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Bruno Silva Saba

Member since 2021

Bronze League

3210 points
Analyzing and Visualizing Data in Looker - Locales Earned Jan 4, 2023 EST
Implementing Cloud Load Balancing for Compute Engine Earned May 17, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned May 13, 2022 EDT
Set Up an App Dev Environment on Google Cloud Earned Apr 27, 2022 EDT
Baseline: Infrastructure Earned Apr 27, 2022 EDT
BigQuery for Data Analysis I Earned Feb 23, 2022 EST
Prepare Data for ML APIs on Google Cloud Earned Nov 12, 2021 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned Oct 29, 2021 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned Oct 8, 2021 EDT

This course, Analyzing and Visualizing Data in Looker - Locales, is intended for non-English learners only. If you wish to take this content in English, please enroll in Analyzing and Visualizing Data in Looker. This course enables you to upscale your data warehouse solutions with an introduction to Looker for data exploration, analysis, and visualization. Upon completing this course, you will be able to start exploring your organization’s Looker instance and analyzing the available data to create shareable visualizations and reports.

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Complete the introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.

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Complete the intermediate Engineer Data for Predictive Modeling with BigQuery ML skill badge to demonstrate skills in the following: building data transformation pipelines to BigQuery using Dataprep by Trifacta; using Cloud Storage, Dataflow, and BigQuery to build extract, transform, and load (ETL) workflows; and building machine learning models using BigQuery ML.

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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.

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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.

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Welcome Gamers! Learn BigQuery and Cloud SQL, all while having fun! You will compete to see who can finish the game with the highest score. Earn the points by completing the steps in the lab.... and get bonus points for speed! Be sure to click "End" when you're done with each lab to get the maximum points. All players will be awarded the game badge.

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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.

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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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