Thant Htoo San
Jest członkiem od 2023
Liga diamentowa
6589 pkt.
Engineer AI Agents with Agent Development Kit (ADK)
Earned paź 15, 2026 EDT
Optimize Agent Behavior
Earned paź 15, 2026 EDT
Agentic Strategy: Discover, Design, and Prototype
Earned paź 14, 2026 EDT
Liftoff with Google Antigravity: Build a Video Game with AI
Earned paź 8, 2026 EDT
Understand Google Cloud Agents
Earned paź 6, 2026 EDT
Orchestrate Multi-agent Workflows with Gemini Enterprise
Earned paź 1, 2026 EDT
Human-Centered AI
Earned paź 1, 2026 EDT
Gen AI Agents: Transform Your Organization
Earned paź 1, 2026 EDT
Deploy Your First Agent
Earned maj 15, 2026 EDT
Build and Deploy Agents in Production
Earned maj 15, 2026 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned kwi 12, 2026 EDT
Create ML Models with BigQuery ML
Earned kwi 11, 2026 EDT
The Basics of Google Cloud Compute
Earned kwi 11, 2026 EDT
Create Agents with Generative Playbooks
Earned kwi 11, 2026 EDT
AI Boost Bites: Automate tasks with Gemini and Apps Script
Earned kwi 11, 2026 EDT
Vector Search and Embeddings
Earned kwi 10, 2026 EDT
Deploy Multi-Agent Architectures
Earned kwi 9, 2026 EDT
Przygotowywanie danych do użycia z interfejsami ML w Google Cloud
Earned kwi 9, 2026 EDT
Create Embeddings, Vector Search, and RAG with BigQuery
Earned kwi 9, 2026 EDT
Introduction to Security in the World of AI
Earned kwi 6, 2026 EDT
Deploy Multi-Agent Systems with Gemini Enterprise Agent Platform
Earned kwi 5, 2026 EDT
Model Armor: Securing AI Deployments
Earned kwi 1, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned mar 8, 2026 EST
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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Step into the future with Agentic Strategy: Discover, Design, and Prototype. This course allows you to master the Google Agentic AI Transformation Framework and move beyond chatbots to autonomous teammates. Through a retail use case, you will learn to quantify business value, prioritize AI projects, map critical user journeys, and build functional prototypes using no-code tools like Google AI Studio and Gemini Enterprise. This course provides a solid roadmap necessary for business and technical leaders to lead their organization into the agentic AI era. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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In this course, you'll learn to build software at a propulsive speed by orchestrating agents in Google Antigravity. This hands-on course will first guide you to install and get started with Antigravity by making a Hello, World(s)! app. Next, you'll use Firebase to deploy that app. Finally, you'll build a video game, Voyager, by orchestrating agents in Antigravity to work in parallel.
Explore other content in the Gemini Agent Ready (GEAR) program.
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This course provides a comprehensive overview of Google Cloud's agent platforms, Gemini Enterprise app, Conversational Agents, Customer Experience (CX) Studio, Gemini Enterprise Agent Platform, and Agent Development Kit. Learners will understand the unique capabilities of each offering, distinguish between the optimal solution for specific use cases, and gain foundational knowledge in creating search and chat applications. Explore other content in the Gemini Agent Ready (GEAR) program.
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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 Enterprise 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 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 Enterprise Agent Ready (GEAR) program.
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Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
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This course will teach you how to build conversational experiences for Conversational Agents using Generative Playbooks. You'll start with an introduction to playbooks and learn how to set up your first one. You'll also learn about the importance of testing, as well as key production considerations like quota limits and integration. The course concludes with a case study that shows how to use playbooks for generative steering. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This video covers how to use Gemini and Apps Script to automate manual tasks across Google Workspace. You'll learn to prompt Gemini to generate Apps Script code that automatically drafts email reminders in Google Sheets for tasks not marked 'Complete.' Automate your workflow with little to no technical expertise, freeing up time for more important work and eliminating manual follow-ups.
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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine. 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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Ukończ szkolenie wprowadzające Przygotowywanie danych do użycia z interfejsami ML w Google Cloud, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: czyszczenie danych przy użyciu usługi Dataprep firmy Trifacta, uruchamianie potoków danych w Dataflow, tworzenie klastrów i uruchamianie zadań Apache Spark w Managed Service for Apache Spark, a także wywoływanie interfejsów API dotyczących uczenia maszynowego, w tym Cloud Natural Language API, Google Cloud Speech-to-Text API oraz Video Intelligence API.
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This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.
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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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In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Agent Runtime on Gemini Enterprise Agent Platform to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Runtime.
Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.
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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 apps. Explore other content in the Gemini Agent Ready (GEAR) program.
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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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