Google Cloud Professional Data Engineer: Get Certified 2022

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

Created by: Dan Sullivan
Cloud Architect, Data Engineer and Author

What Will I 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.

Requirements

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

Target audience

• 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