Angel Pablo
Member since 2021
Silver League
9123 points
Sorumlu Yapay Zeka: Google Cloud ile Yapay Zeka İlkelerini Uygulama
Earned Eyl 13, 2025 EDT
Agent Platform'da İstem Tasarımı
Earned Eyl 13, 2025 EDT
[DEPRECATED] Sorumlu Yapay Zekaya Giriş
Earned Eyl 9, 2025 EDT
Büyük Dil Modellerine Giriş
Earned Eyl 9, 2025 EDT
Üretken Yapay Zeka: Chatbot'tan Daha Fazlası
Earned Ağu 28, 2025 EDT
Üretken Yapay Zekaya Giriş
Earned Ağu 16, 2025 EDT
New Year, New Skills: Red Challenge (A)
Earned Oca 17, 2023 EST
New Year, New Skills: Yellow Challenge (A)
Earned Oca 11, 2023 EST
New Year, New Skills: Green Challenge (A)
Earned Oca 5, 2023 EST
Sports Data Challenge
Earned Ara 18, 2022 EST
Build Infrastructure with Terraform on Google Cloud
Earned Eki 7, 2022 EDT
#GoogleClout Set 2, 1/10
Earned Tem 7, 2022 EDT
Learn to Earn Cloud Data Challenge: Data Analyst Skills
Earned Tem 4, 2022 EDT
Cloud Hero Infra Skills
Earned Kas 19, 2021 EST
Getting Started with Apache Kafka and Confluent Platform on Google Cloud
Earned Kas 18, 2021 EST
DEPRECATED Cloud Architecture
Earned Kas 15, 2021 EST
DEPRECATED Applying BigQuery ML's Classification, Regression, and Demand Forecasting for Retail Applications
Earned Kas 14, 2021 EST
Build a Data Warehouse with BigQuery
Earned Kas 14, 2021 EST
Create ML Models with BigQuery ML
Earned Kas 12, 2021 EST
DEPRECATED Explore Machine Learning Models with Explainable AI
Earned Kas 6, 2021 EDT
Use Machine Learning APIs on Google Cloud
Earned Kas 6, 2021 EDT
Cloud Hero Data Skills
Earned Kas 5, 2021 EDT
BigQuery Verilerinden Analiz Elde Etme
Earned Kas 4, 2021 EDT
Data Science on Google Cloud
Earned Kas 2, 2021 EDT
BigQuery for Machine Learning
Earned Kas 1, 2021 EDT
Compute Engine İçin Cloud Load Balancing'i Uygulama
Earned Eki 29, 2021 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned Eki 28, 2021 EDT
[DEPRECATED] Data Engineering
Earned Eki 28, 2021 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Eki 27, 2021 EDT
Build Streaming Data Pipelines on Google Cloud
Earned Eki 27, 2021 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Eki 27, 2021 EDT
Google Cloud'da Makine Öğrenimi API'leri İçin Veri Hazırlama
Earned Eki 27, 2021 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned Eki 25, 2021 EDT
Scaling with Google Cloud Operations
Earned Eki 18, 2021 EDT
Modernize Infrastructure and Applications with Google Cloud
Earned Eki 18, 2021 EDT
Exploring Data Transformation with Google Cloud
Earned Eki 18, 2021 EDT
Digital Transformation with Google Cloud
Earned Eki 17, 2021 EDT
Kurumsal yapay zeka ve makine öğreniminin kullanımı arttıkça, bu teknolojileri sorumlu bir şekilde geliştirmenin önemi de artıyor. Birçok kişi için sorumlu yapay zeka hakkında konuşmak, bunu uygulamaya geçirmekten daha kolaydır. Kuruluşunuzda sorumlu yapay zekayı nasıl hayata geçireceğinizi öğrenmek istiyorsanız bu kurs tam size göre.
Bu kursta, kendi sorumlu yapay zeka yaklaşımınızı geliştirirken size rehberlik edecek bir çerçeve oluşturmak adına Google Cloud'un bu süreci günümüzde nasıl yürüttüğünü, en iyi uygulama örneklerini ve edindiğimiz tecrübeleri keşfedeceksiniz.
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Agent Platform'da istem mühendisliği, görüntü analizi ve çok modlu üretken teknikler gibi becerileri göstermek için Agent Platform'da İstem Tasarımı beceri rozetini tamamlayın. Etkili istemlerin nasıl oluşturulacağını, üretken yapay zeka çıktılarına nasıl rehberlik edileceğini ve Gemini modellerinin gerçek dünyadaki pazarlama senaryolarına nasıl uygulanacağını keşfedin.
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Giriş seviyesindeki bu mikro öğrenme kursu, sorumlu yapay zekanın ne olduğunu, neden önemli olduğunu ve Google'ın sorumlu yapay zekayı ürünlerinde nasıl uyguladığını açıklamayı amaçlamaktadır. Ayrıca Google'ın 3 yapay zeka ilkesini de tanıtır.
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Giriş seviyesindeki bu mikro öğrenme kursunda; büyük dil modellerinin (LLM) ne olduğu, hangi kullanım alanlarında kullanılabilecekleri ve istem ayarlama ile LLM performansını nasıl artırabileceğiniz ele alınmaktadır. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirebileceğiniz Google araçları da yer almaktadır.
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Üretken Yapay Zeka: Chatbot'tan Daha Fazlası, Gen AI Leader öğrenme rotasının ilk kursudur ve ön koşul gerektirmez. Bu kurs, chatbot'larla ilgili temel bilgilerin ötesine geçerek üretken yapay zekanın kuruluşunuza sağlayabileceği gerçek potansiyeli keşfetmeyi amaçlamaktadır. Üretken yapay zekanın gücünden yararlanmak için çok önemli olan temel modeller ve istem mühendisliği gibi kavramları keşfedeceksiniz. Kurs ayrıca kuruluşunuz için başarılı bir üretken yapay zeka stratejisi geliştirirken dikkate almanız gereken önemli noktalar hakkında size rehberlik edecek.
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Bu giriş seviyesi mikro öğrenme kursu, üretken yapay zekanın ne olduğunu, nasıl kullanıldığını ve geleneksel makine öğrenimi yöntemlerinden farkını açıklamayı amaçlamaktadır. Ayrıca kendi üretken yapay zeka uygulamalarınızı geliştirebileceğiniz Google araçları da ele alınmaktadır.
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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New year, New skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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New year, new skills! Add 23 (or so) new skills and techniques to your toolkit, while sampling certification-based learning paths. Whether you're thinking about Google Cloud's Data, DevOps or Networking certifications, or just exploring, this is the challenge to help you start your year strong.
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GOOOOAALLL! Get practical experience on the fundamentals of sports data science no matter who you're cheering for in this week's matches. Use BigQuery ML to train advanced models to predict goals and evaluate performance. Complete labs to learn new skills and earn the badge. No prior experience needed!
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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.
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Flex your Google Clout! Each day unlocks a new cloud puzzle. Complete all five and you’ll earn the inaugural Google Cloud badge! Share your score on your choice of social networks and join the conversation over in the Google Cloud Community.
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Welcome to the Learn to Earn Cloud Data Challenge! These labs help you get started with data analysis skills. At the end of each lab, you’ll have hands-on experience with one or more of Google Cloud’s powerful data tools. Complete this game to earn a badge, and you’ll be one step closer to completing the challenge. Race the clock to increase your score and watch your name rise on the leaderboard!
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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.
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Organizations around the world rely on Apache Kafka to integrate existing systems in real time and build a new class of event streaming applications that unlock new business opportunities. Google and Confluent are in a partnership to deliver the best event streaming service based on Apache Kafka and to build event driven applications and big data pipelines on Google Cloud Platform. In this course, you will first learn how to deploy and create a streaming data pipeline with Apache Kafka, then try out the different functionalities of the Confluent Platform.
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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Cloud Architect Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.
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In this course you will learn how to use several BigQuery ML features to improve retail use cases. Predict the demand for bike rentals in NYC with demand forecasting, and see how to use BigQuery ML for a classification task that predicts the likelihood of a website visitor making a purchase.
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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
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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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Earn a skill badge by completing the Explore Machine Learning Models with Explainable AI quest, where you will learn how to do the following using Explainable AI: build and deploy a model to an AI platform for serving (prediction), use the What-If Tool with an image recognition model, identify bias in mortgage data using the What-If Tool, and compare models using the What-If Tool to identify potential bias. 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 quest and the final assessment challenge lab to receive a skill badge that you can share with your network.
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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.
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Get hands-on practice with Google Cloud! You will compete with your peers to see who can finish this game with the most points. Speed and accuracy will be used to calculate your scores — earn points by completing the labs accurately and bonus points for speed! Be sure to click “End” where you’re done with each lab to be rewarded your points.
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Giriş düzeyindeki BigQuery Verilerinden Analiz Elde Etme beceri rozetini alarak şu konulardaki becerilerinizi gösterin: SQL sorguları yazma, herkese açık tabloları sorgulama, örnek verileri BigQuery'ye yükleme, BigQuery'deki sorgu doğrulayıcı ile yaygın söz dizimi sorunlarını giderme ve BigQuery verilerine bağlanarak Data Studio'da rapor oluşturma.
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This is the first of two Quests of hands-on labs is derived from the exercises from the book Data Science on Google Cloud Platform, 2nd Edition by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Quest, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring and visualizing data sets using Google Cloud tools and services.
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Want to build ML models in minutes instead of hours using just SQL? BigQuery ML democratizes machine learning by letting data analysts create, train, evaluate, and predict with machine learning models using existing SQL tools and skills. In this series of labs, you will experiment with different model types and learn what makes a good model.
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Giriş düzeyindeki Compute Engine İçin Cloud Load Balancing'i Uygulama beceri rozetini tamamlayarak şu konulardaki becerilerinizi gösterin: Compute Engine'de sanal makineler oluşturma ve dağıtma. Ağ ve uygulama yük dengeleyicileri yapılandırma.
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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 advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
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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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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.
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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
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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, Managed Service for Apache Spark'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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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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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. This course explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts.
As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Many traditional enterprises use legacy systems and apps that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems and investing in new products and services. This course explores these challenges and offers solutions to overcome them by using cloud technology.
As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Cloud technology is a powerful asset, and when paired with data, it becomes a catalyst for innovation and enhanced customer experiences. Exploring Data Transformation with Google Cloud examines how organizations can leverage the cloud to make their data more accessible, actionable, and valuable.
As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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Digital transformation is a critical journey for modern organizations, and establishing a strong baseline in cloud computing is the first step toward driving meaningful innovation. Digital Transformation with Google Cloud introduces the core technologies and strategic frameworks that help organizations modernize their operations. This course explores fundamental cloud concepts, global network infrastructure, and the shared responsibility model to help leaders navigate their path to the cloud with confidence.
As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.
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