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gartham siddharth rao

Member since 2025

Diamond League

7478 points
Implement Cloud Collaboration and Productivity Workflows Earned Nov 26, 2025 EST
Level 2: Intelligent Development and Automation Earned Nov 20, 2025 EST
Google Skills Arcade Trivia November 2025 Week 3 Earned Nov 19, 2025 EST
Google Skills Arcade Trivia November 2025 Week 4 Earned Nov 19, 2025 EST
Manage Kubernetes in Google Cloud Earned Nov 18, 2025 EST
Google Skills Arcade Trivia November 2025 Week 2 Earned Nov 16, 2025 EST
Google Skills Arcade Trivia November 2025 Week 1 Earned Nov 16, 2025 EST
Level 3: Scalable Deployments and Delivery Earned Nov 14, 2025 EST
Google Skills Arcade Base Camp November 2025 Earned Nov 13, 2025 EST
Introduction to Data Analytics in Google Cloud Earned Nov 7, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation Earned Nov 5, 2025 EST
AI Infrastructure: Cloud TPUs Earned Oct 24, 2025 EDT
AI Infrastructure: Cloud GPUs Earned Oct 24, 2025 EDT
AI Infrastructure: Introduction to AI Hypercomputer Earned Oct 24, 2025 EDT
Introduction to Responsible AI Earned Oct 24, 2025 EDT
Introduction to Generative AI Earned Oct 24, 2025 EDT
Introduction to Large Language Models Earned May 6, 2025 EDT
Machine Learning Operations (MLOps) for Generative AI Earned Apr 17, 2025 EDT

Earn an introductory skill badge by completing the Implement Cloud Collaboration and Productivity Workflows course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.

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Innovation today depends on how data, intelligence, and automation come together. With over 70% of organizations adopting cloud-native tools to accelerate development, this challenge will help you learn the technologies shaping that shift. In the first section, you’ll build dynamic dashboards in Looker, manage APIs through API Gateway, and design engaging Conversational Agents that make user interactions smarter and more intuitive. The second section focuses on bringing ideas to life at scale—deploying apps with Cloud Run and Compute Engine, streamlining workflows with Pub/Sub, managing artifacts efficiently, and adding real-time intelligence with tools like Speech-to-Textand Google Sheets charts. Together, these labs prepare you to create intelligent, connected systems that learn, respond, and scale effortlessly.

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Hey there! You're invited to game on with Google Skills Arcade Trivia for November Week 3! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the November Trivia Week 3 badge!

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Hey there! You're invited to game on with Google Skills Arcade Trivia for November Week 4! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the November Trivia Week 4 badge!

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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.

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Hey there! You're invited to game on with Google Skills Arcade Trivia for November Week 2! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the November Trivia Week 2 badge!

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Hey there! You're invited to game on with Google Skills Arcade Trivia for November Week 1! Play throughout the month and boost your cloud learning journey. Every week, we'll release a new set of questions to test your knowledge of Google Cloud Platform. Get started now and earn the November Trivia Week 1 badge!

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From code to cloud, automation drives reliable, repeatable deployment. With over 80% of enterprises adopting DevOps practices, this challenge will guide you through building and managing secure, scalable infrastructure on Google Cloud. You’ll create Artifact Registries for Go, Python, Maven, and more—managing dependencies securely—and deploy static sites using Nginx, Traefik, and Caddy V2 on Cloud Run. Then you will dive into into Terraform Essentials, where you’ll define cloud resources as code—from VPCs and firewall rules to Compute Engine and Cloud Storage—and safeguard configurations with Secret Manager. Together, these labs give you hands-on experience in automating deployments and strengthening cloud infrastructure from the ground up.

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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!

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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.

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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production. Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

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Welcome to the Cloud TPUs course. We'll explore the advantages and disadvantages of TPUs in various scenarios and compare different TPU accelerators to help you choose the right fit. You'll learn strategies to maximize performance and efficiency for your AI models and understand the significance of GPU/TPU interoperability for flexible machine learning workflows. Through engaging content and practical demos, we'll guide you step-by-step in leveraging TPUs effectively.

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Curious about the powerful hardware behind AI? This module breaks down performance-optimized AI computers, showing you why they're so important. We'll explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them. By the end, you'll know exactly how to pick the right GPU for your AI projects, helping you make smart choices for your AI workloads.

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Ready to get started with AI Hypercomputers? This course makes it easy! We'll cover the basics of what they are and how they help AI with AI workloads. You'll learn about the different components inside a hypercomputer, like GPUs, TPUs, and CPUs, and discover how to pick the right deployment approach for your needs.

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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.

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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.

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