Vendeta Vendeta
Учасник із 2026
Золота ліга
Кількість балів: 8749
European University Challenge June 2026
Earned черв. 28, 2026 EDT
Deploy Multi-Agent Architectures
Earned черв. 27, 2026 EDT
Migrating MySQL data to Cloud SQL using Database Migration Service
Earned черв. 27, 2026 EDT
AI Boost Bites: Prompting like a Pro with Google Workspace
Earned черв. 7, 2026 EDT
[DEPRECATED] AI Boost Bites: Intro to NotebookLM
Earned черв. 7, 2026 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack
Earned черв. 7, 2026 EDT
AI Boost Bites: Tame Your Inbox with AI
Earned черв. 7, 2026 EDT
[DEPRECATED] AI Boost Bites: AI Power-Ups for Google Workspace
Earned черв. 7, 2026 EDT
AI Boost Bites: Your Personal Feedback Agent
Earned черв. 7, 2026 EDT
Google DeepMind: Train A Small Language Model
Earned черв. 1, 2026 EDT
Google DeepMind: 03 Design And Train Neural Networks
Earned черв. 1, 2026 EDT
Google DeepMind: 02 Represent Your Language Data
Earned черв. 1, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model
Earned черв. 1, 2026 EDT
Orchestrate Multi-agent Workflows with Gemini Enterprise
Earned трав. 29, 2026 EDT
Human-Centered AI
Earned трав. 29, 2026 EDT
Gen AI Agents: Transform Your Organization
Earned трав. 29, 2026 EDT
Create Your First Gemini Enterprise Application
Earned трав. 28, 2026 EDT
Enterprise Agents and Use Cases
Earned трав. 28, 2026 EDT
Agent Fundamentals
Earned трав. 28, 2026 EDT
Introduction to AI Agents
Earned трав. 28, 2026 EDT
Manage Agent Memory and State
Earned трав. 27, 2026 EDT
Add Agent Capabilities With Tools
Earned трав. 26, 2026 EDT
Optimize Agent Behavior
Earned трав. 26, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK)
Earned трав. 26, 2026 EDT
Build Agents with Agent Development Kit (ADK)
Earned трав. 26, 2026 EDT
Deploy Your First Agent
Earned трав. 25, 2026 EDT
Build and Deploy Agents in Production
Earned трав. 25, 2026 EDT
European University Challenge May 2026
Earned трав. 25, 2026 EDT
European University Challenge April 2026
Earned квіт. 22, 2026 EDT
This month, you’ll master advanced data management, infrastructure security, and cross-platform app development. Dive into HashiCorp Vault to secure infrastructure secrets, scale global data with Cloud Spanner, and build responsive front-ends using Flutter. Top it off by setting up robust monitoring using Prometheus on Google Cloud. Ready to engineer at scale?
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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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This course offers hands-on practice with migrating MySQL data to Cloud SQL using Database Migration Service. You start with an introductory lab that briefly reviews how to get started with Cloud SQL for MySQL, including how to connect to Cloud SQL instances using the Cloud Console. Then, you continue with two labs focused on migrating MySQL databases to Cloud SQL using different job types and connectivity options available in Database Migration Service. The course ends with a lab on migrating MySQL user data when running Database Migration Service jobs.
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This video covers prompt engineering fundamentals for effective AI communication. Learn a simple framework (Persona, Task, Context, Format) to craft clear prompts, getting better, faster results from Gemini in Google Workspace. Discover how to use natural language, be specific, and iterate for optimal AI assistance.
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This video covers how to use NotebookLM as a personal research
assistant by adding sources, asking questions, and generating new content
formats based on your documents.
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This video covers how to eliminate tedious manual data entry using Gemini. Learn how to take a picture or screenshot of data (from PDFs, paper, or images) and prompt Gemini to instantly convert it into a structured Google Sheet. Discover this simple hack to save countless hours transcribing data, turning Gemini into your personal data entry assistant. Just snap, prompt, and export!
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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 five key ways to use Google's AI tools, including Gemini in Workspace, the Gemini app, and NotebookLM, to enhance your daily productivity.
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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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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 focus on the training process for machine learning models. You will learn how to spot and mitigate issues when training a model, such as overfitting and underfitting. In practical coding labs, you will implement and evaluate the multilayer perceptron for simple classification tasks. This will provide insights into the mechanics of training a neural network model and the backpropagation algorithm. Research case studies will demonstrate how neural networks power real-world models. Additionally, you will consider the broader social impacts of innovation by looking beyond immediate benefits to anticipate potential risks, safety concerns, and further-reaching societal consequences.
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In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.
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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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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.
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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.
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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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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.
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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.
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Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.
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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.
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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.
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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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Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems. 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 Vertex AI Agent Engine and Cloud Run, with optional cross-session memory via Memory Bank. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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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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This month, you’ll dive into Cloud ML APIs to analyze images and classify text while managing data security with Bucket Lock. From monitoring metrics with Prometheus to commanding the Cloud Shell, you’ll leverage essential APIs and tools to build a smarter, more secure cloud environment. Ready to scale?
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Ready to master the future of intelligence? This Google Skills game challenges you to monitor projects, create alerts, and create, deploy, and test a Cloud Run function using Google Cloud console!
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