Dataproc is Google’s managed Hadoop offering on the cloud. This course teaches you how the separation of storage and compute allows you to utilize clusters more efficiently purely for processing data and not for storage.

Dataflow represents a fundamentally different approach to Big Data processing than computing engines such as Spark. Dataflow is serverless and fully-managed, meaning that provisioning resources and scaling can be transparent to the data architect.

This course introduces you to essential concepts in handling vast datasets, equipping you with the ability to implement an effective data solution.

Learn the fundamentals of working with big data with PySpark.

Learn about the architecture and management of big data systems.

This course brings any Big Data newbie up to speed on one of the most widely used open-source platform to build data pipelines - Apache Kafka.

Explore advanced topics in big data technologies, architectures, and analytical methods.

Learn how to apply software solutions for different systems and Big Data needs to your IoT designs.

Learn how to build scalable model pipelines for data science in production environments, focusing on best practices for deployment and management.

Distributed systems are the backbone of modern society but entail challenges in areas such as complexity and energy-use. Discover distributed systems from first principles, understand the architectures and techniques derived from them and explore examples of current practical use.

Grow from being a Unix novice to Unix wizard status! Process big data, analyze software code, run DevOps tasks and excel in your everyday job through the amazing power of the Unix shell and command-line tools.

Gain practical knowledge on how to deploy and manage a Hadoop cluster for big data processing.