Hands-On MLOps on Azure
Automate, secure, and scale ML workflows with the Azure ML CLI, GitHub, and LLMOps
Created by Banibrata De
Gain practical skills to automate, secure, and scale machine learning workflows using Azure ML CLI, GitHub, and multi-cloud strategies. Explore hands-on techniques for deploying, monitoring, and managing both traditional models and large language models in real-world scenarios.
Packt | Aug 2025 | 276 min
What You Will Learn
You will work through practical projects and guided workflows that mirror real industry scenarios. Each step builds on the last, moving from pipeline creation to CI/CD automation and LLMOps strategies. By applying tools and techniques in context, you'll develop skills that translate directly to production environments.
Key Features
- Create reproducible ML pipelines using Azure ML CLI and GitHub Actions
- Automate deployment, monitoring, and governance for scalable ML workflows
- Apply LLMOps to operationalize and manage large language models across clouds
Target Audience
Ideal for DevOps engineers, cloud professionals, and SREs who manage or want to manage machine learning models at scale. If you already understand ML basics and want to streamline operations, or you're new to MLOps and need a practical foundation, you'll find actionable guidance tailored to your needs.
