Real-world End to End Machine Learning Ops on Google Cloud
Master ML Ops & CI/CD Pipelines with Google Cloud's Advanced AI and Workflow Tools
Created by Siddharth Raghunath
Explore the full machine learning operations lifecycle on Google Cloud, from setting up automated pipelines to deploying scalable models. Work directly with tools like Vertex AI, Kubeflow, and Cloud Run to streamline and automate your ML workflows. Build practical skills that help you deliver production-ready solutions faster and with greater confidence.
Packt | May 2025 | 364 min
What You Will Learn
You will work through hands-on labs and real-world projects that mirror the challenges of production ML workflows. Each section introduces new tools and techniques, guiding you to automate, deploy, and monitor models efficiently. By blending practical exercises with continuous assessments, you'll develop the confidence to manage complex ML Ops tasks on Google Cloud.
Key Features
- Build and deploy containerized ML models using Google Cloud services
- Automate CI/CD workflows for reliable, repeatable model updates
- Orchestrate advanced ML pipelines with Vertex AI and Kubeflow for scalability
Target Audience
Ideal for data scientists, ML engineers, and DevOps professionals who already understand Python, machine learning basics, and cloud concepts. If you have experience with Docker and CI/CD practices, you'll get the most out of this program. It's designed for those ready to deepen their expertise in automating and scaling ML workflows on Google Cloud.
