July 21, 2025 | 9 AM – 5 PM (EST)
Introduction to Data Engineering on Google Cloud
Kickstart your data journey and learn how to design, build, and manage data processing systems on Google Cloud.
This training helps you understand the core concepts of data engineering on Google Cloud. You will learn how to collect, transform, and publish data using BigQuery, Dataflow, and Pub/Sub. It also covers how to build data pipelines that scale, how to work with structured and unstructured data, and how to leverage machine learning tools within the Google Cloud ecosystem. This course is the ideal first step for aspiring data engineers who want hands-on experience with real cloud technologies.
48
Days
17
Hours
29
Minutes
for July 21, 2025
Date
July 21, 2025
Time
9 AM to 5 PM (EST)
Location
Online – Google Meet
Language
English
Speakers
1
Speaker
Mark Kerzner is a globally respected trainer, author, and technology thought leader with over two decades of experience in AI, cloud computing, and Big Data. Mark has delivered cutting-edge training in Google Cloud, AI/ML, cybersecurity, and modern cloud stacks to global enterprises, universities, and Fortune 500 clients.
Mark Kerzner
Who Should Attend
This course if for
- This course is designed for aspiring data engineers, developers, analysts, and tech professionals who want to start working with data solutions on Google Cloud. It is perfect for anyone who is new to cloud-based data engineering.
What You Need to Know
Prerequisites
Basic knowledge of the topic is beneficial.
Certification
After completing this course, you can prepare for the Google Cloud Certified – Professional Data Engineer certification.
If you pass the exam, you will:
• Receive the Google Cloud Certified – Professional Data Engineer certificate.
• Become a lifelong member of the Google Cloud community.
Program
The course includes presentations, demonstrations, and hands-on labs.
Module 1
Data Engineering Basics
- Get introduced to the role of a data engineer and how data is managed, processed, and transformed in the cloud.
Module 2
BigQuery Fundamentals
- Learn how to use BigQuery to analyze and query large-scale datasets using SQL-like syntax and optimized storage.
Module 3
Data Pipelines with Dataflow
- Understand how to create efficient, autoscaling pipelines for data transformation and real-time stream processing.
Module 4
Streaming Data with Pub/Sub
- Discover how to manage real-time data ingestion and processing using Google Cloud’s messaging service, Pub/Sub.
Module 5
Storage and Databases
- Explore the use of Cloud Storage, Firestore, and other GCP services to store structured and unstructured data effectively.
Module 6
Intro to Machine Learning on GCP
- Get a taste of integrating machine learning into your data workflows using tools like BigQuery ML and AutoML.
Reserve your spot
Reserve your spot and join this Free GCP Core Infrastructure Training via Google Meet.
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