Moisés Constantino Isneros
Menjadi anggota sejak 2021
Silver League
3800 poin
Dasar-Dasar Google Cloud
Earned Mei 23, 2022 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned Nov 25, 2021 EST
Rekayasa Data untuk Pembuatan Model Prediktif dengan BigQuery ML
Earned Nov 11, 2021 EST
Build a Certification Study Guide: PDE Exam Prep
Earned Nov 8, 2021 EST
Menyiapkan Data untuk ML API di Google Cloud
Earned Nov 4, 2021 EDT
Build Batch Data Pipelines on Google Cloud
Earned Nov 3, 2021 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned Okt 26, 2021 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned Okt 25, 2021 EDT
Build Streaming Data Pipelines on Google Cloud
Earned Okt 22, 2021 EDT
[DEPRECATED] Google Cloud Big Data and Machine Learning Fundamentals
Earned Agu 31, 2021 EDT
Understanding LookML in Looker
Earned Agu 18, 2021 EDT
Menyiapkan Data untuk Dasbor dan Laporan Looker
Earned Agu 18, 2021 EDT
[DEPRECATED] Building Advanced Codeless Pipelines on Cloud Data Fusion
Earned Agu 17, 2021 EDT
Membangun Pipeline Tanpa Kode di Cloud Data Fusion
Earned Agu 17, 2021 EDT
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.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
Selesaikan badge keahlian tingkat menengah Rekayasa Data untuk Pembuatan Model Prediktif dengan BigQuery ML untuk menunjukkan keterampilan Anda dalam hal berikut: membangun pipeline transformasi data ke BigQuery dengan Dataprep by Trifacta; menggunakan Cloud Storage, Dataflow, dan BigQuery untuk membangun alur kerja ekstrak, transformasi, dan pemuatan (ETL); serta membangun model machine learning menggunakan BigQuery ML.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
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 Managed Service for Apache Spark, dan memanggil beberapa ML API, termasuk Cloud Natural Language API, Google Cloud Speech-to-Text API, dan Video Intelligence API.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
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.
Pelajari lebih lanjut
In this quest, you will get hands-on experience with LookML in Looker. You will learn how to write LookML code to create new dimensions and measures, create derived tables and join them to Explores, filter Explores, and define caching policies in LookML.
Pelajari lebih lanjut
Selesaikan badge keahlian pengantar Menyiapkan Data untuk Dasbor dan Laporan Looker untuk menunjukkan keterampilan dalam hal berikut: memfilter, mengurutkan, dan melakukan pivot pada data; menggabungkan hasil dari sejumlah Eksplorasi Looker; serta menggunakan fungsi dan operator untuk membangun dasbor dan laporan Looker untuk analisis dan visualisasi data.
Pelajari lebih lanjut
This advanced-level Quest builds on its predecessor Quest, and offers hands-on practice on the more advanced data integration features available in Cloud Data Fusion, while sharing best practices to build more robust, reusable, dynamic pipelines. Learners get to try out the data lineage feature as well to derive interesting insights into their data’s history.
Pelajari lebih lanjut
Kursus ini menawarkan praktik langsung dengan Cloud Data Fusion, platform integrasi data tanpa kode berbasis cloud. Developer ETL, Data Engineer, dan Analis dapat memperoleh manfaat besar dari transformasi dan konektor bawaan untuk membangun dan men-deploy pipeline mereka tanpa perlu menulis kode. Kursus ini dimulai dengan lab panduan memulai yang memperkenalkan UI Cloud Data Fusion kepada peserta. Peserta dapat mencoba menjalankan pipeline batch dan real time serta menggunakan plugin Wrangler untuk melakukan beberapa transformasi menarik pada data.
Pelajari lebih lanjut
