Modern organizations generate massive volumes of data from applications, IoT devices, customer interactions, and digital platforms. To process, store, and analyze this data efficiently, companies rely on scalable cloud data platforms.

This course introduces the core concepts of cloud data engineering, including building data pipelines, processing large datasets, and designing scalable data architectures using cloud services.

Learners will explore how major cloud providers such as AWS, Microsoft Azure, and Google Cloud Platform (GCP) support data engineering through services like data lakes, data warehouses, streaming systems, and managed ETL tools.

Through real-world examples and architecture diagrams, students will learn how to design and implement modern data pipelines capable of handling large-scale analytics and machine learning workloads.

By the end of this course, learners will understand how to build cloud-native data platforms used in modern data-driven organizations.