Nam Phạm Văn
Membro dal giorno 2021
Campionato Argento
4900 punti
Membro dal giorno 2021
Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.
This on-demand course equips students to understand, configure, and maintain multi-cluster Kubernetes infrastructures using Anthos GKE, and Istio-based service mesh, whether deployed with Anthos on Google Cloud or with Anthos deployed on VMware. This is the third, and final, course of the Architecting Hybrid Cloud Infrastructure with Anthos series. Completion of the Architecting with Google Kubernetes Engine path is a prerequisite for this course.
Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
This on-demand course equips students to understand and adopt Istio-based service-mesh with Anthos for centralized observability, traffic management, and service-level security. This is the second course of the Architecting Hybrid Cloud Infrastructure with Anthos series. After completing this course, learners should continue to the Hybrid Cloud Multi-Cluster with Anthos course. Completion of the Architecting with Google Kubernetes Engine path is a prerequisite for this course.
Welcome to Hybrid Cloud Infrastructure Foundations with Anthos! This is the first course of the Architecting Hybrid Cloud Infrastructure with Anthos path. Anthos enables you to build and manage modern applications, and gives you the freedom to choose where to run them. Anthos gives you one consistent experience in both your on-premises and cloud environments. During this course, you will be presented with modules that will take you through skills that you will use as an architect or administrator running Anthos environments. The modules in this course include videos, hands-on labs, and links to helpful documentation.
Earn a skill badge by completing the Share Data Using Google Data Cloud skill badge course, where you will gain practical experience with Google Cloud Data Sharing Partners, which have proprietary datasets that customers can use for their analytics use cases. Customers subscribe to this data, query it within their own platform, then augment it with their own datasets and use their visualization tools for their customer facing dashboards.
Kubernetes è il sistema di orchestrazione dei container più diffuso e Google Kubernetes Engine è stato progettato specificamente per supportare i deployment Kubernetes gestiti in Google Cloud. In questo corso di livello avanzato, potrai esercitarti nella configurazione di immagini e container Docker e nel deployment di applicazioni Kubernetes Engine complete. Grazie a questo corso, apprenderai le competenze pratiche necessarie per integrare l'orchestrazione dei container nel tuo workflow. Stai cercando un Challenge Lab pratico per dimostrare le tue abilità e convalidare le tue conoscenze? Dopo aver completato questo corso, termina il Challenge Lab aggiuntivo alla fine del corso Esegui il deployment di applicazioni Kubernetes su Google Cloud per ricevere un esclusivo badge digitale Google Cloud.
Blockchain and related technologies, such as distributed ledger and distributed apps, are becoming new value drivers and solution priorities in many industries. In this course you will gain hands-on experience with distributed ledger and the exploration of blockchain datasets in Google Cloud. It brings the research and solution work of Google's Allen Day into self-paced labs for you to run and learn directly. Since this course uses advanced SQL in BigQuery, a SQL-in-BigQuery refresher lab is at the start.
Complete the intermediate Manage Data Models in Looker skill badge course to demonstrate skills in the following: maintaining LookML project health; utilizing SQL runner for data validation; employing LookML best practices; optimizing queries and reports for performance; and implementing persistent derived tables and caching policies.
Completa il corso introduttivo con badge delle competenze Genera insight dai dati BigQuery per dimostrare le tue competenze nei seguenti ambiti: scrivere query SQL, eseguire query su tabelle pubbliche, caricare dati di esempio in BigQuery, risolvere i problemi di sintassi comuni con lo strumento di convalida query in BigQuery e creare report in Data Studio collegando ai dati di BigQuery.
In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.
Questo corso presenta i prodotti e i servizi per big data e di machine learning di Google Cloud che supportano il ciclo di vita dai dati all'IA. Esplora i processi, le sfide e i vantaggi della creazione di una pipeline di big data e di modelli di machine learning con Vertex AI su Google Cloud.
This is the second course in the Data to Insights course series. Here we will cover how to ingest new external datasets into BigQuery and visualize them with Looker Studio. We will also cover intermediate SQL concepts like multi-table JOINs and UNIONs which will allow you to analyze data across multiple data sources. Note: Even if you have a background in SQL, there are BigQuery specifics (like handling query cache and table wildcards) that may be new to you. After completing this course, enroll in the Achieving Advanced Insights with BigQuery course.
Earn the intermediate skill badge by completing the Build and Deploy Machine Learning Solutions on Vertex AI skill badge course, where you learn how to use Google Cloud's Vertex AI platform, AutoML, and custom training services to train, evaluate, tune, explain, and deploy machine learning models.