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Shyam Chitgopkar

Member since 2019

Silver League

53688 points
Agent Fundamentals Earned Mar 7, 2026 EST
Build a Certification Study Guide: PMLE Earned Mar 4, 2026 EST
Generative AI Explorer - Vertex AI Earned Mar 1, 2026 EST
Sorumlu Yapay Zeka'ya Giriş Earned Oca 27, 2025 EST
Build Generative AI Agents with Vertex AI and Flutter Earned Oca 26, 2025 EST
Vertex AI Studio'ya Giriş Earned Ara 28, 2024 EST
Üretken Yapay Zeka İçin Makine Öğrenimi Operasyonları (MLOps) Earned Kas 5, 2024 EST
Data Lake Modernization on Google Cloud: Cloud Composer Earned Ağu 10, 2024 EDT
Google Cloud Ağınızı Geliştirme Earned Nis 13, 2024 EDT
Machine Learning Operations (MLOps): Getting Started Earned Mar 15, 2024 EDT
Introduction to AI and Machine Learning on Google Cloud Earned Mar 12, 2024 EDT
Optimize Costs for Google Kubernetes Engine Earned Şub 21, 2024 EST
Implement CI/CD Pipelines on Google Cloud Earned Şub 12, 2024 EST
Optimize Your Google Cloud Costs Earned Şub 9, 2024 EST
Build Infrastructure with Terraform on Google Cloud Earned Şub 6, 2024 EST
Getting Started with Terraform for Google Cloud Earned Şub 5, 2024 EST
Developing a Google SRE Culture Earned Şub 5, 2024 EST
Monitor and Log with Google Cloud Observability Earned Şub 5, 2024 EST
Using DevSecOps in your Google Cloud Environment Earned Oca 31, 2024 EST
Implement DevOps Workflows in Google Cloud Earned Oca 31, 2024 EST
DEPRECATED Cloud Operations and Service Mesh with Anthos Earned Oca 30, 2024 EST
Reliable Google Cloud Infrastructure: Design and Process Earned Oca 29, 2024 EST
App Engine: 3 Ways Earned Ara 19, 2023 EST
Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma Earned Ara 15, 2023 EST
Compute Engine İçin Cloud Load Balancing'i Uygulama Earned Ara 14, 2023 EST
Logging and Monitoring in Google Cloud Earned Ara 14, 2023 EST
Elastic Google Cloud Infrastructure: Scaling and Automation Earned Ara 12, 2023 EST
Getting Started with Google Kubernetes Engine Earned Kas 27, 2023 EST
Essential Google Cloud Infrastructure: Core Services Earned Kas 23, 2023 EST
Essential Google Cloud Infrastructure: Foundation Earned Kas 21, 2023 EST
Google Cloud Fundamentals: Core Infrastructure Earned Kas 9, 2023 EST
Preparing for Your Associate Cloud Engineer Journey Earned Kas 7, 2023 EST
Automate Deployment and Manage Traffic on a Google Cloud Network Earned Kas 7, 2023 EST
Generative AI Fundamentals Earned Ağu 30, 2023 EDT
Büyük Dil Modellerine Giriş Earned Ağu 30, 2023 EDT
Üretken Yapay Zekaya Giriş Earned Ağu 30, 2023 EDT
DevOps Engineer Quizathon Earned Ağu 29, 2023 EDT

AI Agents represent a major shift beyond traditional large language models (LLMs): instead of simply generating text-based solutions, they can also act autonomously to execute them. This course introduces the fundamentals of AI Agents, how they differ from LLM APIs, and where they add value in the real world. Based on Google’s agents whitepaper, it provides the theoretical foundation needed before writing your first lines of agent code—ideal for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior (and not just text generation). Join the community forum for questions and discussions.

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Learn how to use NotebookLM to create a personalized study guide for the Professional Machine Learning Engineer certification exam (PMLE). You'll review NotebookLM features, create a notebook, and use the study guide to practice for a certification exam.

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The Generative AI Explorer - Vertex Quest is a collection of labs on how to use Generative AI on Google Cloud. Through the labs, you will learn about how to use the models in the Vertex AI PaLM API family, including text-bison, chat-bison, and textembedding-gecko. You will also learn about prompt design, best practices, and how it can be used for ideation, text classification, text extraction, text summarization, and more. You will also learn how to tune a foundation model by training it via Vertex AI custom training and deploy it to a Vertex AI endpoint.

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Bu kurs, sorumlu yapay zekanın ne olduğunu, neden önemli olduğunu ve Google'ın sorumlu yapay zekayı ürünlerinde nasıl uyguladığını açıklamayı amaçlayan giriş seviyesinde bir mikro öğrenme kursudur. Ayrıca Google'ın 7 yapay zeka ilkesini de tanıtır.

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In this course, you learn how to develop an app using Flutter, Google's portable UI toolkit, and integrate the app with Gemini, Google's family of generative AI models. You also use Vertex AI Agent Builder, Google's platform for building and managing AI Agents and applications.

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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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Bu kurs, MLOps ekiplerinin üretken yapay zeka modellerini dağıtırken ve yönetirken karşılaştığı zorlukların üstesinden gelmek için gereken bilgi ve araçları sağlamaktadır. Ayrıca yapay zeka ekiplerinin, MLOps süreçlerini kolaylaştırıp üretken yapay zeka projelerinde başarıya ulaşması için Vertex AI'ın nasıl yardımcı olduğunu öğrenmenizi amaçlamaktadır.

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Welcome to Cloud Composer, where we discuss how to orchestrate data lake workflows with Cloud Composer.

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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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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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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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Earn the intermediate skill badge by completing the Implement CI/CD Pipelines on Google Cloud skill badge course where you learn how to use Artifact Registry, Cloud Build, and Cloud Deploy. You interact with the Google Cloud console, Google Cloud CLI, Cloud Run, and GKE. This course teaches you how to build continuous integration pipelines, store and secure artifacts, scan for vulnerabilities, attest to the validity of approved releases. Additionally, you get hands-on experience deploying applications to both GKE and Cloud Run.

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This is the second Quest in a two-part series on Google Cloud billing and cost management essentials. This Quest is most suitable for those in a Finance and/or IT related role responsible for optimizing their organization’s cloud infrastructure. Here you'll learn several ways to control and optimize your Google Cloud costs, including setting up budgets and alerts, managing quota limits, and taking advantage of committed use discounts. In the hands-on labs, you’ll practice using various tools to control and optimize your Google Cloud costs or to influence your technology teams to apply the cost optimization best practices.

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

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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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This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in either of those courses. Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective.

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Earn a skill badge by completing the App Engine`:` 3 ways course, where you learn how to use App Engine with Python, Go, and PHP.

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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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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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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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Welcome to the Getting Started with Google Kubernetes Engine course. If you're interested in Kubernetes, a software layer that sits between your applications and your hardware infrastructure, then you’re in the right place! Google Kubernetes Engine brings you Kubernetes as a managed service on Google Cloud. The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, as it’s commonly referred to, and how to get applications containerized and running in Google Cloud. The course starts with a basic introduction to Google Cloud, and is then followed by an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.

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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, 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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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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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.

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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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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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Bu giriş seviyesi mikro öğrenme kursunda büyük dil modelleri (BDM) nedir, hangi kullanım durumlarında kullanılabileceği ve büyük dil modelleri performansını artırmak için nasıl istem ayarlaması yapabileceğiniz keşfedilecektir. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirmenize yardımcı olacak Google araçları hakkında bilgi verilecektir.

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Bu, üretken yapay zekanın ne olduğunu, nasıl kullanıldığını ve geleneksel makine öğrenme yöntemlerinden nasıl farklı olduğunu açıklamayı amaçlayan giriş seviyesi bir mikro öğrenme kursudur. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirmenize yardımcı olacak Google Araçlarını da kapsar.

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Welcome to the Quizathon! Check your DevOps expertise in Google Cloud.

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