Bu kursta nöral ağların, giriş sırasının belirli bölümlerine odaklanmasına olanak tanıyan güçlü bir teknik olan dikkat mekanizması tanıtılmaktadır. Kursta, dikkat mekanizmasının çalışma şeklini ve makine öğrenimi, metin özetleme ve soru yanıtlama gibi çeşitli makine öğrenimi görevlerinin performansını artırmak için nasıl kullanılabileceğini öğreneceksiniz.
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Bu kursta, görüntü üretme alanında gelecek vadeden bir makine öğrenimi modelleri ailesi olan "difüzyon modelleri" tanıtılmaktadır. Difüzyon modelleri fizikten, özellikle de termodinamikten ilham alır. Geçtiğimiz birkaç yıl içinde, gerek araştırma gerekse endüstri alanında difüzyon modelleri popülerlik kazandı. Google Cloud'daki son teknoloji görüntü üretme model ve araçlarının çoğu, difüzyon modelleri ile desteklenmektedir. Bu kursta, difüzyon modellerinin ardındaki teori tanıtılmakta ve bu modellerin Vertex AI'da nasıl eğitilip dağıtılacağı açıklanmaktadır.
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Kurumsal yapay zeka ve makine öğreniminin kullanımı artmaya devam ettikçe, bunu sorumlu bir şekilde oluşturmanın önemi de artıyor. Sorumlu yapay zeka hakkında konuşmanın, onu uygulamaya koymaktan çok daha kolay olabilmesi burada bir zorluk oluşturmaktadır. Kuruluşunuzda sorumlu yapay zekayı nasıl işlevsel hale getireceğinizi öğrenmekle ilgileniyorsanız, bu kurs tam size göre.
Bu kurs, Google Cloud'un sorumlu yapay zeka yaklaşımını nasıl uyguladığını derinlemesine inceleyerek, kendi sorumlu yapay zeka stratejinizi oluşturmanız için size kapsamlı bir çerçeve sunuyor.
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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 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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Bu kurs, MLOps ekiplerinin üretken yapay zeka modellerini dağıtırken ve yönetirken karşılaştığı zorlukların üstesinden gelmek için gereken bilgi ve araçları sağlamaktadır. Ayrıca yapay zeka ekiplerinin, MLOps süreçlerini kolaylaştırıp üretken yapay zeka projelerinde başarıya ulaşması için Vertex AI'ın nasıl yardımcı olduğunu öğrenmenizi amaçlamaktadır.
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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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Gemini for Google Workspace provides users 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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Gemini for Google Workspace 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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Gemini for Google Workspace 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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Gemini for Google Workspace 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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Gemini for Google Workspace 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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Gemini for Google Workspace 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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Gemini for Google Workspace 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 second installment of the Dataflow course series, we are going to be diving deeper on developing pipelines using the Beam SDK. We start with a review of Apache Beam concepts. Next, we discuss processing streaming data using windows, watermarks and triggers. We then cover options for sources and sinks in your pipelines, schemas to express your structured data, and how to do stateful transformations using State and Timer APIs. We move onto reviewing best practices that help maximize your pipeline performance. Towards the end of the course, we introduce SQL and Dataframes to represent your business logic in Beam and how to iteratively develop pipelines using Beam notebooks.
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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models.
The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
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Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Bigtable for analysis. Learners get hands-on experience building streaming data pipeline components on Google Cloud by using QwikLabs.
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The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.
This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.
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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML. 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 the skill badge course, and final assessment challenge lab, to receive a digital badge that you can share with your network.
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In this course, you learn how to create APIs that utilize multiple services and how you can use custom code on Apigee. You will also learn about fault handling, and how to share logic between proxies. You learn about traffic management and caching. You also create a developer portal, and publish your API to the portal. You learn about logging and analytics, as well as CI/CD and the different deployment models supported by 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 third and final course of the Developing APIs with Google Cloud's Apigee API Platform course series.
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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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In this course, you learn how to design APIs, and how to use OpenAPI specifications to document them. You learn about the API life cycle, and how the Apigee API platform helps you manage all aspects of the life cycle. You learn about how APIs can be designed using API proxies, and how APIs are packaged as API products to be used by app developers.
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 first course of the Developing APIs with Google Cloud's Apigee API Platform series. After completing this course, enroll in the API Security on Google Cloud's Apigee API Platform course.
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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
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Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma kursunu tamamlayarak beceri rozeti kazanın. Bu kursta Cloud Storage, Identity and Access Management, Cloud Functions ve Pub/Sub gibi teknolojilerin temel özelliklerini kullanarak depolama odaklı bulut altyapısı oluşturma ve bu altyapıyla bağlantı kurmayı öğreneceksiniz. Beceri rozeti, Google Cloud ürünleri ve hizmetlerindeki uzmanlık düzeyinizin tanınması amacıyla Google Cloud tarafından verilen özel bir dijital rozettir. Rozeti alabilmek için bildiklerinizi etkileşimli ve uygulamalı bir ortamda başarıyla kullanabilmeniz gerekir. Ağınızla paylaşabileceğiniz bir beceri rozeti kazanmak için bu beceri rozetini ve son değerlendirme niteliğindeki yarışma laboratuvarını tamamlayın.
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Complete the introductory Implement Load Balancing on Compute Engine skill badge to demonstrate skills in the following: writing gcloud commands and using Cloud Shell, creating and deploying virtual machines in Compute Engine, and configuring network and HTTP load balancers. 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 skill badge that you can share with your network.
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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.
Dikkat Mekanizması
Earned Şub 1, 2025 EST
Görüntü Üretmeye Giriş
Earned Şub 1, 2025 EST
Sorumlu Yapay Zeka: Google Cloud ile Yapay Zeka İlkelerinin Uygulanması
Earned Şub 1, 2025 EST
Gemini for Security Engineers
Earned Oca 31, 2025 EST
Gemini for end-to-end SDLC
Earned Oca 31, 2025 EST
Üretken Yapay Zeka İçin Makine Öğrenimi Operasyonları (MLOps)
Earned Oca 30, 2025 EST
Create Engaging Video with Google Vids
Earned Oca 30, 2025 EST
Gemini in Google Drive
Earned Oca 30, 2025 EST
Gemini in Google Meet
Earned Oca 30, 2025 EST
Gemini in Google Sheets
Earned Oca 30, 2025 EST
Gemini in Google Slides
Earned Oca 30, 2025 EST
Gemini in Google Docs
Earned Oca 30, 2025 EST
Gemini in Gmail
Earned Oca 30, 2025 EST
Introduction to Gemini for Google Workspace
Earned Oca 30, 2025 EST
Serverless Data Processing with Dataflow: Develop Pipelines
Earned Oca 30, 2025 EST
How Google Does Machine Learning
Earned Eki 31, 2021 EDT
Preparing for your Professional Data Engineer Journey
Earned Eki 25, 2021 EDT
Serverless Data Processing with Dataflow: Foundations
Earned Eki 21, 2021 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Eki 20, 2021 EDT
Building Resilient Streaming Analytics Systems on Google Cloud
Earned Eki 19, 2021 EDT
Modernizing Data Lakes and Data Warehouses with Google Cloud
Earned Eki 18, 2021 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned Eki 14, 2021 EDT
API Development on Google Cloud's Apigee API Platform
Earned Eki 12, 2021 EDT
API Security on Google Cloud's Apigee API Platform
Earned Eki 12, 2021 EDT
API Design and Fundamentals of Google Cloud's Apigee API Platform
Earned Eki 12, 2021 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned Eki 12, 2021 EDT
Google Cloud'da Uygulama Geliştirme Ortamı Oluşturma
Earned Eki 11, 2021 EDT
Implement Load Balancing on Compute Engine
Earned Eki 8, 2021 EDT
Google Cloud Essentials
Earned Eki 8, 2021 EDT