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Rafael Mello Vieira

Menjadi anggota sejak 2022

Silver League

3400 poin
Serverless Data Processing with Dataflow: Foundations Earned Mei 24, 2023 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud Earned Mei 22, 2023 EDT
Build Streaming Data Pipelines on Google Cloud Earned Mei 18, 2023 EDT
Build Batch Data Pipelines on Google Cloud Earned Apr 28, 2023 EDT
Preparing for your Professional Data Engineer Journey Earned Mar 25, 2023 EDT
Build Data Lakes and Data Warehouses on Google Cloud Earned Jan 24, 2023 EST
Google Cloud Big Data and Machine Learning Fundamentals Earned Jan 15, 2023 EST
Menyiapkan Data untuk ML API di Google Cloud Earned Jan 10, 2023 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales Earned Jan 9, 2023 EST
Membangun Jaringan Google Cloud yang Aman Earned Jan 7, 2023 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud - Locales Earned Jan 6, 2023 EST
Menyiapkan Lingkungan Pengembangan Aplikasi di Google Cloud Earned Jan 4, 2023 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales Earned Jan 4, 2023 EST
Mengimplementasikan Cloud Load Balancing untuk Compute Engine Earned Jan 1, 2023 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales Earned Des 29, 2022 EST

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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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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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

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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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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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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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Selesaikan badge keahlian pengantar Menyiapkan Data untuk ML API di Google Cloud untuk menunjukkan keterampilan Anda dalam hal berikut: menghapus data dengan Dataprep by Trifacta, menjalankan pipeline data di Dataflow, membuat cluster dan menjalankan tugas Apache Spark di Dataproc, dan memanggil beberapa ML API, termasuk Cloud Natural Language API, Google Cloud Speech-to-Text API, dan Video Intelligence API.

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This course, Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud. The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Googl…

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Dapatkan badge keahlian dengan menyelesaikan kursus Membangun Jaringan Google Cloud yang Aman yang membahas resource yang terkait dengan beberapa jaringan untuk membangun, menskalakan, dan mengamankan aplikasi Anda di Google Cloud.

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This course, Google Cloud Computing Foundations: Networking & Security in Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Networking & Security in Google Cloud. The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Dat…

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Dapatkan badge keahlian dengan menyelesaikan kursus Menyiapkan Lingkungan Pengembangan Aplikasi di Google Cloud, yang memungkinkan Anda mempelajari cara membangun dan menghubungkan infrastruktur cloud yang berpusat pada penyimpanan menggunakan kemampuan dasar teknologi berikut: Cloud Storage, Identity and Access Management, Cloud Functions, dan Pub/Sub.

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This course, Google Cloud Computing Foundations: Infrastructure in Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Infrastructure in Google Cloud. The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google C…

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Selesaikan badge keahlian pengantar Mengimplementasikan Cloud Load Balancing untuk Compute Engine untuk menunjukkan keterampilan dalam hal berikut: membuat dan men-deploy virtual machine di Compute Engine serta mengonfigurasi load balancer aplikasi dan jaringan.

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This course, Google Cloud Computing Foundations: Cloud Computing Fundamentals - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Google Cloud Computing Foundations: Cloud Computing Fundamentals .The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud …

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