Üretken Yapay Zekaya Giriş
Earned Ağu 27, 2024 EDT
Business Transformation with Google Cloud - Locales
Earned May 21, 2024 EDT
Complete the Create media search and media recommendations applications with AI Applications skill badge to demonstrate your ability to create, configure, and access media search and recommendations applications using AI Applications.
Please note that AI Applications was previously named Agent Builder, so you may encounter this older name within the lab content.
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 assessment challenge lab, to receive a skill badge that you can share with your network.
When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!
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Bu kursta, yapay zekada gizlilik ve güvenlik konuları ele alınmaktadır. Kurs boyunca, Google Cloud ürünleri ve açık kaynak araçları kullanarak yapay zekayla ilgili önerilen gizlilik ve güvenlik uygulamalarını benimsemenize yardımcı olacak pratik yöntemler ile araçları tanıyacaksınız.
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This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production.
Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production.
Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
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This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.
This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow 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.
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This course is an introduction to Vertex AI Notebooks, which are Jupyter notebook-based environments that provide a unified platform for the entire machine learning workflow, from data preparation to model deployment and monitoring. The course covers the following topics: (1) The different types of Vertex AI Notebooks and their features and (2) How to create and manage Vertex AI Notebooks.
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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.
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Giriş düzeyindeki Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Dataprep by Trifacta ile veri temizleme, Dataflow'da veri ardışık düzenleri çalıştırma, Dataproc'ta küme oluşturma ve Apache Spark işleri çalıştırma ve makine öğrenimi API'lerini (Cloud Natural Language API, Google Cloud Speech-to-Text API ve Video Intelligence API dahil olmak üzere) çağırma.
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Bu kursta yapay zekanın yorumlanabilirliği ve şeffaflığı kavramlarıyla ilgili temel bilgiler sunulmaktadır. Ayrıca geliştiriciler ve mühendisler için yapay zeka sistemlerinde şeffaflığın önemi ele alınmaktadır. Kurs boyunca, veri ve yapay zeka modellerinde yorumlanabilirliğin ve şeffaflığın sağlanmasına yardımcı olacak pratik yöntemleri ve araçları tanıyacaksınız.
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Bu giriş seviyesi mikro öğrenme kursunda büyük dil modelleri (BDM) nedir, hangi kullanım durumlarında kullanılabileceği ve büyük dil modelleri performansını artırmak için nasıl istem ayarlaması yapabileceğiniz keşfedilecektir. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirmenize yardımcı olacak Google araçları hakkında bilgi verilecektir.
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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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Bu kursta, sorumlu yapay zeka kavramı ve yapay zeka ilkeleri tanıtılmaktadır. Kurs, adalet ve önyargıyı pratik şekilde tanımlama teknikleri ile yapay zeka/makine öğrenimi uygulamalarında önyargının azaltılması konularını ele almaktadır. Kurs boyunca, Google Cloud ürünleri ve açık kaynaklı araçları kullanarak sorumlu yapay zekayla ilgili en iyi uygulamaları benimsemenize yardımcı olacak pratik yöntemler ve araçları tanıyacaksınız.
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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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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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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.
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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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Google Cloud Computing Foundations kursunda, bulut bilişimi alanında daha önce çalışmamış veya bu konuda hiç deneyimi olmayan bireylere;
temel bulut kavramları, büyük veri, makine öğrenimi gibi kavramlar ve Google Cloud'un bu kavramlarla hangi noktada,
nasıl birlikte çalıştığı ayrıntılı bir genel bakışla anlatılır.
Kursun sonunda öğrenciler bulut bilişimi, büyük veri ve makine öğrenimi konularında
fikir yürütüp bazı becerileri pratik olarak sergileyebilecek seviyeye ulaşacaktır.
Bu kurs, Google Cloud Computing Foundations adlı kurs serisinin bir parçasıdır.
Kurslar aşağıdaki sırayla tamamlanmalıdır:
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales
Google Cloud Computing Foundations: Networking and Security in Google Cloud - Locales
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales
İlk kursta bulut bilişimi, Google Cloud'u k…
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Bu, üretken yapay zekanın ne olduğunu, nasıl kullanıldığını ve geleneksel makine öğrenme yöntemlerinden nasıl farklı olduğunu açıklamayı amaçlayan giriş seviyesi bir mikro öğrenme kursudur. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirmenize yardımcı olacak Google Araçlarını da kapsar.
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This course, Business Transformation with Google Cloud- Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Business Transformation with Google Cloud.
What is cloud technology or data science and what’s all the hype about? More importantly, what can it do for you, your team, and your business?
If you want to learn about cloud technology so you can excel in your role, help build the future of your business and thrive in the cloud era, then the Business Transformation with Google Cloud course is for you. Through this interactive training, you’ll learn about core cloud business drivers—specifically Google’s cloud—and gain the knowledge/skills to determine if business transformation is right for you and your team, and build short and long-term projects using the “superpowers” of cloud accordingly. You’ll also find several templates, guides, and resource links through the supplementary student workbook to help you build a custom…
Create media search and media recommendations applications with AI Applications
Earned Kas 13, 2025 EST
Geliştiriciler İçin Sorumlu Yapay Zeka: Gizlilik ve Güvenlik
Earned Kas 2, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
Earned Kas 2, 2025 EST
Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Earned Kas 2, 2025 EST
Machine Learning Operations (MLOps): Getting Started
Earned Kas 2, 2025 EST
Production Machine Learning Systems
Earned Kas 2, 2025 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned Eki 31, 2025 EDT
Working with Notebooks in Vertex AI
Earned Eki 31, 2025 EDT
Create ML Models with BigQuery ML
Earned Eki 31, 2025 EDT
Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama
Earned Eki 28, 2025 EDT
Geliştiriciler için Sorumlu Yapay Zeka: Yorumlanabilirlik ve Şeffaflık
Earned Eki 22, 2025 EDT
Büyük Dil Modellerine Giriş
Earned Eki 22, 2025 EDT
Üretken Yapay Zeka İçin Makine Öğrenimi Operasyonları (MLOps)
Earned Eki 22, 2025 EDT
Geliştiriciler İçin Sorumlu Yapay Zeka: Adalet ve Önyargı
Earned Eki 22, 2025 EDT
Create Generative AI Apps on Google Cloud
Earned Eki 22, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned Eki 21, 2025 EDT
Feature Engineering
Earned Eki 21, 2025 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Eki 6, 2025 EDT
[DEPRECATED]-Google Cloud Computing Foundations: Cloud Computing Fundamentals - Turkish
Earned Ağu 29, 2024 EDT
Üretken Yapay Zekaya Giriş
Earned Ağu 27, 2024 EDT
Business Transformation with Google Cloud - Locales
Earned May 21, 2024 EDT