Course
Skills
Machine Learning Operations (MLOps): Getting Started
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud.
What you'll learn
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
Table of contents
Welcome to the Machine Learning Operations (MLOps): Getting Started
4mins
Employing Machine Learning Operations
24mins
Vertex AI and MLOps on Vertex AI
31mins
- What is vertex ai and why does a unified platform matter? 5m
- Introduction to mlops on vertex ai 9m
- How does vertex ai help with the mlops workflow, part 1? 5m
- How does vertex ai help with the mlops workflow, part 2? 8m
- Reading list 0m
- Pluralsight: Getting Started with GCP and Qwiklabs 4m
- Lab introduction Vertex AI: Qwik Start 0m
- Lab: Training and Deploying a TensorFlow Model in Vertex AI 0m
Summary
2mins
