Mettez en pratique vos compétences dans la console Google Cloud
Wahyu Tri Wibowo
Date d'abonnement : 2019
Ligue d'Or
9715 points
Build a Data Warehouse with BigQuery
Earned mai 30, 2024 EDT
Derive Insights from BigQuery Data
Earned mai 23, 2024 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned mai 20, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned mai 17, 2024 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned avr. 20, 2024 EDT
Streaming Analytics into BigQuery
Earned avr. 7, 2024 EDT
Deploy Kubernetes Applications on Google Cloud
Earned oct. 14, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned jan. 18, 2022 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned jan. 17, 2022 EST
[DEPRECATED] Data Engineering
Earned jan. 14, 2022 EST
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.
En savoir plus
Complete the introductory Derive Insights from BigQuery Data skill badge course to demonstrate skills in the following: Write SQL queries.Query public tables.Load sample data into BigQuery.Troubleshoot common syntax errors with the query validator in BigQuery.Create reports in Looker Studio by connecting to BigQuery data.
En savoir plus
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.
En savoir plus
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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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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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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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.
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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.
En savoir plus
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.
En savoir plus
This advanced-level quest is unique amongst the other catalog offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Professional Data Engineer Certification. From Big Query, to Dataprep, to Cloud Composer, this quest is composed of specific labs that will put your Google Cloud data engineering knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, you will need other preparation, too. The exam is quite challenging and external studying, experience, and/or background in cloud data engineering is recommended. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of the Engineer Data in the Google Cloud to receive an exclusive Google Cloud digital badge.
Build a Data Warehouse with BigQuery
Earned mai 30, 2024 EDT
Derive Insights from BigQuery Data
Earned mai 23, 2024 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned mai 20, 2024 EDT
Prepare Data for ML APIs on Google Cloud
Earned mai 17, 2024 EDT
Smart Analytics, Machine Learning, and AI on Google Cloud
Earned avr. 20, 2024 EDT
Streaming Analytics into BigQuery
Earned avr. 7, 2024 EDT
Deploy Kubernetes Applications on Google Cloud
Earned oct. 14, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned jan. 18, 2022 EST
Engineer Data for Predictive Modeling with BigQuery ML
Earned jan. 17, 2022 EST
[DEPRECATED] Data Engineering
Earned jan. 14, 2022 EST