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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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Bulut geliştirme konusunda yeniyseniz ve Google Cloud'un Temel Özellikleri kursunun da ötesinde uygulamalı alıştırma yapmak istiyorsanız bu kurs tam size göre. Cloud Storage'ın yanı sıra Monitoring ve Cloud Functions gibi diğer önemli uygulama hizmetlerini ayrıntılı bir şekilde inceleyen laboratuvarlarla uygulamalı deneyim kazanacaksınız. Her türlü Google Cloud girişiminde kullanabileceğiniz değerli beceriler geliştireceksiniz.

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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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Güvenli Bir Google Cloud Ağı Oluşturma kursunu tamamlayarak beceri rozeti kazanın. Bu kursta, Google Cloud'da uygulamalarınızı derlemek, ölçeklendirmek ve korumak için ağla ilgili birden fazla kaynak hakkında bilgi edineceksiniz.

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Google Cloud Ağınızı Geliştirme kursunu tamamlayarak bir beceri rozeti kazanın. IAM rollerini keşfetme ve proje erişimi ekleme/kaldırma, VPC ağları oluşturma, Compute Engine sanal makinelerini dağıtma ve izleme, SQL sorguları yazma ve çeşitli dağıtım yaklaşımlarıyla Kubernetes'i kullanarak uygulama dağıtma gibi uygulamaları dağıtıp izlemeyle ilgili birden çok yöntemi 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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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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