Partecipa Accedi

Jovan Vito Viani

Membro dal giorno 2025

Campionato Diamante

9221 punti
Orchestrate Multi-agent Workflows with Gemini Enterprise Earned ott 7, 2026 EDT
Human-Centered AI Earned ott 7, 2026 EDT
Gen AI Agents: Transform Your Organization Earned ott 7, 2026 EDT
Deploy Multi-Agent Architectures Earned ott 7, 2026 EDT
Deploy Your First Agent Earned set 28, 2026 EDT
Build and Deploy Agents in Production Earned set 28, 2026 EDT
Add Agent Capabilities With Tools Earned set 28, 2026 EDT
Manage Agent Memory and State Earned set 28, 2026 EDT
Optimize Agent Behavior Earned set 28, 2026 EDT
Engineer AI Agents with Agent Development Kit (ADK) Earned set 28, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK) Earned set 23, 2026 EDT
Create Your First Gemini Enterprise Application Earned set 23, 2026 EDT
Enterprise Agents and Use Cases Earned set 23, 2026 EDT
Agent Fundamentals Earned set 23, 2026 EDT
Prompt Design in Agent Platform Earned apr 4, 2026 EDT
Introduction to Responsible AI - Italiano Earned apr 2, 2026 EDT
Introduction to Large Language Models - Italiano Earned apr 2, 2026 EDT
Introduction to Generative AI - Italiano Earned apr 2, 2026 EDT
AI responsabile per sviluppatori: interpretabilità e trasparenza Earned apr 1, 2026 EDT
AI responsabile per sviluppatori: equità e bias Earned apr 1, 2026 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation Earned apr 1, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI Earned apr 1, 2026 EDT
Boost Productivity with Gemini in BigQuery Earned apr 1, 2026 EDT
Work with Gemini Models in BigQuery Earned apr 1, 2026 EDT
Using BigQuery Machine Learning for Inference Earned mar 31, 2026 EDT
Gemini for Data Scientists and Analysts Earned mar 31, 2026 EDT
Responsible AI: Applying AI Principles with Google Cloud - Italiano Earned nov 19, 2025 EST
Digital Transformation with Google Cloud Earned ott 22, 2025 EDT
Exploring Data Transformation with Google Cloud Earned ott 22, 2025 EDT

Complete the introductory Orchestrate Multi-Agent Workflows with Gemini Enterprise skill badge to demonstrate skills in the following: using agentic assistants powered by Gemini Enterprise to unify data across first- and third-party sources, develop multimedia marketing materials, and automate business actions across systems. Skill badges validate your practical knowledge on specific products through hands-on labs and challenge assessments. Earn a badge by completing a course or jump straight into the challenge lab to get your badge today. Badges prove your proficiency, enhance your professional profile, and ultimately lead to increased career opportunities. Visit your profile to track badges you’ve earned. Explore other content in the Gemini Agent Ready (GEAR) program.

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Explore the vital transition from task-driven workflows to human-centric AI orchestration. You will learn to strategically distinguish between augmentation and automation, and how to balance machine efficiency with human intuition. Explore other content in the Gemini Agent Ready (GEAR) program.

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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 Agent Ready (GEAR) program.

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Complete the advanced Deploy Multi-Agent Architectures skill badge to demonstrate skills in the following: building multi-agent systems with ADK, connecting agents with the Agent-to-Agent (A2A) protocol, integrating external tools using the Model Context Protocol (MCP), and deploying a complete multi-agent solution to Agent Engine. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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Take your agents from localhost to production. This course teaches you to deploy ADK agents to Agent Runtime and Cloud Run, with optional cross-session memory via Memory Bank. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program. Join the community forum for questions and discussions

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Explore the architecture and deployment of multi-agent systems using Google’s Agent Development Kit (ADK) and Google Cloud’s robust infrastructure. You will learn to design hierarchical agent trees and deterministic workflow agents while identifying the ideal hosting environment—from serverless Cloud Run to high-performance GKE—to ensure your AI agents are secure, scalable, and production-ready. Explore other content in the Gemini Agent Ready (GEAR) program.

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You’ve built agents with advanced configuration—now give them real-world capabilities. Equip agents with tools that enable searching the web, executing code, querying databases, and performing custom actions. Transform agents from intelligent responders into capable assistants that take action. Explore other content in the Gemini Agent Ready (GEAR) program. Join the community forum for questions and discussions

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You've built basic LLM agents that respond to queries—now let's make them stateful. Use session state to build agents that maintain context, remember user preferences, and provide personalized experiences. Transform agents from stateless responders to intelligent assistants. Explore other content in the Gemini Agent Ready (GEAR) program. Join the community forum for questions and discussions

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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. Explore other content in the Gemini Agent Ready (GEAR) program. Join the community forum for questions and discussions

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Complete the intermediate Engineer AI Agents with Agent Development Kit (ADK) 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. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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

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Create your first Gemini Enterprise application to earn a skill badge! Connect diverse data sources to your application to build a powerful, unified search and analysis engine. Master advanced capabilities like deep research agents, multi-agent ideation, and Gemini Notebook for focused analysis. Explore other content in the Gemini Agent Ready (GEAR) program.

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Discover how AI agents drive business impact. You’ll map agent types to your KPIs and explore use cases that solve real bottlenecks. Then, learn how Gemini Enterprise empowers you to build and orchestrate the right agents—from no-code to high-code solutions. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.

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

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

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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 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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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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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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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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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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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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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.

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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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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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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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