Preparing for your Professional Data Engineer Journey
Earned août 31, 2022 EDT
Prepare Data for ML APIs on Google Cloud
Earned août 29, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned août 18, 2022 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned août 13, 2022 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned août 12, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned août 8, 2022 EDT
This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.
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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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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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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.
En savoir plus
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.
En savoir plus
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.
Preparing for your Professional Data Engineer Journey
Earned août 31, 2022 EDT
Prepare Data for ML APIs on Google Cloud
Earned août 29, 2022 EDT
Engineer Data for Predictive Modeling with BigQuery ML
Earned août 18, 2022 EDT
Build Data Lakes and Data Warehouses on Google Cloud
Earned août 13, 2022 EDT
Implementing Cloud Load Balancing for Compute Engine
Earned août 12, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals
Earned août 8, 2022 EDT