Fiizyk MJ
Member since 2023
Diamond League
127385 points
Plan Your Cloud Next Generation Firewall Needs
Earned сент. 22, 2026 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned сент. 16, 2026 EDT
Google Cloud Computing Foundations: Networking & Security in Google Cloud
Earned сент. 16, 2026 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud
Earned сент. 16, 2026 EDT
Prepare Data for ML APIs on Google Cloud
Earned сент. 16, 2026 EDT
Build a Secure Google Cloud Network
Earned сент. 16, 2026 EDT
Monitor and Log with Google Cloud Observability
Earned сент. 9, 2026 EDT
Build Infrastructure with Terraform on Google Cloud
Earned сент. 9, 2026 EDT
Monitor Environments with Google Cloud Managed Service for Prometheus
Earned сент. 8, 2026 EDT
Troubleshooting with AI Using Cloud Assist Investigations
Earned сент. 8, 2026 EDT
Observability in Google Cloud
Earned сент. 7, 2026 EDT
Gemini in Google Workspace Studio
Earned сент. 7, 2026 EDT
Enterprise Agents and Use Cases
Earned сент. 3, 2026 EDT
Create Your First Gemini Enterprise Application
Earned сент. 3, 2026 EDT
Gemini in Google Vids
Earned сент. 3, 2026 EDT
Agent Fundamentals
Earned сент. 3, 2026 EDT
Introduction to AI Agents
Earned сент. 3, 2026 EDT
Introduction to the Gemini App
Earned сент. 3, 2026 EDT
Deploy and Scale AI Models with Cloud Run
Earned сент. 3, 2026 EDT
Orchestrate Workflows with the Data Agent Kit
Earned авг. 28, 2026 EDT
Add Agent Capabilities With Tools
Earned авг. 28, 2026 EDT
Agentic Strategy: Discover, Design, and Prototype
Earned авг. 28, 2026 EDT
Optimize Agent Behavior
Earned авг. 27, 2026 EDT
Build Agent Skills with Google
Earned авг. 26, 2026 EDT
Manage Agent Memory and State
Earned авг. 26, 2026 EDT
Liftoff with Google Antigravity: Build a Video Game with AI
Earned авг. 26, 2026 EDT
Introduction to Security Principles in Cloud Computing
Earned авг. 19, 2026 EDT
Create ML Models with BigQuery ML
Earned июля 10, 2026 EDT
Serverless Data Processing with Dataflow: Operations
Earned июля 10, 2026 EDT
Security Command Center: Vulnerabilities and Misconfigurations
Earned июля 10, 2026 EDT
Google Threat Intelligence
Earned июля 10, 2026 EDT
Introduction to Google Security Operations (SIEM)
Earned июля 10, 2026 EDT
Build a Certification Study Guide: PSOE Exam Prep
Earned июля 9, 2026 EDT
Security Command Center: Identify and Prioritize Risks
Earned июля 9, 2026 EDT
Google Workspace Troubleshooting
Earned июля 9, 2026 EDT
Machine Learning Operations (MLOps): Getting Started
Earned июля 9, 2026 EDT
Build a Certification Study Guide: ACE Exam Prep
Earned июня 24, 2026 EDT
Serverless Data Processing with Dataflow: Develop Pipelines
Earned июня 3, 2026 EDT
Model Armor: Securing AI Deployments
Earned дек. 19, 2025 EST
Introduction to Security in the World of AI
Earned дек. 19, 2025 EST
Introduction Google Security Operations (SOAR)
Earned дек. 18, 2025 EST
Google Security Operations - SOAR Analyst
Earned дек. 17, 2025 EST
[DEPRECATED] Google Security Operations - SOAR Developer
Earned дек. 16, 2025 EST
Introduction to Data Analytics in Google Cloud
Earned дек. 16, 2025 EST
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned дек. 16, 2025 EST
AI Boost Bites: Create Your Own Retro Arcade Game
Earned дек. 11, 2025 EST
AI Boost Bites: Become a "Vibe DJ"
Earned дек. 11, 2025 EST
AI Boost Bites: Create Your Ultimate College Scouting Report
Earned дек. 11, 2025 EST
AI Boost Bites: One-Click Campaign Visuals
Earned дек. 11, 2025 EST
AI Boost Bites: From Napkin Sketch to Functional App
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: NotebookLM Reports
Earned дек. 11, 2025 EST
AI Boost Bites: Your Personal Feedback Agent
Earned дек. 11, 2025 EST
AI Boost Bites: Presentation Scripts with Gemini
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: Project Notebooks
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: NotebookLM for Market Research
Earned дек. 11, 2025 EST
[Deprecated]AI Boost Bites: NotebookLM Video Overviews
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: Discover Sources in NotebookLM
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: NotebookLM Mind Maps
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: Intro to NotebookLM
Earned дек. 11, 2025 EST
AI Boost Bites: Email Content Creation
Earned дек. 11, 2025 EST
AI Boost Bites: Create Docs in Seconds
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: AI Power-Ups for Google Workspace
Earned дек. 11, 2025 EST
AI Boost Bites: Tame Your Inbox with AI
Earned дек. 11, 2025 EST
AI Boost Bites: Gemini Slide Summaries
Earned дек. 11, 2025 EST
AI Boost Bites: Automate tasks with Gemini and Apps Script
Earned дек. 11, 2025 EST
AI Boost Bites: Poke Holes in Your Strategy
Earned дек. 11, 2025 EST
AI Boost Bites: Personalization with customized prompts
Earned дек. 11, 2025 EST
AI Boost Bites: Prompting like a Pro with Google Workspace
Earned дек. 11, 2025 EST
AI Boost Bites: Content Generation with Gemini Made Easy
Earned дек. 11, 2025 EST
[DEPRECATED] AI Boost Bites: NotebookLM for Competitive Edge
Earned июня 16, 2025 EDT
AI Boost Bites: Gemini Image-to-Sheets Hack
Earned июня 16, 2025 EDT
[DEPRECATED] AI Boost Bites: "Eat the Frog" with NotebookLM
Earned июня 16, 2025 EDT
AI Boost Bites: No-Code Sheets & Scripts
Earned июня 16, 2025 EDT
AI Boost Bites: Exec Summaries with Gemini Gems
Earned июня 16, 2025 EDT
AI Boost Bites: TL;DR with Gemini in Docs & Drive
Earned июня 16, 2025 EDT
AI Boost Bites: Amplify Exec Voices with AI
Earned июня 16, 2025 EDT
[DEPRECATED] AI Boost Bites: Customer insights with NotebookLM
Earned июня 16, 2025 EDT
AI Boost Bites: Gemini Gems – Your ultimate marketing sidekick
Earned июня 16, 2025 EDT
Security Command Center Fundamentals
Earned июня 16, 2025 EDT
Work with Gemini Models in BigQuery
Earned июня 12, 2025 EDT
Gen AI Agents: Transform Your Organization
Earned апр. 14, 2025 EDT
Gen AI Apps: Transform Your Work
Earned апр. 14, 2025 EDT
Gen AI: Navigate the Landscape
Earned апр. 14, 2025 EDT
Gen AI: Unlock Foundational Concepts
Earned апр. 14, 2025 EDT
Gen AI: Beyond the Chatbot
Earned апр. 14, 2025 EDT
Create Embeddings, Vector Search, and RAG with BigQuery
Earned марта 11, 2025 EDT
Build a Certification Study Guide: PMLE
Earned янв. 7, 2025 EST
Responsible AI for Developers: Privacy & Safety
Earned янв. 7, 2025 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned янв. 3, 2025 EST
[DEPRECATED] Agent Summarization (Custom)
Earned дек. 4, 2024 EST
Introduction to Security in the World of AI
Earned дек. 3, 2024 EST
Conversational AI on Vertex AI and Dialogflow CX
Earned нояб. 15, 2024 EST
[DEPRECATED] Gemini for end-to-end SDLC
Earned окт. 31, 2024 EDT
[DEPRECATED] Gemini for Network Engineers
Earned окт. 31, 2024 EDT
[DEPRECATED] Gemini for DevOps Engineers
Earned окт. 31, 2024 EDT
Build a Certification Study Guide: PCSE Exam Prep
Earned сент. 26, 2024 EDT
[DEPRECATED] Gemini for Security Engineers
Earned сент. 26, 2024 EDT
Build a Certification Study Guide: PCA Exam Prep
Earned сент. 21, 2024 EDT
Google Security Operations - Deep Dive
Earned сент. 20, 2024 EDT
[Deprecated]Google Security Operations - Fundamentals
Earned сент. 19, 2024 EDT
[DEPRECATED] Gemini for Cloud Architects
Earned сент. 19, 2024 EDT
Serverless Data Processing with Dataflow: Foundations
Earned сент. 19, 2024 EDT
Gemini in Google Drive
Earned сент. 17, 2024 EDT
Gemini in Google Slides
Earned сент. 17, 2024 EDT
Gemini in Google Meet
Earned сент. 17, 2024 EDT
Gemini in Google Sheets
Earned сент. 17, 2024 EDT
Gemini in Google Docs
Earned сент. 17, 2024 EDT
Gemini in Gmail
Earned сент. 17, 2024 EDT
Google Workspace with Gemini: Foundations of Your AI Workflow
Earned сент. 17, 2024 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned сент. 16, 2024 EDT
Machine Learning Operations (MLOps) with Agent Platform: Model Evaluation
Earned сент. 16, 2024 EDT
Vector Search and Embeddings
Earned сент. 12, 2024 EDT
Responsible AI for Developers: Fairness & Bias
Earned сент. 11, 2024 EDT
Transformer Models and BERT Model
Earned сент. 11, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned сент. 11, 2024 EDT
Introduction to Vertex AI Studio
Earned сент. 11, 2024 EDT
Create Image Captioning Models
Earned сент. 11, 2024 EDT
Encoder-Decoder Architecture
Earned сент. 11, 2024 EDT
Attention Mechanism
Earned сент. 11, 2024 EDT
Introduction to Image Generation
Earned сент. 11, 2024 EDT
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned сент. 11, 2024 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals
Earned сент. 8, 2024 EDT
Introduction to Data Analytics in Google Cloud
Earned сент. 8, 2024 EDT
Change Management for Google Workspace
Earned сент. 5, 2024 EDT
Google Workspace Data Governance
Earned сент. 3, 2024 EDT
Google Workspace Security
Earned сент. 2, 2024 EDT
Prompt Design in Agent Platform
Earned авг. 21, 2024 EDT
Google Workspace Core Services
Earned авг. 20, 2024 EDT
Google Workspace User and Resource Management
Earned авг. 20, 2024 EDT
DEPRECATED Planning for a Google Workspace Deployment
Earned марта 28, 2024 EDT
Preparing for Your Google Workspace Administrator Journey
Earned марта 28, 2024 EDT
API Design and Fundamentals with the Apigee API Platform
Earned февр. 6, 2024 EST
Set Up an App Dev Environment on Google Cloud
Earned февр. 5, 2024 EST
Managing Cloud Infrastructure with Terraform
Earned февр. 1, 2024 EST
Build Data Lakes and Data Warehouses on Google Cloud
Earned февр. 1, 2024 EST
Getting Started With Application Development
Earned янв. 31, 2024 EST
Build a Certification Study Guide: PDE Exam Prep
Earned янв. 29, 2024 EST
Google Cloud Architecture: Design Principles
Earned янв. 28, 2024 EST
Getting Started with Terraform for Google Cloud
Earned янв. 28, 2024 EST
Trust and Security with Google Cloud
Earned янв. 25, 2024 EST
Scaling with Google Cloud Operations
Earned янв. 25, 2024 EST
Modernize Infrastructure and Applications with Google Cloud
Earned янв. 25, 2024 EST
Innovating with Google Cloud Artificial Intelligence
Earned янв. 24, 2024 EST
Exploring Data Transformation with Google Cloud
Earned янв. 24, 2024 EST
Optimize Your Google Cloud Costs
Earned янв. 24, 2024 EST
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned янв. 23, 2024 EST
Digital Transformation with Google Cloud
Earned янв. 22, 2024 EST
Developing a Google SRE Culture
Earned янв. 22, 2024 EST
Google Cloud Fundamentals: Core Infrastructure
Earned янв. 22, 2024 EST
Enterprise Search on Generative AI App Builder
Earned янв. 18, 2024 EST
Introduction to AI and Machine Learning on Google Cloud
Earned окт. 20, 2023 EDT
Google Cloud Data Analytics Essentials
Earned окт. 11, 2023 EDT
Responsible AI: Applying AI Principles with Google Cloud
Earned авг. 31, 2023 EDT
Generative AI Fundamentals
Earned авг. 30, 2023 EDT
Introduction to Large Language Models
Earned авг. 28, 2023 EDT
Introduction to Generative AI
Earned авг. 28, 2023 EDT
[DEPRECATED]Introduction to Responsible AI
Earned авг. 28, 2023 EDT
Identify critical assets and their compliance requirements.
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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This third course covers cloud automation and management tools and building secure networks.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.
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Earn a skill badge by completing the Build a Secure Google Cloud Network skill badge course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud.
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Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.
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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.
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Earn a skill badge by completing the Monitor Environments with Google Cloud Managed Service for Prometheus skill badge course, where you learn Kubernetes Monitoring with Google Cloud Managed Service for Prometheus.
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Gemini Cloud Assist investigations is an AI-enabled tool for iterative troubleshooting in Google Cloud environments, and aims to help users troubleshoot common issues to find the root cause of problems that may occur when using Google Cloud services.
This course equips DevOps, SRE, and platform engineers with the skills to effectively use Gemini Cloud Assist investigations for streamlined troubleshooting of Google Cloud services. The training focuses on foundational knowledge of Gemini Cloud Assist investigations, with the intent to reduce troubleshooting time and enhance overall operational efficiency for users of Google Cloud.
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Welcome to Observability in Google Cloud, the second part of a two-part course series. It is suggested that you complete part 1, Logging and Monitoring in Google Cloud, prior to taking this course.
This course is all about application performance management tools, including Error Reporting, Cloud Trace, and Cloud Profiler.
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This course aims to empower Google Workspace users to efficiently automate cross-application tasks, significantly boosting productivity and streamlining daily operations. Learners will gain practical skills in designing and configuring automations as well as customizing steps in Google Workspace Studio.
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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 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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This course introduces Google Vids, an AI-powered creation tool in Google Workspace that helps you turn raw documents into professional, engaging videos without prior editing experience. You will learn how to quickly generate drafts using templates and automated tools, as well as how to customize your content with transcript-based editing, dynamic visual enhancements, and custom music. Finally, you will explore how to integrate AI avatars and voiceovers to seamlessly narrate your presentations across various business use cases.
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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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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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This training aims to empower Google Workspace users to seamlessly integrate the Gemini app, securely accessing their data to unlock new levels of productivity. Learners will learn how to leverage Gemini's capabilities to enhance creativity and accelerate problem-solving for complex business challenges.
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AI inference is the process of using a trained machine learning model to make predictions on new, unseen data by applying learned patterns. This course is designed for developers, data scientists, and ML engineers interested in quickly deploying AI inference services on Cloud Run. It is useful for those familiar with cloud-based serverless application deployment solutions, but who may not have experience with running AI inference using Google Cloud serverless products.
The course includes examples that deploys a model for AI inference with GPUs and integrates gen AI apps with data storage services.
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This course brings AI-driven, natural-language data engineering into the IDE and CLI workflows you already use. Built on the Agent Development Kit (ADK), the Data Agent Kit connects to a wide array of Google Cloud services, including BigQuery, Spanner, BigLake, Dataproc, and Managed Airflow. By using it, you can collapse days of pipeline scaffolding, data build tool (dbt) authoring, and orchestration wiring into prompt-driven sessions.
As an intermediate-to-advanced practitioner, you will learn to build a data agent with the Agent Development Kit (ADK). You'll wire up the Model Context Protocol (MCP) layer, and use your agent to explore catalogs, transform data, train models, and orchestrate scheduled pipelines on Google Cloud.
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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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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 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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Close the gap between general AI capabilities and your domain knowledge through Agent Skills. This course walks you through the full lifecycle of custom skill building, from local scaffolding and testing to enterprise scaling and sharing using Google's agent ecosystem, including Google Antigravity, ADK, and Skill Registry. Additionally, you use Google Agents CLI toolkit to attach skills to standalone 24/7 cloud agents, equipping your team with reliable, autonomous digital coworkers.
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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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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 is the first of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts. You’ll identify common tools used by entry-level cloud security analysts to automate tasks.
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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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In the last installment of the Dataflow course series, we will introduce the components of the Dataflow operational model. We will examine tools and techniques for troubleshooting and optimizing pipeline performance. We will then review testing, deployment, and reliability best practices for Dataflow pipelines. We will conclude with a review of Templates, which makes it easy to scale Dataflow pipelines to organizations with hundreds of users. These lessons will help ensure that your data platform is stable and resilient to unanticipated circumstances.
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Learn how to use Security Command Center (SCC) to triage vulnerabilities and misconfigurations identified by platform security detectors.
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Google Threat Intelligence provides unmatched visibility into threats by delivering detailed and timely threat intelligence to security teams around the world. This course covers the various capabilities of Google Threat Intelligence and common ways that organizations use this product to proactively mitigate threats.
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This course provides a comprehensive, end-to-end exploration of Google SecOps SIEM, guiding learners from foundational concepts to advanced investigation and detection engineering. Participants will gain hands-on experience with data ingestion, normalization, RBAC configuration, searching, and dashboarding using both legacy and native capabilities. Through structured modules, demos, and curated examples, the course emphasizes real-world investigation workflows, UDM-based analytics, and YARA-L rule development. By the end of the course, learners will be equipped to operationalize SIEM effectively within their environment and build scalable processes for detection, investigation, and reporting.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Security Operations Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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In the context of a real-world use case, learn how to use Security Command Center’s virtual red teaming feature to identify risks. Then, learn how attack exposure scores help you prioritize issues and how risk reports keep stakeholders in the loop.
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This course was designed to prepare Google Workspace Administrators to troubleshoot common Google Workspace issues. Learners will practice diagnosing and resolving problems in Gmail, Calendar, and Drive, and navigating the Admin console. They will also experience analyzing audit logs to troubleshoot security issues, and gathering information and using available resources to troubleshoot and report technical issues.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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Learn how to use Gemini Notebook to create a personalized study guide for the Associate Cloud Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook , and learn how to use a study guide to practice for a certification exam.
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In this second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.
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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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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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This course introduces the SOAR component of Google SecOps, guiding learners through setup, response automation, and reporting. With demos, hands-on examples, and quizzes, participants will learn how to simplify investigations and make day-to-day security operations more efficient. The course is designed around short videos, averaging about five minutes each, divided into granular topics to support different learning styles and fit into the time learners have available.
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This course helps you understand how to use Chronicle to properly handle security incidents.
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This course helps developers customize Chronicle and augment its abilities with third party integrations.
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Welcome learner! This is the first of five courses of the Google Cloud Data Analytics Certificate. Jump into the world of data analytics and cloud computing. Explore the data lifecycle in the cloud and gain a better understanding of the common tools used by data analysts.
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You made it! This is the fifth and final course of the Google Cloud Data Analytics Certificate. There’s no time like the present to start preparing for your job as a Cloud Data Analyst. Let's polish up that resume and refine those interview skills to allow you to show up with confidence for your interview!
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This video covers how to use a simple prompt in Gemini Canvas to build, customize, and share your own playable game, like Tic-Tac-Toe.
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In this video, you'll learn to build a working music synthesizer using a simple text prompt in Gemini Canvas. You'll see how to specify controls like waveform, attack, and sustain, and then interact with the generated instrument to create and experiment with your own unique sounds.
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This video covers how to use Gemini Deep Research with creative prompts to turn complex information into a fun, personalized analysis, like a sports scouting report and bracket.
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In this video, you'll learn to use the Create menu in Gemini Canvas to instantly convert a block of text into a variety of visual formats. You’ll see how to take a brainstormed marketing campaign and turn it into both a shareable infographic and an internal webpage with just one click.
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This video covers how to use Gemini Canvas to transform a simple drawing of an app into a functional prototype using a technique called "vibe coding."
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This video covers how NotebookLM's Reports feature dynamically suggests formats to help you create customized, trustworthy analyses of your documents with ease.
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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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This video covers how to use Gemini Advanced to research a topic, create a presentation outline, and then use Gemini in Google Docs to generate talking points.
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This video covers how to create a 'project notebook' in NotebookLM by adding all relevant sources to build a central, searchable knowledge hub for your team.
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This video covers how to use NotebookLM for common marketing tasks like
analyzing customer feedback, conducting market research, and generating
content ideas.
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This video covers how to use the Video Overviews feature in NotebookLM to automatically generate a short explainer video based on your source documents.
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This video covers how to use the 'Discover Sources' feature in NotebookLM to find and import relevant web-based sources directly into your research project.
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This video covers how to use the Mind Maps feature in NotebookLM to automatically create a visual representation of your sources, helping you understand connections and key concepts.
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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 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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This video covers how to use the 'Help me create' feature in Google Docs to generate a complete, formatted document by referencing content from other files in your Drive.
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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 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 Slides to automatically generate
meeting recaps and draft follow-up emails, which can streamline your
post-meeting workflow and save you time.
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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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This video covers using AI to identify weaknesses and hidden assumptions in your strategy. You'll learn the "Poke Holes" method, a simple way to pressure-test your plans with AI prompts, uncovering gaps and strengthening your strategic thinking.
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This video covers how to personalize your Gemini results in Google
Workspace. Learn to incorporate documents and research papers directly
into your prompts using the "@" symbol to get more targeted and relevant
AI output tailored to your needs.
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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 will cover how you can leverage Gemini's advanced AI capabilities in Google Docs to brainstorm ideas, draft various marketing content, and collaborate with your team.
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This video will cover how to use NotebookLM to gather and analyze
publicly available information, combine it with internal documents, and
extract key competitive insights.
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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 you can leverage Notebook LM to "eat the frog" on your to-do list by automating complex tasks like summarizing legislation and mapping services, saving you hours of work.
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This video covers how you can leverage Gemini's advanced AI capabilities within Google Sheets to effortlessly pull data and generate insights in minutes, all without the need for any technical or coding background.
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This video covers how you can create your own Brevity Gem to summarize and transform messy notes or long documents into clear, concise, executive-ready summaries.
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This video covers how you can use Gemini to summarize long documents in Google Workspace, so you can quickly get the information you need and save time. You'll learn how to use Gemini to summarize entire documents or just selected text, as well as how to use Gemini in Drive to summarize across multiple files.
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This video will cover how to leverage Gemini Gems to create authentic
social media posts in your leader's unique voice. Learn to overcome the
challenge of scaling executive social presence by training a Gem with
writing samples and clear instructions. Discover how to generate engaging
posts quickly, saving time while amplifying thought leadership and
ensuring authenticity.
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This video covers how NotebookLM can revolutionize customer insight gathering from call or chat transcripts. You'll learn to upload PDF transcripts of hundreds of conversations (even multilingual ones!) and quickly extract key themes, trending topics, and actionable insights without listening for hours. Discover how to save findings, share notebooks, and even generate interactive podcast summaries of your data.
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This video covers how to create your own Gemini Gems, advanced AI capabilities that can automate repetitive tasks and supercharge your productivity.
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Learn about the fundamental features of Security Command Center on Google Cloud. Spend time in this course to understand assets, detection and compliance. Security Command Center is a key part of your Google Cloud security journey, complete these modules and quiz to earn a completion badge.
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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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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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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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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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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 introduces important topics of AI privacy and safety. It explores practical methods and tools to implement AI privacy and safety recommended practices through the use of Google Cloud products and open-source tools.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.
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In this course you will learn how Contact Center AI Agent Assist can help distill complex customer interactions into concise and clear summaries.
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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 will learn how to use the new generative AI features in Dialogflow CX to create virtual agents that can have more natural and engaging conversations with customers. Discover how to deploy generative fallback responses to gracefully handle errors and omissions in customer conversations, deploy generators to increase intent coverage, and structure, ingest, and manage data in a data store. And explore how to deploy and maintain generative AI agents using your data, and deploy and maintain hybrid agents in combination with existing intent-based design paradigms.
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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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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps network engineers create, update, and maintain VPC networks. You learn how to prompt Gemini to provide specific guidance for your networking tasks, beyond what you would receive from a search engine. Using a hands-on lab, you experience how Gemini makes it easier for you to work with Google Cloud VPC networks.
Duet AI was renamed to Gemini, our next-generation model.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps engineers manage infrastructure. You learn how to prompt Gemini to find and understand application logs, create a GKE cluster, and investigate how to create a build environment. Using a hands-on lab, you experience how Gemini improves the DevOps workflow.
Duet AI was renamed to Gemini, our next-generation model.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Security Engineer certification exam. You'll review Gemini Notebook features, create a notebook, and learn how to use a study guide to practice for the certification exam.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps you secure your cloud environment and resources. You learn how to deploy example workloads into an environment in Google Cloud, identify security misconfigurations with Gemini, and remediate security misconfigurations with Gemini. Using a hands-on lab, you experience how Gemini improves your cloud security posture.
Duet AI was renamed to Gemini, our next-generation model.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Cloud Architect certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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Take these next steps to learn more about the Google Security Operations Platform. Build on fundamental knowledge to go deeper on customization and tuning.
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This course covers the baseline skills needed for the Google Security Operations Platform. The modules will cover specific actions and features that security engineers should become familiar with to start using the toolset.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps administrators provision infrastructure. You learn how to prompt Gemini to explain infrastructure, deploy GKE clusters and update existing infrastructure. Using a hands-on lab, you experience how Gemini improves the GKE deployment workflow.
Duet AI was renamed to Gemini, our next-generation model.
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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This course covers how to use Gemini in Google Drive to manage and retrieve files. Learn to locate assets using natural language, extract specific facts via AI Overviews without opening files, instantly summarize multiple media formats, and save file collections as Projects for repeatable research. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This course covers how to use Gemini in Google Slides to transform concepts into visually compelling presentations. Learn to generate structured decks from a single prompt or existing source document, refine slide layouts using automated design enhancement, create custom vector graphics and photos, and dynamically craft on-slide copy alongside precise speaker notes.
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This course covers how to use Gemini in Google Meet to enhance video collaboration. Learn to automate note-taking, utilize real-time text and speech translation, privately catch up on missed discussions, and instantly optimize your audio and video quality. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This course covers how to use Gemini in Google Sheets to automate data organization and crunch complex numbers. Learn to structure tables from raw text, auto-populate data using natural language, generate native spreadsheet formulas on demand, and rapidly extract high-level insights or visualizations without needing advanced spreadsheet expertise. Explore other content in the Gemini Agent Ready (GEAR) program.
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This course covers how to use Gemini in Google Docs to streamline your writing and content creation. Learn to draft documents from scratch, refine writing tone and clarity with interactive tools, summarize complex files, and seamlessly transform long-form text into structured assets for other Google Workspace applications. Explore other content in the Gemini Enterprise Agent Ready (GEAR) program.
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This course covers how to use Gemini in Gmail to optimize your email management. Learn to summarize lengthy threads, retrieve information using natural language, draft professional responses, and organize communication strategies directly inside your inbox. Explore other content in the Gemini Agent Ready (GEAR) program.
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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. Here, you will learn about the key features of Gemini and how they can be used to improve productivity and efficiency. Continue building your skills in the full Google Workspace with Gemini learning path, and explore other content in the Gemini Agent Ready (GEAR) program.
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This course introduces concepts of AI interpretability and transparency. It discusses the importance of AI transparency for developers and engineers. It explores practical methods and tools to help achieve interpretability and transparency in both data and AI models.
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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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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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This course introduces concepts of responsible AI and AI principles. It covers techniques to practically identify fairness and bias and mitigate bias in AI/ML practices. It explores practical methods and tools to implement Responsible AI best practices using Google Cloud products and open source tools.
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This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.This course is estimated to take approximately 45 minutes to complete.
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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 introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.
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This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model. By the end of this course, you will be able to create your own image captioning models and use them to generate captions for images
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This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering. You learn about the main components of the encoder-decoder architecture and how to train and serve these models. In the corresponding lab walkthrough, you’ll code in TensorFlow a simple implementation of the encoder-decoder architecture for poetry generation from the beginning.
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This course will introduce you to the attention mechanism, a powerful technique that allows neural networks to focus on specific parts of an input sequence. You will learn how attention works, and how it can be used to improve the performance of a variety of machine learning tasks, including machine translation, text summarization, and question answering. This course is estimated to take approximately 45 minutes to complete.
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This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Gemini Enterprise Agent Platform.
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This is the fifth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll combine and apply the foundational knowledge and skills from courses 1-4 in a hands-on Capstone project that focuses on the full data lifecycle project. You’ll practice using cloud-based tools to acquire, store, process, analyze, visualize, and communicate data insights effectively. By the end of the course, you’ll have completed a project demonstrating their proficiency in effectively structuring data from multiple sources, presenting solutions to varied stakeholders, and visualizing data insights using cloud-based software. You’ll also update your resume and practice interview techniques to help prepare for applying and interviewing for jobs.
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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in.
By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills.
The courses should be completed in the following order:
1. Google Cloud Computing Foundations: Cloud Computing Fundamentals
2. Google Cloud Computing Foundations: Infrastructure in Google Cloud
3. Google Cloud Computing Foundations: Networking and Security in Google Cloud
4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.
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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.
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This course is for deployment personnel of Google Cloud and its partner organizations who are tasked with managing cultural change and skill gaps of customers adopting Google Workspace, engaging sponsors and enlisting the support of customer stakeholders, communicating the anticipated changes to the customer and their users. It will guide you through the Workspace change management methodology and all phases of the customer journey.
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This course equips learners with skills to govern data within their Google Workspace environment. Learners will explore data loss prevention rules in Gmail and Drive to prevent data leakage. They will then learn how to use Google Vault for data retention, preservation, and retrieval purposes. Next, they will learn how to configure data regions and export settings to align with regulations. Finally, learners will discover how to classify data using labels for enhanced organization and security.
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This course empowers learners to secure their Google Workspace environment. Learners will implement strong password policies and two-step verification to govern user access. They will then utilize the security investigation tool to proactively identify and respond to security risks. Next, they will manage third-party app access and mobile devices to ensure security. Finally, learners will enforce email security and compliance measures to protect organizational data.
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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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This course was designed to give learners a comprehensive understanding of Google Workspace core services. Learners will explore enabling, disabling, and configuring settings for these services, including Gmail, Calendar, Drive, Meet, Chat, and Docs. Next, they'll learn how to deploy and manage Gemini to empower their users. Finally, learners will examine use cases for AppSheet and Apps Script to automate tasks and extend the functionality of Google Workspace applications.
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This course was designed to provide an understanding of user and resource management in Google Workspace. Learners will explore the configuration of organizational units to align with their organization's needs. Additionally, learners will discover how to manage various types of Google Groups. They will also develop expertise in managing domain settings within Google Workspace. Finally, learners will master the optimization and structuring of resources within their Google Workspace environment.
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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series.
In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area.
You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training.
This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.
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This course helps learners prepare to study for the Professional Google Workspace Administrator Certification exam. Learners will be exposed to and engage with exam topics through a series of readings, diagnostic questions, and knowledge checks. After completing this course, learners will have a personalized workbook that will guide them through the rest of their certification readiness journey.
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In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API lifecycle, and how the Apigee API platform helps you manage all aspects of the lifecycle. You learn how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers.
Through a combination of lessons, hands-on labs, and supplemental materials, you will learn how to design, build, secure, deploy, and manage API solutions using Google Cloud's Apigee API Platform. This is the first course of the Developing APIs with the Apigee API Platform series. After completing this course, enroll in the API Security with the Apigee API Platform course.
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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.
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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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In this course, application developers learn how to design and develop cloud-native applications that seamlessly integrate managed services from Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants learn how to apply best practices for application development and use the appropriate Google Cloud storage services for object storage, relational data, caching, and analytics.
Completing one version of each lab is required. Each lab is available in Node.js. In most cases, the same labs are also provided in Python or Java. You may complete each lab in whichever language you prefer.
This is the first course of the Developing Applications with Google Cloud series. After completing this course, enroll in the Securing and Integrating Components of your Application course.
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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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In this course, you’ll learn how to apply the Google Cloud Well-Architected Framework to design resilient, production-grade cloud environments. You’ll analyze real-world challenges across six distinct industries to balance competing priorities like low-latency performance, ironclad security, and carbon efficiency. By the end, you'll possess a practical architectural playbook and the critical thinking skills needed to lead reviews and optimize cloud workloads in the field.
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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure.
Learners will get hands-on practice building and managing Google Cloud resources using Terraform.
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As organizations move their data and applications to the cloud, they must address a rapidly evolving landscape of security challenges. This course explores the foundations of cloud security, the value of Google Cloud’s secure-by-design infrastructure, and the defense-in-depth strategy, while highlighting how AI-driven operations and compliance tools help organizations meet strict global regulatory requirements.
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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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. This course explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
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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Many traditional enterprises use legacy systems and apps that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems and investing in new products and services. This course explores these challenges and offers solutions to overcome them by using cloud technology.
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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Artificial intelligence (AI) and machine learning (ML) represent an important evolution in information technologies that are quickly transforming a wide range of industries. Innovating with Google Cloud Artificial Intelligence explores how organizations can use AI and ML to transform their business processes.
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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This is the second Quest in a two-part series on Google Cloud billing and cost management essentials. This Quest is most suitable for those in a Finance and/or IT related role responsible for optimizing their organization’s cloud infrastructure. Here you'll learn several ways to control and optimize your Google Cloud costs, including setting up budgets and alerts, managing quota limits, and taking advantage of committed use discounts. In the hands-on labs, you’ll practice using various tools to control and optimize your Google Cloud costs or to influence your technology teams to apply the cost optimization best practices.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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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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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.
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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
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Enterprises of all sizes have trouble making their information readily accessible to employees and customers alike. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites often offer a vast selection of products, services, and information, but customers are frustrated by ineffective site search and navigation capabilities.
This course teaches you to use Generative AI App Builder to integrate enterprise-grade generative AI search.
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This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.
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Discover how to turn raw numbers into clear, data-driven decisions on Google Cloud. Through hands-on labs and practical real-world scenarios, this beginner-level course guides you through querying data in BigQuery, exploring trends in Looker, and crafting shareable, interactive reports in Data Studio.
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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you.
In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.
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Earn a skill badge by completing the Introduction to Generative AI, Introduction to Large Language Models and Introduction to Responsible AI courses. By passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI.
A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.
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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps. Explore other content in the Gemini Agent Ready (GEAR) program.
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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.
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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.
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