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PANJI WINATA

Menjadi anggota sejak 2024

Diamond League

27069 poin
Agen AI Generatif: Mentransformasi Organisasi Anda Earned Sep 18, 2025 EDT
Gen AI Apps: Transform Your Work Earned Sep 18, 2025 EDT
Gen AI: Navigate the Landscape Earned Sep 18, 2025 EDT
AI Generatif: Memahami Konsep Dasar Earned Sep 18, 2025 EDT
AI Generatif: Lebih dari Sekadar Chatbot Earned Sep 18, 2025 EDT
Bekerja dengan Model Gemini di BigQuery Earned Sep 16, 2025 EDT
Meningkatkan Produktivitas dengan Gemini in BigQuery Earned Sep 16, 2025 EDT
Serverless Data Processing with Dataflow: Foundations Earned Sep 15, 2025 EDT
Pengantar AI Generatif Earned Sep 14, 2025 EDT
Preparing for your Professional Data Engineer Journey Earned Sep 11, 2025 EDT
Pengantar AI dan Machine Learning di Google Cloud Earned Mei 25, 2025 EDT
Professional Machine Learning Engineer Study Guide Earned Jan 13, 2025 EST
Put It All Together: Prepare for a Cloud Data Analyst Job Earned Des 8, 2024 EST
The Power of Storytelling: How to Visualize Data in the Cloud Earned Des 2, 2024 EST
Data Transformation in the Cloud Earned Des 1, 2024 EST
Data Management and Storage in the Cloud Earned Nov 29, 2024 EST
Introduction to Data Analytics in Google Cloud Earned Nov 13, 2024 EST

Agen AI Generatif: Mentransformasi Organisasi Anda adalah kursus kelima dan terakhir dari jalur pembelajaran Generative AI Leader. Kursus ini membahas cara organisasi menggunakan agen AI generatif kustom untuk membantu mengatasi tantangan bisnis tertentu. Anda akan mendapatkan praktik langsung dalam membangun agen AI generatif dasar, sambil mempelajari komponen agen ini, seperti model, loop penalaran, dan alat.

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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

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AI Generatif: Memahami Konsep Dasar adalah kursus kedua dari alur pembelajaran Generative AI Leader. Dalam kursus ini, Anda akan mempelajari konsep dasar AI generatif. Anda akan mempelajari perbedaan antara AI, ML, dan AI generatif serta mempelajari bagaimana berbagai jenis data memungkinkan AI generatif mengatasi tantangan bisnis. Anda juga akan mendapatkan insight tentang strategi Google Cloud untuk mengatasi keterbatasan model dasar dan tantangan utama dalam pengembangan dan deployment AI yang bertanggung jawab dan aman.

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AI Generatif: Lebih dari Sekadar Chatbot adalah kursus pertama dari alur pembelajaran Generative AI Leader. Kursus ini tidak memiliki prasyarat. Kursus ini bertujuan untuk melampaui pemahaman dasar tentang chatbot guna mengeksplorasi potensi sebenarnya dari AI generatif untuk organisasi Anda. Anda akan mempelajari konsep seperti model dasar dan rekayasa perintah, yang penting untuk memanfaatkan kekuatan AI generatif. Kursus ini juga memandu Anda melalui pertimbangan penting yang harus Anda buat saat mengembangkan strategi AI generatif yang sukses untuk organisasi Anda.

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Kursus ini menunjukkan cara menggunakan model AI/ML untuk tugas-tugas AI generatif di BigQuery. Melalui kasus penggunaan praktis yang melibatkan pengelolaan hubungan pelanggan (CRM), Anda akan mempelajari alur kerja pemecahan masalah bisnis dengan model Gemini. Untuk memudahkan pemahaman, kursus ini juga menyediakan panduan langkah demi langkah melalui solusi coding menggunakan kueri SQL dan notebook Python.

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Kursus ini mengeksplorasi Gemini in BigQuery, yakni paket fitur yang didukung AI untuk membantu alur kerja data ke AI. Paket fitur ini meliputi eksplorasi dan persiapan data, pembuatan kode dan pemecahan masalah, serta penemuan dan visualisasi alur kerja. Melalui penjelasan konseptual, kasus penggunaan praktis, dan lab interaktif, kursus ini akan membantu para praktisi data dalam meningkatkan produktivitas mereka dan mempercepat pipeline pengembangan.

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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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Ini adalah kursus pengantar pembelajaran mikro yang bertujuan untuk mendefinisikan AI Generatif, cara penggunaannya, dan perbedaannya dari metode machine learning konvensional. Kursus ini juga mencakup Alat-alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.

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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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Kursus ini memperkenalkan penawaran AI dan machine learning (ML) di Google Cloud yang membangun project AI prediktif dan generatif. Kursus ini akan membahas teknologi, produk, dan alat yang tersedia di seluruh siklus proses data ke AI, yang mencakup fondasi, pengembangan, dan solusi AI. Kursus ini bertujuan membantu data scientist, developer AI, dan engineer ML meningkatkan keterampilan dan pengetahuan mereka melalui pengalaman belajar yang menarik dan latihan praktik langsung.

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This course helps learners create a study plan for the PMLE (Professional Machine Learning 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 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.

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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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