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This training is intended for big data practitioners who want to further their understanding of Dataflow in order to advance their data processing applications. Beginning with foundations, this training explains how Apache Beam and Dataflow work together to meet your...

In this course, we discuss challenges with data integration and the need for a data integration platform (middleware). We then discuss how Cloud Data Fusion can help to effectively integrate data from a variety of sources and formats and generate insights. We take a...

In this course, you learn about the internals of BigQuery and best practices for designing, optimizing, and administering your data warehouse. Through a combination of lectures, demos, and labs, you learn about BigQuery architecture and how to design optimal storage...

Explore the technologies, products, and tools available to build an ML model, an ML pipeline, and a generative AI project on Google Cloud

Through a combination of lectures, hands-on labs, and supplemental materials, you will learn how to design, implement, deploy, secure, manage, and scale applications on Google Cloud using Cloud Run.

Ready to become a Google Data Engineer? This Certification Prep Guide provides everything you need to know about the current Google Certified Professional Data Engineer certification and offers helpful tips that IT professionals can use when preparing for the Google Data Engineer exam. Start here!

Learn to design GCP deployments.

This course gives participants a broad study of networking options on Google Cloud Platform. You will explore and deploy GCP networking technologies, such as Google Virtual Private Cloud (VPC) networks, subnets, firewalls, interconnection among networks, load balancing, Cloud DNS, and Cloud CDN.

Discuss the available infrastructure components of Google Cloud Platform and how they provide a powerful and flexible foundation on which to build your applications.

Learn the value of Google Cloud Platform.