Cloud Engineer Courses

This course focuses on the principles and practices around Devops. The course will introduce you to the Continuous Integration, Continuous Delivery and Continuous Deployment. You will learn how to use Jenkins to automate the build process and how to use Docker to automate the deployment process. You will also learn how to use Kubernetes to manage the deployment of your containers. You will also learn how to use Terraform to automate the deployment of your infrastructure.

Through a series of use case scenarios and practical learning, you’ll learn to identify services and features to build resilient, secure, and highly available IT solutions in the AWS Cloud.

This course gives developers exposure to and practice with best practices for building serverless applications using AWS Lambda and other services in the AWS serverless platform.

MLOps Engineering on AWS will help you bring DevOps-style practices into the building, training, and deployment of ML models. ML data platform engineers, DevOps engineers, and developers/operations staff with responsibility for operationalizing ML models will learn to address the challenges associated with handoffs between data engineers, data scientists, software developers, and operations through the use of tools, automation, processes, and teamwork. By the end of the course, go from learning to doing by building an MLOps action plan for your organization.

Do you want to develop business insights from siloed data stores with the help of a data lake? Our new one-day classroom course, Building Data Lakes on AWS, will help you practice building and securing a data lake in a hands-on environment.

The course dives deep into the Amazon Redshift service and the current thinking in building and operating data analytics pipelines to turn data into insights.