Course Description
This course is designed to help IT professionals prepare for the Google Certified Professional—Data Engineer Certification Exam.
In this course, we review the exam guidelines and product strategies for the major Google Cloud Platform storage, big data, and analytics services covered by the exam. We examine concepts related to data transformation, real-time processing, visualization, and machine learning and best practices to solve common problems.
This course assumes prior knowledge of Google Cloud Platform (GCP) and is not an introduction to GCP.
Learning ObjectivesIT professionals interested in obtaining the Google Certified Professional—Data Engineer certification. Data scientists and machine learning practitioners who want to learn more about taking optimal advantage of the big data services provided by Google Cloud Platform will also benefit from this course.
PrerequisitesPrior to taking the Google Cloud Data Engineer Professional exam, students should have prior experience working with Google Cloud Platform big data services. The exam tests one’s understanding of architecting secure and reliable business solutions that leverage Google Cloud Platform for storing, analyzing, and visualizing data. We strongly recommend taking the
Included with this course are sample quizzes and numerous case study examples that will help you both prepare for the exam, and have a greater level of understanding of how to build data analytics and machine learning systems on Google Cloud Platform.
Module 1: Data Engineer Certification Overview
Module 2: Google Big Data Fundamentals
Module 3: Storing Binary Data
Module 4: Storing Relational Data
Module 5: Managed NoSQL Solutions
Module 6: Big Data Processing and Analytics
Module 7: Data Processing Pipelines
Module 8: Visualization and Analytics
Module 9: Machine Learning Fundamentals
Module 10: Machine Learning on Google Cloud Platform
Module 11: Case Studies