Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine
Earned nov. 11, 2025 EST
AI Boost Bites: Intro to NotebookLM
Earned nov. 10, 2025 EST
Use Machine Learning APIs on Google Cloud
Earned nov. 9, 2025 EST
AI Infrastructure: Cloud TPUs
Earned nov. 6, 2025 EST
AI Infrastructure: Cloud GPUs
Earned nov. 6, 2025 EST
AI Infrastructure: Introduction to AI Hypercomputer
Earned nov. 5, 2025 EST
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned mai 20, 2025 EDT
Explore Generative AI with the Gemini API in Vertex AI
Earned mai 11, 2025 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned mai 9, 2025 EDT
Prompt Design in Vertex AI
Earned mai 6, 2025 EDT
Build Real World AI Applications with Gemini and Imagen
Earned avr. 25, 2025 EDT
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 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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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
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Welcome to the Cloud TPUs course. We'll explore the advantages and disadvantages of TPUs in various scenarios and compare different TPU accelerators to help you choose the right fit. You'll learn strategies to maximize performance and efficiency for your AI models and understand the significance of GPU/TPU interoperability for flexible machine learning workflows. Through engaging content and practical demos, we'll guide you step-by-step in leveraging TPUs effectively.
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Curious about the powerful hardware behind AI? This module breaks down performance-optimized AI computers, showing you why they're so important. We'll explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them. By the end, you'll know exactly how to pick the right GPU for your AI projects, helping you make smart choices for your AI workloads.
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Ready to get started with AI Hypercomputers? This course makes it easy! We'll cover the basics of what they are and how they help AI with AI workloads. You'll learn about the different components inside a hypercomputer, like GPUs, TPUs, and CPUs, and discover how to pick the right deployment approach for your needs.
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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge course to demonstrate skills in the following: using multimodal prompts to extract information from text and visual data, generating a video description, and retrieving extra information beyond the video using multimodality with Gemini; building metadata of documents containing text and images, getting all relevant text chunks, and printing citations by using Multimodal Retrieval Augmented Generation (RAG) with Gemini.
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Complete the intermediate Explore Generative AI with the Gemini API in Vertex AI skill badge to demonstrate skills in text generation, image and video analysis for enhanced content creation, and applying function calling techniques within the Gemini API. Discover how to leverage sophisticated Gemini techniques, explore multimodal content generation, and expand the capabilities of your AI-powered projects.
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Complete the intermediate Develop Gen AI Apps with Gemini and Streamlit skill badge course to demonstrate skills in text generation, applying function calls with the Python SDK and Gemini API, and deploying a Streamlit application with Cloud Run. In this course, you learn Gemini prompting, test Streamlit apps in Cloud Shell, and deploy them as Docker containers in Cloud Run.
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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.
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Complete the introductory Build Real World AI Applications with Gemini and Imagen skill badge to demonstrate skills in the following: image recognition, natural language processing, image generation using Google's powerful Gemini and Imagen models, deploying applications on the Vertex AI platform.
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine
Earned nov. 11, 2025 EST
AI Boost Bites: Intro to NotebookLM
Earned nov. 10, 2025 EST
Use Machine Learning APIs on Google Cloud
Earned nov. 9, 2025 EST
AI Infrastructure: Cloud TPUs
Earned nov. 6, 2025 EST
AI Infrastructure: Cloud GPUs
Earned nov. 6, 2025 EST
AI Infrastructure: Introduction to AI Hypercomputer
Earned nov. 5, 2025 EST
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned mai 20, 2025 EDT
Explore Generative AI with the Gemini API in Vertex AI
Earned mai 11, 2025 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned mai 9, 2025 EDT
Prompt Design in Vertex AI
Earned mai 6, 2025 EDT
Build Real World AI Applications with Gemini and Imagen
Earned avr. 25, 2025 EDT