Google Cloud Professional Data Engineer: Get Certified 2020

Build scalable, reliable data pipelines, databases, and machine learning applications.

What you’ll learn

How to pass the Google Cloud Professional Data Engineer Exam
Build scalable, reliable data pipelines
Choose appropriate storage systems, including relational, NoSQL and analytical databases
Apply multiple types of machine learning techniques to different use cases
Deploy machine learning models in production
Monitor data pipelines and machine learning models
Design scalable, resilient distributed data intensive applications
Migrate data warehouse from on-premises to Google Cloud
Evaluate and improve the quality of machine learning models
Grasp fundamental concepts in machine learning, such as backpropagation, feature engineering, overfitting and underfitting.

Understanding of basic cloud computing concepts such as virtual machines and databases.
One year or more experience working with data management or data analysis

Cloud engineers and architects who want to pass the Professional Data Engineer exam
Data engineers who want to learn about Google’s advanced tools and services for data engineering
Data scientists and data engineers who want to understand machine learning concepts
Cloud application developers who want to use machine learning to build applications
Devops engineers who need to support data engineering pipelines and machine learning models

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