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Vijay Ghyar

Member since 2025

Gold League

3481 points
Digital Transformation with Google Cloud Earned Oca 23, 2026 EST
AI Boost Bites: Your Personal Feedback Agent Earned Oca 23, 2026 EST
AI Infrastructure: Storage Options Earned Oca 23, 2026 EST
AI Infrastructure: Deployment Types Earned Oca 23, 2026 EST
AI Infrastructure: Cloud TPUs Earned Oca 23, 2026 EST
AI Infrastructure: Cloud GPUs Earned Oca 23, 2026 EST
AI Infrastructure: Introduction to AI Hypercomputer Earned Oca 23, 2026 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation Earned Oca 12, 2026 EST
Üretken Yapay Zeka İçin Makine Öğrenimi Operasyonları (MLOps) Earned Oca 12, 2026 EST
Sorumlu Yapay Zeka'ya Giriş Earned Oca 12, 2026 EST
Büyük Dil Modellerine Giriş Earned Oca 11, 2026 EST
Üretken Yapay Zekaya Giriş Earned Oca 11, 2026 EST

There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.

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This video covers how to build a personalized "Work with Me" agent using Gemini Gems, which helps streamline foundational feedback and makes your meetings more strategic and efficient.

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In this course, you’ll take a comprehensive journey through the storage solutions available on Google Cloud, specifically tailored for AI and high-performance computing (HPC) workloads. You’ll learn how to choose the right storage for each stage of the ML lifecycle. You’ll explore how to optimize for I/O performance during training, manage massive datasets for data preparation, and serve model artifacts with low latency. Through practical examples and demonstrations, you’ll gain the expertise to design robust storage solutions that accelerate your AI innovation.

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This course provides a comprehensive guide to deploying, managing, and optimizing AI and high-performance computing (HPC) workloads on Google Cloud. Through a series of lessons and practical demonstrations, you’ll explore diverse deployment strategies, ranging from highly customizable environments using Google Compute Engine (GCE) to managed solutions like Google Kubernetes Engine (GKE). Specifically, you’ll learn how to create clusters and deploy GKE for inference.

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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 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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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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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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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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