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Federico P

Member since 2023

Diamond League

8780 points
Streaming Analytics into BigQuery Earned מאי 20, 2024 EDT
Share Data Using Google Data Cloud Earned מאי 20, 2024 EDT
Build a Data Warehouse with BigQuery Earned מאי 20, 2024 EDT
Prepare Data for ML APIs on Google Cloud Earned מאי 17, 2024 EDT
Gemini for Data Scientists and Analysts Earned מאי 6, 2024 EDT
Google Workspace with Gemini: Foundations of Your AI Workflow Earned מאי 2, 2024 EDT
Engineer Data for Predictive Modeling with BigQuery ML Earned אפר 12, 2024 EDT

Earn a skill badge by completing the Streaming Analytics into BigQuery skill badge course, where you use Pub/Sub, Dataflow and BigQuery together to stream data for analytics.

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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.

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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.

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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 Managed Service for Apache Spark, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.

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In this course, you learn how Gemini, a generative AI-powered collaborator from Google Cloud, helps analyze customer data and predict product sales. You also learn how to identify, categorize, and develop new customers using customer data in BigQuery. Using hands-on labs, you experience how Gemini improves data analysis and machine learning workflows.

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Google Workspace with Gemini provides customers with generative AI features in Google Workspace. Here, you will learn about the key features of Gemini and how they can be used to improve productivity and efficiency. Continue building your skills in the full Google Workspace with Gemini learning path, and explore other content in the Gemini Agent Ready (GEAR) program.

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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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