Google Data Engineer Exam – Professional Certification Preparation
Description
This Learning Path is designed to help you prepare for the Google Certified Professional Data Engineer Exam. Even if you don't plan to take the Exam, these courses will help you gain a solid understanding of the various data processing components of the Google Cloud Platform.
At the heart of Google’s big data services is BigQuery, a managed data warehouse in the cloud. The first three courses will show you how to load and query data in BigQuery, optimize BigQuery’s performance, and visualize your data.
The next three courses will show you how to process your data. First, you will use Cloud Machine Learning Engine to train neural networks to perform predictive analytics. Next, you’ll use Cloud Dataflow and Cloud Dataproc to build data processing pipelines that transform and summarize your data using Apache Beam, Hadoop, and Spark.
The final course will introduce you to Bigtable, Google’s revolutionary NoSQL database. It will show you how to take advantage of Bigtable’s high performance for big data applications.
All of these courses include hands-on demos you can do yourself. Then you can test what you’ve learned by taking the practice exam.
Learning Objectives
- Design a data processing system
- Build and maintain data structures and databases
- Analyze data and enable machine learning
- Optimize data representations, data infrastructure performance, and cost
- Ensure reliability of data processing infrastructure
- Visualize data
- Design secure data processing systems
Prerequisites
- Basic database knowledge
Intended Audience
- Data professionals
- People studying for the Google Professional Data Engineer exam
Feedback
If you have thoughts or suggestions for this Learning Path, please contact Cloud Academy at support@cloudacademy.com.
Updates
- Apr. 9, 2018: Added "Building Convolutional Neural Networks on Google Cloud" course
Certificate
Learning Path Steps
BigQuery is Google’s managed data warehouse in the cloud. BigQuery is incredibly fast. It can scan billions of rows in seconds. It’s also surprisingly inexpensive and easy to use. Querying terabytes of data costs only pennies and you only pay for what you u...
BigQuery is Google's incredibly fast, secure, and surprisingly inexpensive data warehouse, but there are ways to make it even faster, cheaper, and more secure. Here are some examples of what you will learn in this course: BigQuery can process billions o...
Course Description Google Data Studio is a web-based application for creating reports and dashboards. It’s an easy-to-use tool for displaying your data visually. It was designed to help Google Analytics users create custom reports, but it can now read data...
Machine learning is a hot topic these days and Google has been one of the biggest newsmakers. Recently, Google’s AlphaGo program beat the world’s No. 1 ranked Go player. That’s impressive, but Google’s machine learning is being used behind the scenes every ...
Course Description Once you know how to build and train neural networks using TensorFlow and Google Cloud Machine Learning Engine, what’s next? Before long, you’ll discover that prebuilt estimators and default configurations will only get you so far. To op...
Most organizations are already gathering and analyzing big data or plan to do so in the near future. One common way to process huge datasets is to use Apache Hadoop or Spark. Google even has a managed service for hosting Hadoop and Spark. It’s called Cloud ...
Course Description Google Cloud Dataproc is a managed service for running Apache Hadoop and Spark jobs. It can be used for big data processing and machine learning. But you could run these data processing frameworks on Compute Engine instances, so what do...
Bigtable is an internal Google database system that’s so revolutionary that it kickstarted the NoSQL industry. In the mid 2000’s, Google had a problem. The web indexes behind its search engine had become massive and it took a long time to keep rebuilding th...
This short video gives you a list of some of the other resources you should review before taking the Google Certified Professional Data Engineer exam.
GCP Data Engineer Certification Preparation
Changelog
Added preparation exam
About the Author
Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).