Google Cloud Professional Data Engineer: Get Certified 2022 (Udemy.com)
Build scalable, reliable data pipelines, databases, and machine learning applications.
Created by: Dan Sullivan
Last updated May 2025
What you will 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.
How it compares
Against the other 118 rated Udemy courses in Cloud Computing on CourseDuck:
- Rating4.5 out of 5higher than 44% of them
- Reviews4,690#16 of 119 by number of reviews
- Length6.3 hourslonger than 59% of them
- Last updatedMay 2025more recently than 60% of them
Course Description
The need for data engineers is constantly growing and certified data engineers are some of the top paid certified professionals. Data engineers have a wide range of skills including the ability to design systems to ingest large volumes of data, store data cost-effectively, and efficiently process and analyze data with tools ranging from reporting and visualization to machine learning. Earning a Google Cloud Professional Data Engineer certification demonstrates you have the knowledge and skills to build, tune, and monitor high performance data engineering systems.
This course is designed and developed by the author of the official Google Cloud Professional Data Engineer exam guide and a data architect with over 20 years of experience in databases, data architecture, and machine learning. This course combines lectures with quizzes and hands-on practical sessions to ensure you understand how to ingest data, create a data processing pipelines in Cloud Dataflow, deploy relational databases, design highly performant Bigtable, BigQuery, and Cloud Spanner databases, query Firestore databases, and create a Spark and Hadoop cluster using Cloud Dataproc.
The final portion of the course is dedicated to the most challenging part of the exam: machine learning. If you are not familiar with concepts like backpropagation, stochastic gradient descent, overfitting, underfitting, and feature engineering then you are not ready to take the exam. Fortunately, this course is designed for you. In this course we start from the beginning with machine learning, introducing basic concepts, like the difference between supervised and unsupervised learning. We’ll build on the basics to understand how to design, train, and evaluate machine learning models. In the process, we’ll explain essential concepts you will need to understand to pass the Professional Data Engineer exam. We'll also review Google Cloud machine learning services and infrastructure, such as BigQuery ML and tensor processing units.
The course includes a 50 question practice exam that will test your knowledge of data engineering concepts and help you identify areas you may need to study more.
By the end of this course, you will be ready to use Google Cloud Data Engineering services to design, deploy and monitor data pipelines, deploy advanced database systems, build data analysis platforms, and support production machine learning environments.
ARE YOU READY TO PASS THE EXAM? Join me and I'll show you how!
Instructor Details
- 4.5 Rating
4,690 Reviews
Dan Sullivan
Dan Sullivan is a cloud architect, systems developer, and author of the Official Google Cloud Professional Architect Study Guide, the Official Google Cloud Professional Data Engineer Study Guide, and the Official Google Cloud Associate Engineer Study Guide.
He is an experienced trainer and his online training courses have been viewed over 1 million times. Dan has extensive experience in multiple fields, including cloud architecture, data architecture and modeling, machine learning, data science, and streaming analytics.
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Reviews
By Helder Varela on 8/1/2023
I liked the course and I think the instructor did a good job. In some parts I think is needed some update specifically the Google Cloud interface, because as of July / August 2023, the interface is different in some services. It is not that major but it does not help sometimes.
By Alok Tripathi on 4/23/2023
I have finished my Data Engineering certificate. It was a helpful course that covered various data engineering topics and prepared me well for certification. It's a great resource to refer back to for future reference.
By John Hyaduck on 1/27/2022
The presenter mentioned you can set some database options but never said what those were. (They were in the notes) VertexAI was in beta at the time this course was published. I understand that the ML elements for this version and the next in 2022 share the same foundations but I think there should be some mention in the course that changes (or services offered) for AI/ML are evolving.
By Skylar Youngblood on 12/12/2021
It is a great course but it doesn't have labs which is fine for me since I have done lots of labs in GCP but it isn't for someone with no GCP experience. I love the detail in BigTable, DataProc, and ML topics. I would like to see more from pipeline migration. On the practice exams I've done there is always a couple questions on Storage Transfer Service. That is a big topic I would suggest adding since there are so many different services offered. I mainly bought this course for the practice exam and to cover the gaps of my learning which is ML.
By ZINE EDDINE ATIK on 10/31/2021
The course is very informative and straightforward but it's a solid introduction with pointers to external resources rather then a full official guide to hack the GCP Data Engineer certification ! The Test exam with 50 questions at the last of the course is very useful !
By Sameer Dongare on 7/17/2021
I think the course not only covered all the topics required for certification but at the same time it also highlighted the important points of each topic.
By Nishanta Banik on 5/13/2021
Hello Dan, it was an awesome course. Thanks for compiling & making it available for all of us. Kindly upload the Presentation Slide. It would be really helpful...
By Anonymized User on 12/2/2020
The course is good. I will recommend this course who are seriously considering to appear for GCP Professional Data Engineer Certification. Before going through the course material, make sure that you understand the basic Data Processing services in GCP. The language used by the author is very technical and make sure that you understand the terminologies well before taking this course.
By Heidi C on 11/14/2020
This is a great course with comprehensive lectures. I would highly recommend for anyone getting certified or wanting to become more confident with all of the data storage and processing solutions in GCP.
By Vamsidhar Muggulla on 8/19/2020
This course is for beginners who are getting started with GCP for Data Engineering. Can have more clearer explaination with examples, people without computer science background will struggle a lot. The course covers maximum topics needed but not much in detail, poor video quality especially text from GCP console, this may affect users eyes a lot. I'm just exploring, this is my first course in the site just checking how it works and I'm not serious about certification or anything.
Quality Score
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Overall Score : 90 / 100












