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Manuel Escalona

Menjadi anggota sejak 2022

Diamond League

29420 poin
Logging and Monitoring in Google Cloud Earned Jun 28, 2024 EDT
Infrastruktur Google Cloud yang Dapat Diandalkan: Desain dan Proses Earned Jun 20, 2024 EDT
Mulai Menggunakan Google Kubernetes Engine Earned Jun 13, 2024 EDT
Preparing for your Professional Cloud Architect Journey Earned Jun 11, 2024 EDT
Infrastruktur Google Cloud Elastis: Penskalaan dan Otomatisasi Earned Jun 5, 2024 EDT
Infrastruktur Google Cloud yang Penting: Layanan Inti Earned Mei 28, 2024 EDT
Infrastruktur Google Cloud yang Penting: Fondasi Earned Mei 22, 2024 EDT
BI Reporting: Looker Visualization on BigQuery Earned Mei 3, 2024 EDT
Application Development with Cloud Run Earned Des 8, 2023 EST
Getting Started with Terraform for Google Cloud Earned Sep 7, 2023 EDT
DEPRECATED Planning for a Google Workspace Deployment Earned Sep 6, 2023 EDT
Membuat dan Mengelola Instance AlloyDB Earned Sep 5, 2023 EDT
Membuat dan Mengelola Instance Bigtable Earned Agu 28, 2023 EDT
Membuat dan Mengelola Instance Cloud Spanner Earned Agu 23, 2023 EDT
Pengantar Responsible AI Earned Agu 15, 2023 EDT
Generative AI Fundamentals Earned Agu 15, 2023 EDT
Pengantar Model Bahasa Besar Earned Agu 14, 2023 EDT
Pengantar AI Generatif Earned Agu 14, 2023 EDT
Contact Center AI: Conversational Design Fundamentals Earned Agu 9, 2023 EDT
DEPRECATED BigQuery for Marketing Analysts Earned Jul 18, 2023 EDT
BigQuery untuk Machine Learning Earned Jul 14, 2023 EDT
Managing Cloud Infrastructure with Terraform Earned Jul 12, 2023 EDT
Dasar-Dasar Google Cloud: Infrastruktur Inti Earned Jul 5, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned Jun 30, 2023 EDT
Data Warehousing for Partners: BigQuery Extended Capabilities Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Analyze Data with Looker Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Streaming Analytics Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Stream Data with Pub/Sub Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Process Data with Dataflow Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Cloud Data Fusion Pipelines Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Process Data with Dataproc Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Optimize in BigQuery Earned Jun 27, 2023 EDT
Data Warehousing for Partners: Data Warehouse Migration with BigQuery Earned Jun 27, 2023 EDT
Dasar-Dasar Google Cloud Earned Jun 5, 2023 EDT
Enterprise Database Migration Earned Jun 2, 2023 EDT
Cloud SQL Earned Mei 25, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned Jul 16, 2022 EDT

Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.

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Kursus ini membekali peserta dengan keterampilan untuk membangun solusi yang sangat andal dan efisien di Google Cloud menggunakan pola desain yang telah terbukti. Kursus ini merupakan kelanjutan dari kursus Membangun dengan Google Compute Engine atau Membangun dengan Google Kubernetes Engine dan memberikan pengalaman interaktif dengan teknologi yang dibahas dalam kursus tersebut. Melalui kombinasi presentasi, aktivitas desain, dan lab interaktif, peserta akan mempelajari cara menentukan serta menyeimbangkan kebutuhan bisnis dan teknis untuk merancang deployment Google Cloud yang sangat andal, sangat tersedia, aman, dan hemat biaya.

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Selamat datang di kursus Mulai Menggunakan Google Kubernetes Engine. Jika Anda tertarik dengan Kubernetes, lapisan software yang berada di antara aplikasi Anda dan infrastruktur hardware Anda, maka Anda berada di tempat yang tepat! Google Kubernetes Engine menghadirkan Kubernetes sebagai layanan terkelola di Google Cloud. Tujuan kursus ini adalah untuk memperkenalkan dasar-dasar Google Kubernetes Engine, atau GKE, sebagaimana umumnya disebut, dan cara membuat aplikasi dalam container dan menjalankannya di Google Cloud. Kursus ini dimulai dengan pengantar dasar tentang Google Cloud, lalu dilanjutkan dengan ringkasan container dan Kubernetes, arsitektur Kubernetes, dan operasi Kubernetes.

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This course helps learners create a study plan for the PCA (Professional Cloud Architect) 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 akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud. Melalui kombinasi video materi edukasi, demo, dan lab interaktif, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk membuat interkoneksi jaringan yang aman, load balancing, penskalaan otomatis, otomatisasi infrastruktur, serta layanan terkelola.

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Kursus akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud, dengan fokus pada Compute Engine. Melalui kombinasi video materi edukasi, demo, dan lab praktis, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk komponen infrastruktur seperti jaringan, sistem, dan layanan aplikasi. Kursus ini juga membahas cara men-deploy solusi praktis termasuk kunci enkripsi yang disediakan pelanggan, pengelolaan keamanan dan akses, kuota dan penagihan, serta pemantauan resource.

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Kursus akselerasi sesuai permintaan ini memperkenalkan peserta pada infrastruktur dan layanan platform yang komprehensif dan fleksibel yang disediakan oleh Google Cloud, dengan fokus pada Compute Engine. Melalui kombinasi video materi edukasi, demo, dan lab interaktif, peserta akan mengeksplorasi dan men-deploy berbagai elemen solusi, termasuk komponen infrastruktur seperti jaringan, virtual machine, dan layanan aplikasi. Anda akan mempelajari cara menggunakan Google Cloud melalui konsol dan Cloud Shell. Anda juga akan mempelajari peran arsitek cloud, pendekatan desain infrastruktur, dan konfigurasi networking virtual dengan Virtual Private Cloud (VPC), Project, Jaringan, Subnetwork, alamat IP, Rute, dan Aturan firewall.

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This workload aims to upskill Google Cloud partners to perform specific tasks for modernization using LookML on BigQuery. A proof-of-concept will take learners through the process of creating LookML visualizations on BigQuery. During this course, learners will be guided specifically on how to write Looker modeling language, also known as LookML and create semantic data models, and learn how LookML constructs SQL queries against BigQuery. At a high level, this course will focus on basic LookML to create and access BigQuery objects, and optimize BigQuery objects with LookML.

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This course introduces you to fundamentals, practices, capabilities and tools applicable to modern cloud-native application development using Google Cloud Run. Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to on Google Cloud using Cloud Run.design, implement, deploy, secure, manage, and scale applications

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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building and managing Google Cloud resources using Terraform.

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Planning for a Google Workspace Deployment is the final course in the Google Workspace Administration series. In this course, you will be introduced to Google's deployment methodology and best practices. You will follow Katelyn and Marcus as they plan for a Google Workspace deployment at Cymbal. They'll focus on the core technical project areas of provisioning, mail flow, data migration, and coexistence, and will consider the best deployment strategy for each area. You will also be introduced to the importance of Change Management in a Google Workspace deployment, ensuring that users make a smooth transition to Google Workspace and gain the benefits of work transformation through communications, support, and training. This course covers theoretical topics, and does not have any hands on exercises. If you haven’t already done so, please cancel your Google Workspace trial now to avoid any unwanted charges.

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Selesaikan badge keahlian pengantar Membuat dan Mengelola Instance AlloyDB untuk menunjukkan keterampilan dalam hal berikut: melakukan operasi inti AlloyDB dan tugas, bermigrasi ke AlloyDB dari PostgreSQL, mengelola database AlloyDB, dan mempercepat kueri analisis menggunakan Columnar Engine AlloyDB.

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Selesaikan badge keahlian pengantar Membuat dan Mengelola Instance Bigtable untuk menunjukkan keterampilan dalam hal berikut: membuat instance, mendesain skema, mengkueri data, dan melakukan tugas administratif di Bigtable termasuk memantau performa serta mengonfigurasi penskalaan otomatis dan replikasi node.

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Dapatkan badge keahlian dengan menyelesaikan kursus tentang pengantar Membuat dan Mengelola Instance Cloud Spanner untuk menunjukkan keterampilan dalam: membuat dan berinteraksi dengan instance dan database Cloud Spanner; memuat database Cloud Spanner menggunakan berbagai teknik; mencadangkan database Cloud Spanner; menentukan skema dan memahami rencana kueri; serta men-deploy Aplikasi Web Modern yang terhubung ke instance Cloud Spanner.

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Ini adalah kursus pengantar pembelajaran mikro yang dimaksudkan untuk menjelaskan responsible AI, alasan pentingnya responsible AI, dan cara Google mengimplementasikan responsible AI dalam produknya. Kursus ini juga memperkenalkan 7 prinsip AI Google.

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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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Ini adalah kursus pengantar pembelajaran mikro yang membahas definisi model bahasa besar (LLM), kasus penggunaannya, dan cara menggunakan prompt tuning untuk meningkatkan performa LLM. Kursus ini juga membahas beberapa alat Google yang dapat membantu Anda mengembangkan aplikasi AI Generatif Anda sendiri.

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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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Welcome to "CCAI Conversational Design Fundamentals", the first course in the "Customer Experiences with Contact Center AI" series. In this course, learn how to design customer conversational solutions using Contact Center Artificial Intelligence (CCAI). You will be introduced to CCAI and its three pillars (Dialogflow, Agent Assist, and Insights), and the concepts behind conversational experiences and how the study of them influences the design of your virtual agent. After taking this course you will be prepared to take your virtual agent design to the next level of intelligent conversation.

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Want to turn your marketing data into insights and build dashboards? Bring all of your data into one place for large-scale analysis and model building. Get repeatable, scalable, and valuable insights into your data by learning how to query it and using BigQuery. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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Ingin membangun model ML dalam hitungan menit, bukan jam, hanya dengan menggunakan SQL? BigQuery ML memperluas akses machine learning dengan memungkinkan analis data membuat, melatih, mengevaluasi, dan memprediksi sesuatu dengan model machine learning menggunakan alat serta keterampilan SQL yang ada. Dalam rangkaian lab ini, Anda akan bereksperimen dengan beragam jenis model dan mempelajari ciri-ciri model yang baik.

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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.

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Dasar-Dasar Google Cloud: Infrastruktur Inti memperkenalkan konsep dan terminologi penting untuk bekerja dengan Google Cloud. Melalui video dan lab interaktif, kursus ini menyajikan dan membandingkan banyak layanan komputasi dan penyimpanan Google Cloud, bersama dengan resource penting dan alat pengelolaan kebijakan.

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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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This course explores the Geographic Information Systems (GIS), GIS Visualization, and machine learning enhancements to BigQuery.

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This course explores how to leverage Looker to create data experiences and gain insights with modern business intelligence (BI) and reporting.

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This course explores how to implement a streaming analytics solution using Dataflow and BigQuery.

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This course explores how to implement a streaming analytics solution using Pub/Sub.

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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataflow.

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This course continues to explore the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Cloud Data Fusion.

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This course explores the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataproc.

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Welcome to Optimize in BigQuery, where we map Enterprise Data Warehouse concepts and components to BigQuery and Google data services with a focus on optimization.

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In this course, you will receive technical training for Enterprise Data Warehouses solutions using BigQuery based on the best practices developed internally by Google’s technical sales and services organizations. The course will also provide guidance and training on key technical challenges that can arise when migrating existing Enterprise Data Warehouses and ETL pipelines to Google Cloud. You will get hands-on experience with real migration tasks, such as data migration, schema optimization, and SQL Query conversion and optimization. The course will also cover key aspects of ETL pipeline migration to Dataproc as well as using Pub/Sub, Dataflow, and Cloud Data Fusion, giving you hands-on experience using all of these tools for Data Warehouse ETL pipelines.

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Dalam kursus tingkat pemula ini, Anda akan mendapatkan praktik langsung dengan alat dan layanan dasar Google Cloud. Video opsional disediakan untuk memberikan konteks dan ulasan lebih lanjut mengenai konsep-konsep yang dibahas dalam lab ini. Dasar-Dasar Google Cloud adalah kursus pertama yang direkomendasikan bagi peserta kursus Google Cloud— Anda bisa mengikutinya dengan pengetahuan yang minim atau tanpa pengetahuan sama sekali tentang cloud, dan mendapatkan pengalaman praktis yang dapat diterapkan pada project Google Cloud pertama Anda setelah menyelesaikan kursus ini. Mulai dari menulis perintah Cloud Shell dan men-deploy virtual machine pertama Anda, hingga menjalankan aplikasi di Kubernetes Engine atau dengan load balancing, Dasar-Dasar Google Cloud merupakan pengantar utama untuk fitur dasar platform ini.

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This course is intended to give architects, engineers, and developers the skills required to help enterprise customers architect, plan, execute, and test database migration projects. Through a combination of presentations, demos, and hands-on labs participants move databases to Google Cloud while taking advantage of various services. This course covers how to move on-premises, enterprise databases like SQL Server to Google Cloud (Compute Engine and Cloud SQL) and Oracle to Google Cloud bare metal.

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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.

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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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