PANJI WINATA
Member since 2024
Diamond League
27069 points
Introduction to Data Analytics in Google Cloud
Earned Ara 11, 2025 EST
Data Management and Storage in the Cloud
Earned Ara 11, 2025 EST
Data Transformation in the Cloud
Earned Ara 11, 2025 EST
The Power of Storytelling: How to Visualize Data in the Cloud
Earned Ara 10, 2025 EST
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned Ara 10, 2025 EST
Üretken Yapay Zeka Ajanları: Kuruluşunuzu Dönüştürün
Earned Eyl 18, 2025 EDT
Üretken Yapay Zeka Uygulamaları: İşinizi Dönüştürün
Earned Eyl 18, 2025 EDT
Üretken Yapay Zeka: Ekosistemi Tanıma
Earned Eyl 18, 2025 EDT
Üretken Yapay Zeka: Temel Kavramları Öğrenin
Earned Eyl 18, 2025 EDT
Üretken Yapay Zeka: Chatbot'tan Daha Fazlası
Earned Eyl 18, 2025 EDT
Work with Gemini Models in BigQuery
Earned Eyl 16, 2025 EDT
Boost Productivity with Gemini in BigQuery
Earned Eyl 16, 2025 EDT
Serverless Data Processing with Dataflow: Foundations
Earned Eyl 15, 2025 EDT
Üretken Yapay Zekaya Giriş
Earned Eyl 14, 2025 EDT
Build a Certification Study Guide: PDE Exam Prep
Earned Eyl 11, 2025 EDT
Introduction to AI and Machine Learning on Google Cloud
Earned May 25, 2025 EDT
Build a Certification Study Guide: PMLE
Earned Oca 13, 2025 EST
Put It All Together: Prepare for a Cloud Data Analyst Job
Earned Ara 8, 2024 EST
The Power of Storytelling: How to Visualize Data in the Cloud
Earned Ara 2, 2024 EST
Data Transformation in the Cloud
Earned Ara 1, 2024 EST
Data Management and Storage in the Cloud
Earned Kas 29, 2024 EST
Introduction to Data Analytics in Google Cloud
Earned Kas 13, 2024 EST
Welcome learner! This is the first of five courses of the Google Cloud Data Analytics Certificate. Jump into the world of data analytics and cloud computing. Explore the data lifecycle in the cloud and gain a better understanding of the common tools used by data analysts.
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Hi again! This is the second course of the Google Cloud Data Analytics Certificate. Get cozy with the key components of data governance, normalized and star schemas, data catalogs, and data lakehouse architecture.
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This is the third of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll begin by getting an overview of the data journey, from collection to insights. You’ll then learn how to use SQL to transform raw data into a usable format. Next, you’ll learn how to transform high volumes of data with a data pipeline. Finally, you’ll gain experience applying transformation strategies to real data sets to solve business needs.
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You’re over halfway through the program! This is the fourth course of the Google Cloud Data Analytics Certificate. Level up your data visualization skills by unlocking the secrets of transforming flat data into captivating stories that leap from the screen and onto the agenda of your key stakeholders. Happy learning!
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You made it! This is the fifth and final course of the Google Cloud Data Analytics Certificate. There’s no time like the present to start preparing for your job as a Cloud Data Analyst. Let's polish up that resume and refine those interview skills to allow you to show up with confidence for your interview!
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Üretken Yapay Zeka Ajanları: Kuruluşunuzu Dönüştürün, Üretken Yapay Zeka Lideri öğrenme rotasının beşinci ve son kursudur. Bu kursta, kuruluşların özel üretken yapay zeka ajanlarını kullanarak belirli işletme zorluklarının üstesinden nasıl gelebileceği ele alınmaktadır. Temel bir üretken yapay zeka ajanı oluşturarak pratik yapacak, bu ajanların modeller, mantık döngüleri ve araçlar gibi bileşenlerini keşfedeceksiniz.
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Üretken Yapay Zeka Uygulamaları ile İşinizi Dönüştürün, Üretken Yapay Zeka Lideri öğrenme rotasının dördüncü kursudur. Bu kursta, Google'ın üretken yapay zeka uygulamaları (ör. Gemini ile Google Workspace ve NotebookLM) tanıtılmaktadır. Temellendirme, veriyle artırılmış üretim, etkili istemler hazırlama ve otomatik iş akışları oluşturma gibi kavramlar hakkında size rehberlik eder.
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Üretken Yapay Zeka: Ekosistemi Tanıma, Üretken Yapay Zeka Lideri öğrenme rotasının üçüncü kursudur. Üretken yapay zeka, çalışma şeklimizi ve çevremizle etkileşim kurma biçimimizi değiştiriyor. Peki bir lider olarak bu teknolojinin gücünden yararlanıp işletmenizde nasıl gerçek sonuçlar elde edebilirsiniz? Bu kursta, üretken yapay zeka çözümleri oluşturmanın farklı katmanlarını, Google Cloud'un sunduğu hizmetleri ve çözüm seçerken dikkate alınması gereken faktörleri keşfedeceksiniz.
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Üretken Yapay Zeka: Temel Kavramları Öğrenin, Üretken Yapay Zeka Lideri öğrenme rotasının ikinci kursudur. Bu kursta, yapay zeka, makine öğrenimi ve üretken yapay zeka arasındaki farkları keşfederek üretken yapay zekanın temel kavramlarını öğrenecek ve çeşitli veri türlerinin üretken yapay zekanın kurumsal zorlukları çözmesine nasıl yardımcı olduğunu anlayacaksınız. Temel modellerin sınırlamalarını gidermeye yardımcı olacak Google Cloud stratejileriyle sorumlu ve güvenli yapay zeka geliştirme ve dağıtımının temel zorlukları hakkında da bilgi edineceksiniz.
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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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This course demonstrates how to use AI/ML models for generative AI tasks in BigQuery. Through a practical use case involving customer relationship management, you learn the workflow of solving a business problem with Gemini models. To facilitate comprehension, the course also provides step-by-step guidance through coding solutions using both SQL queries and Python notebooks.
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This course explores Gemini in BigQuery, a suite of AI-driven features to assist data-to-AI workflow. These features include data exploration and preparation, code generation and troubleshooting, and workflow discovery and visualization. Through conceptual explanations, a practical use case, and hands-on labs, the course empowers data practitioners to boost their productivity and expedite the development pipeline.
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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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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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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Data Engineer certification exam.
You'll review Gemini Notebook features, create a notebook in Gemini Notebook, and learn how to use a study guide to practice for a certification exam.
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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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Learn how to use Gemini Notebook to create a personalized study guide for the Professional Machine Learning Engineer (PMLE) certification exam. You'll review Gemini Notebook features, create a notebook, and use the study guide to practice for a certification exam.
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This is the fifth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll combine and apply the foundational knowledge and skills from courses 1-4 in a hands-on Capstone project that focuses on the full data lifecycle project. You’ll practice using cloud-based tools to acquire, store, process, analyze, visualize, and communicate data insights effectively. By the end of the course, you’ll have completed a project demonstrating their proficiency in effectively structuring data from multiple sources, presenting solutions to varied stakeholders, and visualizing data insights using cloud-based software. You’ll also update your resume and practice interview techniques to help prepare for applying and interviewing for jobs.
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This is the fourth of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll focus on developing skills in the five key stages of visualizing data in the cloud: storytelling, planning, exploring data, building visualizations, and sharing data with others. You’ll also gain experience using UI/UX skills to wireframe impactful, cloud-native visualizations and work with cloud-native data visualization tools to explore datasets, create reports, and build dashboards that drive decisions and foster collaboration.
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This is the third of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll begin by getting an overview of the data journey, from collection to insights. You’ll then learn how to use SQL to transform raw data into a usable format. Next, you’ll learn how to transform high volumes of data with a data pipeline. Finally, you’ll gain experience applying transformation strategies to real data sets to solve business needs.
Learn more
This is the second of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll explore how data is structured and organized. You’ll gain hands-on experience with the data lakehouse architecture and cloud components like BigQuery, Google Cloud Storage, and DataProc to efficiently store, analyze, and process large datasets.
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This is the first of five courses in the Google Cloud Data Analytics Certificate. In this course, you’ll define the field of cloud data analysis and describe roles and responsibilities of a cloud data analyst as they relate to data acquisition, storage, processing, and visualization. You’ll explore the architecture of Google Cloud-based tools, like BigQuery and Cloud Storage, and how they are used to effectively structure, present, and report data.
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