Bring your ideas to life by gaining hands-on experience in application development and deployment on Google Cloud Platform. Master security, traffic management, and learn to use development frameworks while earning a Google Cloud Credential. No prior experience needed!
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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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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.
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The Cloud hums with constant communication, and the backbone of that connection is networking, linking all your resources and services. Get ready to gain hands-on experience with Google Cloud's powerful networking tools and earn an exclusive Google Cloud Credential—no prior experience needed!
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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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Excited to follow your favorite soccer/football stars on their next quest? Use GenAIus Travel Guides to learn how to interact with chat applications, master prompt engineering, understand the importance of context in AI, and work with Generative AI. Earn an exclusive Google Cloud Generative AI Credential and showcase your new skills! No prior experience needed!
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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.
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Gen AI is spearheading a revolution in careers. Whether you're seasoned or new to the field, Gen AI holds the key to fresh possibilities. Obtaining a Google Cloud credential in this innovative technology can enhance your resume. And the best part? No prior experience is required.
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Google Cloud Certifications provide a tangible way for you to demonstrate your skills to potential or current employers. These certifications incorporate performance-based questions, testing your hands-on expertise through practical tasks. Begin your journey towards becoming a Google Certified Professional with the help of the Arcade Cert Zone. Be one of the first 20 people to complete the challenge and earn a 100% discount voucher for your next Google Cloud Digital Leader Examination. Welcome!
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The sports season is in full swing—even in The Arcade! Join the Arcade Skills League to learn how to bowl perfect data solutions, hit boundaries with APIs, and score goals with AppScript. Get ready to take on these advanced challenges and earn your Google Cloud Credential!
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In this course, you learn how to secure your APIs. You explore the security concerns you will encounter for your APIs. You learn about OAuth, the primary authorization method for REST APIs. You will learn about JSON Web Tokens (JWTs) and federated security. You also learn about securing against malicious requests, safely sending requests across a public network, and how to secure your data for users of Apigee.
Through a combination of lectures, 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 second course of the Developing APIs with Google Cloud's Apigee API Platform series. After completing this course, enroll in the API Development on Google Cloud's Apigee API Platform course.
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¨Microservices" describes a software design pattern in which an application is a collection of loosely coupled services. These services are fine-grained, and can be individually maintained and scaled. The microservices architecture is ideal for the public cloud, with its focus on elastic scaling with on-demand resources. In this course, you will learn how to build Java applications using Spring Boot and Spring Cloud on Google Cloud.
You'll use Spring Cloud Config to manage your application's configuration. You'll send and receive messages with Pub/Sub and Spring Integration. You'll also use Cloud SQL as a managed relational database for your Java applications, and learn how to migrate to Spanner, which is Google Cloud's globally-distributed strongly consistent database service. You'll also learn about tracing and debugging your Spring applications with Google Cloud Observability.
To succeed in this course, you should be familiar with the Java programming language and building Java a…
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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.
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Під час курсу ви зможете ознайомитися з продуктами й сервісами Google Cloud для роботи з масивами даних і машинним навчанням, які підтримують життєвий цикл роботи з даними для тренування моделей штучного інтелекту. У курсі розглядаються процеси, проблеми й переваги створення конвеєру масиву даних і моделей машинного навчання з Vertex AI у Google Cloud.
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Курс "Знайомство з Google Cloud: основна інфраструктура" охоплює важливі поняття й терміни щодо використання Google Cloud. Переглядаючи відео й виконуючи практичні завдання, слухачі ознайомляться з різними сервісами Google Cloud для обчислень і зберігання даних, а також важливими ресурсами й інструментами для керування правилами. Крім того, вони зможуть їх порівнювати.
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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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Complete the intermediate Inspect Rich Documents with Gemini Multimodality and Multimodal RAG skill badge 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. 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 course and the final assessment challenge lab to receive a skill badge that you can share with your network.
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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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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. Кваліфікаційний значок – це ексклюзивна цифрова відзнака, яка підтверджує, що ви вмієте працювати з продуктами й сервісами Google Cloud і можете застосовувати ці знання в інтерактивному практичному середовищі. Щоб отримати кваліфікаційний значок і показати його колегам, пройдіть цей курс і підсумковий тест.
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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 intermediate Manage Kubernetes in Google Cloud skill badge to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques. 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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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. Кваліфікаційний значок – це ексклюзивна цифрова відзнака, яка підтверджує, що ви вмієте працювати з продуктами й сервісами Google Cloud, а також застосовувати ці знання в інтерактивному практичному середовищі. Щоб отримати кваліфікаційний значок і показати його колегам, пройдіть цей курс і підсумковий тест.
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Пройдіть вступний кваліфікаційний курс Налаштування розподілу навантаження в Compute Engine, щоб продемонструвати свої навички написання команд gcloud і використання Cloud Shell, створення й розгортання віртуальних машин у Compute Engine, а також налаштування мережі й розподілювачів навантаження HTTP. Кваліфікаційний значок – це ексклюзивний цифровий значок від Google Cloud, який засвідчує, що ви знаєтеся на продуктах і сервісах цієї платформи й можете застосовувати ці знання в інтерактивному практичному середовищі. Щоб отримати кваліфікаційний значок і показати його колегам, пройдіть цей курс і підсумковий тест.
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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 2: Develop and Deploy
Earned черв. 13, 2024 EDT
DEPRECATED Networking Fundamentals on Google Cloud
Earned черв. 8, 2024 EDT
Implement Cloud Security Fundamentals on Google Cloud
Earned черв. 8, 2024 EDT
Level 1: Cloud Networking
Earned черв. 8, 2024 EDT
Introduction to Generative AI - Українська
Earned черв. 4, 2024 EDT
Level 3: GenAIus Travels
Earned черв. 4, 2024 EDT
Preparing for Your Associate Cloud Engineer Journey
Earned трав. 5, 2024 EDT
Level 3: GenAIus Careers
Earned квіт. 29, 2024 EDT
The Arcade Certification Zone April 2024
Earned квіт. 29, 2024 EDT
The Arcade Skills League
Earned квіт. 29, 2024 EDT
API Security on Google Cloud's Apigee API Platform
Earned квіт. 27, 2024 EDT
Building Scalable Java Microservices with Spring Boot and Spring Cloud
Earned квіт. 27, 2024 EDT
Kubernetes in Google Cloud
Earned квіт. 27, 2024 EDT
Google Cloud Big Data and Machine Learning Fundamentals - українська
Earned квіт. 24, 2024 EDT
Google Cloud Fundamentals: Core Infrastructure - Yкраїнська
Earned квіт. 24, 2024 EDT
Принципи відповідального використання ШІ для розробників: інтерпретованість і прозорість
Earned квіт. 23, 2024 EDT
Принципи відповідального використання ШІ для розробників: об’єктивність і упередженість
Earned квіт. 23, 2024 EDT
Inspect Rich Documents with Gemini Multimodality and Multimodal RAG
Earned квіт. 23, 2024 EDT
Machine Learning Operations (MLOps) for Generative AI
Earned квіт. 22, 2024 EDT
Vector Search and Embeddings
Earned квіт. 22, 2024 EDT
Introduction to Vertex AI Studio
Earned квіт. 20, 2024 EDT
Create Image Captioning Models
Earned квіт. 20, 2024 EDT
Transformer Models and BERT Model
Earned квіт. 20, 2024 EDT
Encoder-Decoder Architecture
Earned квіт. 20, 2024 EDT
Attention Mechanism
Earned квіт. 20, 2024 EDT
Introduction to Image Generation
Earned квіт. 20, 2024 EDT
Підготовка даних для інтерфейсів API машинного навчання в Google Cloud
Earned квіт. 20, 2024 EDT
Build a Secure Google Cloud Network
Earned квіт. 20, 2024 EDT
Manage Kubernetes in Google Cloud
Earned квіт. 20, 2024 EDT
Налаштування середовища для розробки додатка в Google Cloud
Earned квіт. 19, 2024 EDT
Налаштування розподілу навантаження в Compute Engine
Earned квіт. 16, 2024 EDT
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
Earned квіт. 16, 2024 EDT
Google Cloud Computing Foundations: Networking & Security in Google Cloud
Earned квіт. 15, 2024 EDT
Google Cloud Computing Foundations: Infrastructure in Google Cloud
Earned квіт. 14, 2024 EDT
Google Cloud Computing Foundations: Cloud Computing Fundamentals
Earned квіт. 14, 2024 EDT