Ali Kuzhuget
Membro dal giorno 2023
Campionato Diamante
18369 punti
Gemini for Application Developers
Earned apr 26, 2026 EDT
Boost Productivity with Gemini in BigQuery
Earned apr 26, 2026 EDT
Gemini for end-to-end SDLC
Earned apr 16, 2026 EDT
Work with Gemini Models in BigQuery
Earned apr 15, 2026 EDT
Using BigQuery Machine Learning for Inference
Earned apr 15, 2026 EDT
Gemini for Data Scientists and Analysts
Earned apr 14, 2026 EDT
AI Boost Bites: Tame Your Inbox with AI
Earned apr 12, 2026 EDT
AI Boost Bites: Email Content Creation
Earned apr 12, 2026 EDT
[DEPRECATED] Google Sheets
Earned apr 12, 2026 EDT
Conversational Insights
Earned apr 7, 2026 EDT
Create ML Models with BigQuery ML
Earned apr 5, 2026 EDT
AI Infrastructure: Cloud TPUs
Earned apr 5, 2026 EDT
AI Infrastructure: Introduction to AI Hypercomputer
Earned apr 5, 2026 EDT
AI Infrastructure: Cloud GPUs
Earned apr 5, 2026 EDT
Introduction to Google Distributed Cloud Sandbox
Earned apr 5, 2026 EDT
AI Boost Bites: Create Your Own Retro Arcade Game
Earned apr 5, 2026 EDT
Build a Certification Study Guide: PCNE Exam Prep
Earned apr 5, 2026 EDT
Google DeepMind: Train A Small Language Model
Earned apr 1, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model
Earned mar 28, 2026 EDT
Optimize Agent Behavior
Earned mar 19, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK)
Earned mar 19, 2026 EDT
Agent Fundamentals
Earned mar 19, 2026 EDT
Implement Cloud Collaboration and Productivity Workflows
Earned mar 19, 2026 EDT
Digital Transformation with Google Cloud
Earned mar 19, 2026 EDT
Model Armor: Securing AI Deployments
Earned mar 18, 2026 EDT
Introduction to Security in the World of AI
Earned mar 18, 2026 EDT
AI responsabile per sviluppatori: privacy e sicurezza
Earned mar 18, 2026 EDT
Working with Notebooks in Vertex AI
Earned mar 17, 2026 EDT
AI responsabile per sviluppatori: interpretabilità e trasparenza
Earned mar 17, 2026 EDT
AI responsabile per sviluppatori: equità e bias
Earned mar 17, 2026 EDT
Introduzione all'AI e al machine learning su Google Cloud
Earned mar 16, 2026 EDT
Gen AI Agents: Transform Your Organization
Earned mar 13, 2026 EDT
AI Boost Bites: Your Personal Feedback Agent
Earned mar 13, 2026 EDT
Gen AI Apps: Transform Your Work
Earned mar 13, 2026 EDT
Gen AI: Navigate the Landscape
Earned mar 12, 2026 EDT
Gen AI: Unlock Foundational Concepts
Earned mar 12, 2026 EDT
Gen AI: Beyond the Chatbot
Earned mar 11, 2026 EDT
Prompt Design in Agent Platform
Earned mar 11, 2026 EDT
Responsible AI: Applying AI Principles with Google Cloud - Italiano
Earned mar 11, 2026 EDT
Build a Certification Study Guide: PMLE
Earned mar 9, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation
Earned mar 9, 2026 EDT
Introduction to Responsible AI - Italiano
Earned mar 8, 2026 EDT
Introduction to Generative AI - Italiano
Earned mar 8, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned mar 7, 2026 EST
Introduction to Large Language Models - Italiano
Earned mar 7, 2026 EST
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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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.
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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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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
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Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
Duet AI was renamed to Gemini, our next-generation model.
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This video covers how to use Gemini in Gmail to summarize emails, find information, and draft replies, helping you manage your inbox more efficiently.
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This video covers how to use Gemini in Gmail to draft new emails,
refine their tone, respond with context from Drive files, and use smart
reply suggestions.
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In this course we will introduce you to Google Sheets, Google’s cloud-based spreadsheet software, included with Google Workspace.
With Google Sheets, you can create and edit spreadsheets directly in your web browser—no special software is required.
Multiple people can work simultaneously, you can see people’s changes as they make them, and every change is saved automatically.
You will learn how to open Google Sheets, create a blank spreadsheet, and create a spreadsheet from a template. You will add, import, sort, filter and format your data using Google Sheets and learn how to work across different file types.
Formulas and functions allow you to make quick calculations and better use your data. We will look at creating a basic formula, using functions, and referencing data. You will also learn how to add a chart to your spreadsheet.
Google Sheets spreadsheets are easy to share. We will look at the different ways you can share with others. We will also discuss how to track changes…
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In this course you will learn how to leverage Conversational Insights to uncover hidden information from your contact center data to increase operational efficiency and drive data-driven business decisions.
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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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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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Ready to get started with AI Hypercomputer? 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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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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In this course, you'll gain a solid understanding of Google Distributed Cloud (GDC) Sandbox—a cost-effective and accessible environment for building, testing, and evaluating GDC solutions. You'll explore the GDC Sandbox's architecture, key features, and service offerings and see how they enable real-world use cases. Most importantly, you'll observe demonstrations on performing essential operational tasks, such as deploying virtual machines and containers.
By the end, you'll be equipped to confidently navigate the GDC Sandbox environment.
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In this video, you'll learn to use a simple text prompt in Gemini Canvas to build a playable game. You'll see how to create a Tic-Tac-Toe game, use a follow-up prompt to customize its theme to a retro 8-bit style, and share the final game with a link.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Network Engineer certification exam. You'll review Gemini Notebook features, add sources to your notebook, and learn how to personalize your Gemini Notebook experience to study for the exam.
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Complete the advanced Google DeepMind: Train A Small Language Model skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model. Access this lab at no-cost by signing up for the no-cost subscription. Receive 35 free credits each month!
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In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.
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You’ve built your first agent—now it’s time to take it further. In this course, you’ll advance your skills by learning how to turn a basic AI agent into a sophisticated, precise assistant—applying advanced instructions, model selection, planning capabilities, and structured output patterns.
Join the community forum for questions and discussions
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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.
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This course introduces the fundamentals of AI agents and explores where agents add value in the real world. It provides a foundation for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior.
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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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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 reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI applications.
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Artificial Intelligence (AI) offers transformative possibilities, but it also introduces new security challenges. This course equips security and data protection leaders with strategies to securely manage AI within their organizations. Learn a framework for proactively identifying and mitigating AI-specific risks, protecting sensitive data, ensuring compliance, and building a resilient AI infrastructure. Pick use cases from four different industries to explore how these strategies apply in real-world scenarios.
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Questo corso introduce argomenti importanti relativi alla privacy e alla sicurezza dell'AI. Esplora metodi e strumenti pratici per implementare le pratiche consigliate per la privacy e la sicurezza dell'AI utilizzando gli strumenti open source e i prodotti Google Cloud.
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This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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Questo corso introduce i concetti di interpretabilità e la trasparenza dell'AI. Parla dell'importanza della trasparenza dell'AI per sviluppatori ed engineer. Illustra metodi e strumenti pratici per aiutare a raggiungere interpretabilità e trasparenza sia nei dati che nei modelli di AI.
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Questo corso introduce i concetti di AI responsabile e i principi dell'AI. Tratta le tecniche per identificare sostanzialmente l'equità e i bias e mitigare i bias nelle pratiche di AI/ML. Illustra metodi e strumenti pratici per implementare le best practice dell'AI responsabile utilizzando gli strumenti open source e i prodotti Google Cloud.
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Questo corso presenta le offerte di intelligenza artificiale (AI) e machine learning (ML) su Google Cloud per la creazione di progetti di AI predittiva e generativa. Esplora le tecnologie, i prodotti e gli strumenti disponibili durante tutto il ciclo di vita data-to-AI, includendo le basi, lo sviluppo e le soluzioni di AI. Ha lo scopo di aiutare data scientist, sviluppatori di AI e ML engineer a migliorare le proprie abilità e conoscenze attraverso attività di apprendimento coinvolgenti ed esercizi pratici.
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Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reasoning loops, and tools. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and Gemini Notebook. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.
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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.
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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.
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Complete the introductory Prompt Design in Agent Platform skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Agent Platform. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.
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Dal momento che l'uso dell'intelligenza artificiale e del machine learning nelle aziende continua a crescere, cresce anche l'importanza di realizzarli in modo responsabile. Molti sono scoraggiati dal fatto che parlare di IA responsabile può essere più facile che metterla in pratica. Se vuoi imparare come operativizzare l'IA responsabile nella tua organizzazione, questo corso fa per te.
In questo corso scoprirai come Google Cloud ci riesce attualmente, oltre alle best practice e alle lezioni apprese, per fungere da framework per costruire il tuo approccio all'IA responsabile.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
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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 Agent Platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'IA responsabile, perché è importante e in che modo Google implementa l'IA responsabile nei propri prodotti. Introduce anche i 7 principi dell'IA di Google.
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Questo è un corso di microlearning di livello introduttivo volto a spiegare cos'è l'AI generativa, come viene utilizzata e in che modo differisce dai tradizionali metodi di machine learning. Descrive inoltre gli strumenti Google che possono aiutarti a sviluppare le tue app Gen AI.
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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 Gemini Enterprise Agent Platform empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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Questo è un corso di microlearning di livello introduttivo che esplora cosa sono i modelli linguistici di grandi dimensioni (LLM), i casi d'uso in cui possono essere utilizzati e come è possibile utilizzare l'ottimizzazione dei prompt per migliorare le prestazioni dei modelli LLM. Descrive inoltre gli strumenti Google per aiutarti a sviluppare le tue app Gen AI.
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