Your next Google Cloud Credential is within reach! Complete a series of hands-on labs (adventures!) that will help you build key Google Cloud Skills. You’ll cover topics like Compute, Storage, Networking, IAM, Kubernetes, BigQuery, and more, working through real-world scenarios to boost your understanding. No prior experience required!
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Complete the introductory Monitoring in Google Cloud skill badge course to demonstrate skills in the following: using Cloud Monitoring tools to monitor resources on Google Cloud.
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Earn a Introductory skill badge by completing the Build Serverless Applications with Cloud Run Functions course, where you learn how to use Cloud Run functions through the Google Cloud console and on the command line.
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Earn a skill badge by completing the Get Started with API Gateway skill badge course, where you learn how to use API Gateway to deploy, secure, and manage APIs with a fully managed gateway.
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Earn a skill badge by completing the Get Started with Pub/Sub skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.
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Earn a skill badge by completing the Analyze Images with the Cloud Vision API quest, where you discover how to leverage the Cloud Vision API for various tasks, including extracting text from images.
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Earn a skill badge by completing the Networking Fundamentals on Google Cloud quest, where you learn how to work with VPC networks and load balancers on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this Skill Badge, and the final assessment challenge lab, to receive a digital badge that you can share with your network.
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Earn the Introductory skill badge by completing the Cloud Speech API: 3 Ways course, where you learn how to use speech related API tools to synthesise and transcribe speech.
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Earn a skill badge by completing the App Engine`:` 3 ways course, where you learn how to use App Engine with Python, Go, and PHP.
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Earn an introductory skill badge by completing the Get Started with Google Workspace Tools 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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Complete the introductory Get Started with Dataplex skill badge to demonstrate skills in the following: creating Dataplex assets, creating aspect types, and applying aspects to entries in Dataplex.
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Earn a skill badge by completing the Get Started with Looker skill badge course, where you learn how to analyze, visualize, and curate data using Looker Studio and Looker.
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Earn a skill badge by completing the Get Started with Cloud Storage skill badge course, where you learn how to create a Cloud Storage bucket, how to use the Cloud Storage command line, and how to use Bucket Lock to protect objects in a bucket.
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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.
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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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Під час цього курсу ви ознайомитеся з важливими темами, що стосуються конфіденційності й безпеки в системах ШІ. Ви дізнаєтеся про практичні методи й інструменти, які дають змогу застосувати рекомендації щодо конфіденційності й безпеки в системах ШІ за допомогою продуктів Google Cloud і інструментів із відкритим кодом.
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У цьому курсі розглядаються поняття інтерпретованості й прозорості штучного інтелекту, а також їх важливість для розробників. Ви дізнаєтеся про практичні методи й інструменти, які дають змогу досягти інтерпретованості й прозорості даних і моделей штучного інтелекту.
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Під час цього курсу ви зможете ознайомитися з концепціями відповідального підходу й принципами щодо штучного інтелекту. Ви дізнаєтеся про практичні методи виявлення об’єктивності й упередженості в роботі ШІ та технологій машинного навчання, а також ознайомитеся зі способами мінімізувати упередженість. У курсі розглядаються практичні методи й інструменти для впровадження відповідального підходу до ШІ за допомогою продуктів Google Cloud і інструментів із відкритим кодом.
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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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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.
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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 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 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 Vertex AI.
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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 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 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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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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Що більше штучний інтелект і машинне навчання використовуються в корпоративних середовищах, то нагальнішою стає потреба розробити принципи відповідального ставлення до них. Однак говорити про принципи відповідального використання штучного інтелекту легше, ніж застосовувати їх на практиці. Цей курс допоможе вам дізнатись, як запровадити відповідальну роботу зі штучним інтелектом у вашій організації.
У цьому курсі ви дізнаєтеся про підхід Google Cloud до відповідального використання ШІ, а також отримаєте практичні поради й набудете досвіду, який допоможе вам розробити власний підхід до цього завдання.
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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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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке відповідальне використання штучного інтелекту, чому воно важливе і як компанія Google реалізує його у своїх продуктах. Крім того, у цьому курсі викладено 7 принципів Google щодо штучного інтелекту.
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У цьому ознайомлювальному курсі мікронавчання ви дізнаєтеся, що таке великі мовні моделі, де вони використовуються і як підвищити їх ефективність коригуванням запитів. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучного інтелекту.
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Це ознайомлювальний курс мікронавчання, який має пояснити, що таке генеративний штучний інтелект, як він використовується й чим відрізняється від традиційних методів машинного навчання. Він також охоплює інструменти Google, які допоможуть вам створювати власні додатки на основі генеративного штучногоінтелекту.
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Recently, a McKinsey report found that Generative AI could add up to $4.4 trillion a year to the global economy, signaling an imminent surge in the demand for GenAI professionals. Now is the perfect time to get a head start and gain hands-on experience with Google Cloud's powerful GenAI tools and techniques, carefully designed to enhance your tech skills and set you on a promising course. Play now to be at the forefront of innovation, shaping the future with GenAI and earning your first Google Cloud GenAI game badge!
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Пройдіть вступний кваліфікаційний курс Підготовка даних для інтерфейсів API машинного навчання в Google Cloud, щоб продемонструвати свої навички щодо очистки даних за допомогою сервісу Dataprep by Trifacta, запуску конвеєрів даних у Dataflow, створення кластерів і запуску завдань Apache Spark у Dataproc, а також виклику API машинного навчання, зокрема Cloud Natural Language API, Google Cloud Speech-to-Text API і Video Intelligence API.
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Щоб отримати кваліфікаційний значок, пройдіть курс Налаштування середовища для розробки додатка в Google Cloud. У ньому ви навчитеся створювати й підключати хмарну інфраструктуру, спрямовану на зберігання даних, за допомогою базових можливостей таких технологій, як Cloud Storage, система керування ідентифікацією і доступом, Cloud Functions та Pub/Sub.
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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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Пройдіть вступний кваліфікаційний курс Налаштування Cloud Load Balancing для Compute Engine, щоб продемонструвати свої навички: створення й розгортання віртуальних машин у Compute Engine; налаштування мережі й розподілювачів навантаження додатків.
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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.
Level 3: Google Cloud Adventures
Earned жовт. 28, 2024 EDT
Monitoring in Google Cloud
Earned жовт. 26, 2024 EDT
Build Serverless Applications with Cloud Run Functions
Earned жовт. 26, 2024 EDT
Get Started with API Gateway
Earned жовт. 26, 2024 EDT
Get Started with Pub/Sub
Earned жовт. 25, 2024 EDT
Analyze Images with the Cloud Vision API
Earned жовт. 25, 2024 EDT
DEPRECATED Networking Fundamentals on Google Cloud
Earned жовт. 25, 2024 EDT
Cloud Speech API: 3 Ways
Earned жовт. 24, 2024 EDT
App Engine: 3 Ways
Earned жовт. 24, 2024 EDT
Get Started with Google Workspace Tools
Earned жовт. 8, 2024 EDT
Get Started with Dataplex
Earned жовт. 8, 2024 EDT
Get Started with Looker
Earned жовт. 7, 2024 EDT
Get Started with Cloud Storage
Earned жовт. 7, 2024 EDT
The Basics of Google Cloud Compute
Earned жовт. 7, 2024 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned жовт. 7, 2024 EDT
Принципи відповідального використання ШІ для розробників: конфіденційність і безпека
Earned вер. 30, 2024 EDT
Принципи відповідального використання ШІ для розробників: інтерпретованість і прозорість
Earned вер. 30, 2024 EDT
Принципи відповідального використання ШІ для розробників: об’єктивність і упередженість
Earned вер. 30, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned вер. 30, 2024 EDT
Vector Search and Embeddings
Earned вер. 30, 2024 EDT
Introduction to Vertex AI Studio
Earned вер. 30, 2024 EDT
Create Image Captioning Models
Earned вер. 30, 2024 EDT
Transformer Models and BERT Model
Earned вер. 30, 2024 EDT
Encoder-Decoder Architecture
Earned вер. 30, 2024 EDT
Attention Mechanism
Earned вер. 30, 2024 EDT
Introduction to Image Generation
Earned вер. 30, 2024 EDT
Develop Gen AI Apps with Gemini and Streamlit
Earned вер. 30, 2024 EDT
Gemini for end-to-end SDLC
Earned вер. 30, 2024 EDT
Gemini for DevOps Engineers
Earned вер. 30, 2024 EDT
Gemini for Security Engineers
Earned вер. 30, 2024 EDT
Gemini for Network Engineers
Earned вер. 30, 2024 EDT
Gemini for Data Scientists and Analysts
Earned вер. 30, 2024 EDT
Gemini for Cloud Architects
Earned вер. 30, 2024 EDT
Gemini for Application Developers
Earned вер. 13, 2024 EDT
Responsible AI: Applying AI Principles with Google Cloud - Yкраїнська
Earned вер. 13, 2024 EDT
Prompt Design in Vertex AI
Earned вер. 13, 2024 EDT
Introduction to Responsible AI - Українська
Earned вер. 13, 2024 EDT
Introduction to Large Language Models - Українська
Earned вер. 13, 2024 EDT
Introduction to Generative AI - Українська
Earned вер. 18, 2023 EDT
Level 3: GenAI
Earned вер. 18, 2023 EDT
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud
Earned вер. 17, 2023 EDT
Налаштування середовища для розробки додатка в Google Cloud
Earned вер. 17, 2023 EDT
Build a Secure Google Cloud Network
Earned вер. 17, 2023 EDT
Налаштування Cloud Load Balancing для Compute Engine
Earned вер. 17, 2023 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned вер. 16, 2023 EDT
Google Cloud Computing Foundations: Networking & Security in Google Cloud
Earned вер. 16, 2023 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud
Earned вер. 16, 2023 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals
Earned вер. 16, 2023 EDT