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Apply your skills in Google Cloud console

Eli Muthoka

Date d'abonnement : 2025

Ligue de Diamant

13609 points
Develop Serverless Applications on Cloud Run Earned fév. 23, 2026 EST
Deploy Kubernetes Applications on Google Cloud Earned fév. 18, 2026 EST
Developing Containerized Applications on Google Cloud Earned fév. 16, 2026 EST
Enterprise Agents and Use Cases Earned fév. 13, 2026 EST
Introduction to AI Agents Earned fév. 13, 2026 EST
Optimize Agent Behavior Earned fév. 11, 2026 EST
Build Your First Agent with Agent Development Kit (ADK) Earned fév. 11, 2026 EST
Agent Fundamentals Earned fév. 10, 2026 EST
Build a Secure Google Cloud Network Earned fév. 9, 2026 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned fév. 5, 2026 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud Earned fév. 4, 2026 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud Earned jan. 28, 2026 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned jan. 23, 2026 EST
Developing Applications with Cloud Run on Google Cloud: Fundamentals Earned jan. 2, 2026 EST
Developing Applications with Google Cloud: Foundations Earned déc. 29, 2025 EST
Prepare Data for ML APIs on Google Cloud Earned déc. 17, 2025 EST
Accelerate App Development with Gemini CLI Earned déc. 11, 2025 EST
Configure Gemini Code Assist for Organizations Earned déc. 10, 2025 EST
Build Generative AI Agents with Vertex AI and Flutter Earned déc. 9, 2025 EST
Website Modernization with Generative AI on Google Cloud Earned déc. 8, 2025 EST
Streamline App Development with Gemini Code Assist Earned déc. 8, 2025 EST
Kickstarting Application Development with Gemini Code Assist Earned déc. 3, 2025 EST
Deploy and Scale AI Models with Cloud Run Earned déc. 2, 2025 EST
Create Generative AI Apps on Google Cloud Earned nov. 29, 2025 EST
Develop Gen AI Apps with Gemini and Streamlit Earned nov. 27, 2025 EST
Gemini for DevOps Engineers Earned nov. 26, 2025 EST
Gemini for Security Engineers Earned nov. 26, 2025 EST
Gemini for Network Engineers Earned nov. 26, 2025 EST
Gemini for Data Scientists and Analysts Earned nov. 25, 2025 EST
Gemini for Cloud Architects Earned nov. 25, 2025 EST
Introduction to AI and Machine Learning on Google Cloud Earned nov. 24, 2025 EST
Set Up an App Dev Environment on Google Cloud Earned nov. 21, 2025 EST
Google Cloud Fundamentals: Core Infrastructure Earned nov. 20, 2025 EST
Responsible AI: Applying AI Principles with Google Cloud Earned nov. 19, 2025 EST
Prompt Design in Vertex AI Earned nov. 19, 2025 EST
Introduction to Responsible AI Earned nov. 19, 2025 EST
Introduction to Large Language Models Earned nov. 19, 2025 EST
Implementing Cloud Load Balancing for Compute Engine Earned nov. 19, 2025 EST
Implement Cloud Collaboration and Productivity Workflows Earned nov. 17, 2025 EST
Create Engaging Video with Google Vids Earned nov. 8, 2025 EST
Gemini in Google Drive Earned nov. 8, 2025 EST
Gemini in Google Meet Earned nov. 8, 2025 EST
Gemini in Google Sheets Earned nov. 8, 2025 EST
Gemini in Google Slides Earned nov. 7, 2025 EST
Gemini in Google Docs Earned nov. 6, 2025 EST
Gemini in Gmail Earned nov. 6, 2025 EST
Introduction to Google Workspace with Gemini Earned nov. 6, 2025 EST
Gemini for Application Developers Earned nov. 3, 2025 EST
Gemini for end-to-end SDLC Earned oct. 29, 2025 EDT
Develop AI-Powered Prototypes in Google AI Studio Earned oct. 26, 2025 EDT
Introduction to Generative AI Earned oct. 24, 2025 EDT

Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.

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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.

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In this course, you learn about containers and how to build, and package container images. The content in this course includes best practices for creating and securing containers, and provides an introduction to Cloud Run and Google Kubernetes Engine for application developers.

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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.

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Gain a conceptual overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems. You’ll explore the technical architecture—models, tools, and orchestration—that enables agents to learn, plan, and achieve goals on your behalf.

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You’ve built 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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AI Agents represent a major shift beyond traditional large language models (LLMs): instead of simply generating text-based solutions, they can also act autonomously to execute them. This course introduces the fundamentals of AI Agents, how they differ from LLM APIs, and where they add value in the real world. Based on Google’s agents whitepaper, it provides the theoretical foundation needed before writing your first lines of agent code—ideal for developers, architects, and technical decision-makers who want to understand AI systems through the lens of autonomous, goal-directed behavior (and not just text generation). Join the community forum for questions and discussions.

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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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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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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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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 course introduces the Cloud Run serverless platform for running applications. In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle. You learn about service identities, how to control access to services, and how to develop and test your application locally before deploying it to Cloud Run. The course also teaches you how to integrate with other services on Google Cloud so you can build full-featured applications.

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In this course, you learn the fundamentals of application development on Google Cloud. You learn best practices for cloud applications, and how to select compute and data options to match your application use cases. You're introduced to generative AI and how it's used to help build applications. You learn about authentication and authorization, application deployment, continuous integration and delivery, and monitoring and performance tuning for your applications running in Google Cloud. Using lectures and hands-on labs, you learn how to get started building and running applications on 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 Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.

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This course is designed for app developers and DevOps engineers who want to work smarter by using Gemini CLI, a generative AI agent made for the terminal and powered by Gemini. This course discusses Gemini CLI installation and configuration, and introduces use cases and security best practices. It explains commands, tools, MCP servers, and extensions. With a hands-on exercise, you'll install and configure Gemini CLI and use it to analyze code and build and modify an app.

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This course is designed for Google Cloud developers and DevOps engineers who have basic knowledge of the Google Cloud console and are responsible for configuring Gemini Code Assist for an organization. The course introduces the benefits of Gemini Code Assist and compares the features of the different Gemini Code Assist editions. The course also shows you how to configure and manage Gemini Code Assist within an organization.

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In this course, you learn how to develop an app using Flutter, Google's portable UI toolkit, and integrate the app with Gemini, Google's family of generative AI models. You also use Vertex AI Agent Builder, Google's platform for building and managing AI Agents and applications.

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Enhance the navigation experience of your website by using generative AI to provide a better search experience for your users. In this course, you learn how to use Vertex AI Search to provide your website users a generative search experience enabling them to discover content offered by the website. As a website editor, you also learn how to use generative AI to quickly and efficiently translate and improve the content using suggestions.

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Designed for developers of all levels, this course introduces you to the core features and functionalities of Gemini Code Assist, an AI-powered app development collaborator for Google Cloud. From intelligent code suggestions and auto-completion to real-time error detection and refactoring assistance, you'll discover how Gemini Code Assist can significantly enhance your productivity and code quality, and save valuable time to focus on more productive and enjoyable tasks.

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Earn a skill badge by completing the Kickstarting Application Development with Gemini Code Assist course, where you will learn to leverage the power of Google's AI coding assistant and multiple development tech

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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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Generative AI applications can create new user experiences that were nearly impossible before the invention of large language models (LLMs). As an application developer, how can you use generative AI to build engaging, powerful apps on Google Cloud? In this course, you'll learn about generative AI applications and how you can use prompt design and retrieval augmented generation (RAG) to build powerful applications using LLMs. You'll learn about a production-ready architecture that can be used for generative AI applications and you'll build an LLM and RAG-based chat application.

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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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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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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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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 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.

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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 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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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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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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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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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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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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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.

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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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Earn an introductory skill badge by completing the Implement Cloud Collaboration and Productivity Workflows course, where you will get introduced to Google's collaborative platform and learn to use Gmail, Calendar, Meet, Drive, Sheets, and AppSheet.

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In this course, you'll learn about Google Vids, an online video creation and editing app available to select Google Workspace users. Through lessons and demos, you'll learn how to build and tell compelling stories through video at work. You'll also discover how to seamlessly incorporate media, audio and video clips, customize styles, and easily share your creations. Some Vids features use generative AI to help you work more efficiently. Remember, generative AI tools including Gemini, may suggest inaccurate or inappropriate information. Don’t rely on Gemini features as medical, legal, financial or other professional advice. It’s also important to remember that the Gemini feature suggestions don’t represent Google’s views, and should not be attributed to Google.

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Google Workspace with Gemini provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Drive using video lessons, hands-on activities and practical examples. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Drive to improve your workflows.

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Google Workspace with Gemini provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Meet. Through video lessons, hands-on activities and practical examples, you will gain a comprehensive understanding of the Gemini features in Google Meet. You learn how to use Gemini to generate background images, improve your video quality, and translate captions. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Meet to maximize the effectiveness of your video conferences.

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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Sheets.

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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Slides.

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Google Workspace with Gemini provides customers with access to generative AI features. This course delves into the capabilities of Gemini in Google Docs using video lessons, hands-on activities and practical examples. You learn how to use Gemini to generate written content based on prompts. You also explore using Gemini to edit text you’ve already written, helping you improve your overall productivity. By the end of this course, you'll be equipped with the knowledge and skills to confidently utilize Gemini in Google Docs to improve your writing.

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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this mini-course, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Gmail.

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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. In this learning path, you learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Workspace.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps developers build applications. You learn how to prompt Gemini to explain code, recommend Google Cloud services, and generate code for your applications. Using a hands-on lab, you experience how Gemini improves the application development workflow. 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 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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Complete the introductory Develop AI-Powered Prototypes in Google AI Studio skill badge to demonstrate skills in the following: crafting effective prompts, leveraging multimodal capabilities for image and video analysis, prototyping functional AI-driven applications from templates and text prompts, and utilizing API keys to build and deploy custom AI solutions.

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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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