Responsible AI for Developers: Interpretability & Transparency
Earned avr. 19, 2026 EDT
Responsible AI for Developers: Fairness & Bias
Earned avr. 16, 2026 EDT
Manage Agent Memory and State
Earned avr. 14, 2026 EDT
Add Agent Capabilities With Tools
Earned avr. 12, 2026 EDT
Optimize Agent Behavior
Earned avr. 10, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK)
Earned avr. 9, 2026 EDT
Build Agents with Agent Development Kit (ADK)
Earned avr. 9, 2026 EDT
Networking in Google Cloud: Network Architecture
Earned avr. 6, 2026 EDT
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned mars 30, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned mars 24, 2026 EDT
Boost Productivity with Gemini in BigQuery
Earned mars 23, 2026 EDT
Work with Gemini Models in BigQuery
Earned mars 22, 2026 EDT
Using BigQuery Machine Learning for Inference
Earned mars 20, 2026 EDT
Gemini for Data Scientists and Analysts
Earned mars 19, 2026 EDT
Learn how to use NotebookLM to create a personalized study guide for the Associate Cloud Engineer certification exam.
You'll review NotebookLM features, create a notebook in NotebookLM, and learn how to use a 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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In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Vertex AI Agent Engine to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Engine.
Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.
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This course provides a comprehensive overview of Google Cloud's agent platforms, Gemini Enterprise app, Conversational Agents, Customer Experience (CX) Studio, Gemini Enterprise Agent Platform, and Agent Development Kit. Learners will understand the unique capabilities of each offering, distinguish between the optimal solution for specific use cases, and gain foundational knowledge in creating search and chat applications.
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This structured course is for developers interested in building intelligent agents using the Agent Development Kit (ADK). It combines hands-on experience, core concepts, and practical application, to provide a comprehensive guide to using ADK. You can also join our community of Google Cloud experts and peers to ask questions, collaborate on answers, and connect with the Googlers making the products you use every day.
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In this course, you will learn how to centralize diverse sources like PDFs, web pages, and even audio files into a single, intelligent workspace. You will learn to chat with your documents to find specific information, generate instant summaries, and verify answers with AI-powered citations.
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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.
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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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Google Cloud : Prompt Engineering Guide examines generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.
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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 applications.
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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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Configure, fix, and deploy agents to earn a skill badge! Use Agent Development Kit (ADK) to verify travel info and audit marketing claims. Master agent lifecycle management to build reliable, automated verification tools.
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Complete the intermediate Engineer AI Agents with Agent Development Kit (ADK) skill badge by completing this course to demonstrate skills in the following: formulating real-world language model research problems; building a simple tokenizer; preparing a dataset for training a transformer language model; running the training loop of a small language model.
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This course introduces Gemini Enteprise, a powerful platform that brings together AI agents, enterprise search, NotebookLM, and intelligent data access to solve organizational challenges. Through real-world examples and hands-on exploration, learners will be able to connect Gemini Enterprise capabilities to real business needs, describe its architecture, and explain how it handles data access and privacy across roles.
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Unite Google’s expertise in search and AI with Gemini Enterprise, a powerful tool designed to help employees find specific information from document storage, email, chats, ticketing systems, and other data sources, all from a single search bar. The Gemini Enterprise assistant can also help brainstorm, research, outline documents, and take actions like inviting coworkers to a calendar event to accelerate knowledge work and collaboration of all kinds.
(Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)
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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 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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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.
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Welcome to the third course of the "Networking in Google Cloud" series: Network Architecture!
In this course, you will explore the fundamentals of designing efficient and scalable network architectures within Google Cloud.
In the first module, Introduction to Network Architecture, we'll start by introducing you to the core components and concepts of network architecture, including subnets, routes, firewalls, and load balancing.
Then in the second module, network topologies, we'll dive into various network topologies commonly used in Google Cloud, discussing their strengths, and weaknesses.
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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 Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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This course is dedicated to equipping you with the knowledge and tools needed to uncover the unique challenges faced by MLOps teams when deploying and managing Generative AI models, and exploring how Vertex AI empowers AI teams to streamline MLOps processes and achieve success in Generative AI projects.
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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.
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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
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Learn about BigQuery ML for Inference, why Data Analysts should use it, its use cases, and supported ML models. You will also learn how to create and manage these ML models in BigQuery.
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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.
Duet AI was renamed to Gemini, our next-generation model.
Build a Certification Study Guide: ACE Exam Prep
Earned juin 12, 2026 EDT
Responsible AI for Developers: Privacy & Safety
Earned juin 9, 2026 EDT
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine
Earned juin 9, 2026 EDT
Understand Google Cloud Agents
Earned juin 8, 2026 EDT
Build intelligent agents with Agent Development Kit (ADK)
Earned juin 7, 2026 EDT
Unlock Insights with NotebookLM
Earned mai 31, 2026 EDT
Orchestrate Multi-agent Workflows with Gemini Enterprise
Earned mai 24, 2026 EDT
Human-Centered AI
Earned mai 23, 2026 EDT
Gen AI Agents: Transform Your Organization
Earned mai 20, 2026 EDT
AI Boost Bites: Personalization with customized prompts
Earned mai 11, 2026 EDT
AI Boost Bites: Prompting like a Pro with Google Workspace
Earned mai 10, 2026 EDT
[DEPRECATED] Google Cloud: Prompt Engineering Guide
Earned mai 9, 2026 EDT
Model Armor: Securing AI Deployments
Earned mai 4, 2026 EDT
Introduction to Security in the World of AI
Earned avr. 29, 2026 EDT
[DEPRECATED] Engineer AI Agents with Agent Development Kit
Earned avr. 21, 2026 EDT
Engineer AI Agents with Agent Development Kit (ADK)
Earned avr. 21, 2026 EDT
Introduction to Gemini Enterprise
Earned avr. 20, 2026 EDT
Accelerate Knowledge Exchange with Gemini Enterprise
Earned avr. 20, 2026 EDT
Responsible AI for Developers: Interpretability & Transparency
Earned avr. 19, 2026 EDT
Responsible AI for Developers: Fairness & Bias
Earned avr. 16, 2026 EDT
Manage Agent Memory and State
Earned avr. 14, 2026 EDT
Add Agent Capabilities With Tools
Earned avr. 12, 2026 EDT
Optimize Agent Behavior
Earned avr. 10, 2026 EDT
Build Your First Agent with Agent Development Kit (ADK)
Earned avr. 9, 2026 EDT
Build Agents with Agent Development Kit (ADK)
Earned avr. 9, 2026 EDT
Networking in Google Cloud: Network Architecture
Earned avr. 6, 2026 EDT
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned mars 30, 2026 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned mars 24, 2026 EDT
Boost Productivity with Gemini in BigQuery
Earned mars 23, 2026 EDT
Work with Gemini Models in BigQuery
Earned mars 22, 2026 EDT
Using BigQuery Machine Learning for Inference
Earned mars 20, 2026 EDT
Gemini for Data Scientists and Analysts
Earned mars 19, 2026 EDT