The Google Cloud Professional Data Engineer is able to harness the power of Google’s big data capabilities and make data-driven decisions by collecting, transforming, and visualizing data. Through designing, building, maintaining, and troubleshooting data processing systems with a particular emphasis on the security, reliability, fault tolerance, scalability, fidelity, and efficiency of such systems, a Google Cloud data engineer is able to put these systems to work.This course will prepare you for the Google Cloud Professional Data Engineer exam by diving into all of Google Cloud’s data services. With interactive demonstrations and an emphasis on hands-on work, you will learn how to master each of Google’s big data and machine learning services and become a certified data engineer on Google Cloud.Updated to the latest Google exam requirements in July 2019, this course will prepare you to succeed in your quest to become Google Cloud Certified!
Overview
Syllabus
- Getting Started
- Foundational Concepts
- Cloud SQL
- Datastore
- Bigtable
- Cloud Spanner
- Real Time Messaging with Cloud Pub/Sub
- Data Pipelines with Cloud Dataflow
- Dataproc
- BigQuery
- Machine Learning
- AI Platform (Formerly Cloud ML Engine)
- Pretrained Machine Learning API's
- Datalab
- Cleaning Your Data with Dataprep
- Building Data Visualizations with Data Studio
- Orchestrating Data Workflows with Cloud Composer
- Final Steps
Taught by
Matthew Ulasien
Related Courses
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Google Certified Professional Data Engineer
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Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud
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Google Cloud Certified Professional Cloud Architect (LA)
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Preparing for Google Cloud Certification: Cloud Data Engineer
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Engineer Data in Google Cloud
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Google Cloud Big Data and Machine Learning Fundamentals
