Automate Cloud Workflows with Python Scripting

Overview

Automate Cloud Workflows with Python Scripting is an intermediate course designed for developers, ML engineers, and data scientists seeking to eliminate manual, error-prone cloud tasks. Modern ML workflows often involve multiple complex steps—provisioning a GPU, running a training job, and saving the model—all of which are inefficient to perform by hand. This course teaches you how to automate this entire process from end to end using Python. You will learn to write powerful scripts that programmatically manage cloud resources, execute multi-step computational jobs, and ensure data persistence. Through hands-on labs, you will master using Python’s argparse library to create flexible, reusable scripts configurable from the command line, and you’ll apply Infrastructure as Code (IaC) principles to build scalable, resilient, and cost-effective solutions. By the end of this course, you will be equipped to transform your manual cloud processes into robust, automated pipelines ready for production.

Syllabus

Cloud Automation and Parameterized Scripting

In this module, you will learn the essential skills to automate cloud tasks using Python. We will cover the entire automation lifecycle, from understanding the high cost of manual work to writing a configurable, end-to-end script that can provision resources, execute a task, and reliably manage data by saving it to persistent storage.