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Akash Jagtap

Membro dal giorno 2023

Campionato Diamante

6983 punti
Deploy Multi-Agent Architectures Earned set 3, 2026 EDT
Build Collaborative Multi-Agent Systems with ADK & MCP Earned set 1, 2026 EDT
Add Agent Capabilities With Tools Earned ago 31, 2026 EDT
Manage Agent Memory and State Earned ago 21, 2026 EDT
Engineer AI Agents with Agent Development Kit (ADK) Earned lug 31, 2026 EDT
Optimize Agent Behavior Earned lug 29, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK) Earned lug 27, 2026 EDT
Agent Fundamentals Earned lug 25, 2026 EDT
Exploring Data Transformation with Google Cloud Earned nov 23, 2023 EST
Digital Transformation with Google Cloud Earned nov 23, 2023 EST
Introduction to Responsible AI - Italiano Earned nov 23, 2023 EST
Introduction to Generative AI - Italiano Earned nov 23, 2023 EST
Introduction to Large Language Models - Italiano Earned nov 23, 2023 EST

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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Learn to design, coordinate, and deploy multi-agent systems using Google’s Agent Development Kit (ADK) and the Model Context Protocol (MCP). Using a travel concierge example, you'll learn to orchestrate a network of specialized agents with custom guardrails. By the end of the course, you'll understand the design patterns and deployment strategies required for robust, scalable AI workflows. 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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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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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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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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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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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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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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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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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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