Machine Learning Operations (MLOps) with Vertex AI: Manage Features explores the tools and practices used to support machine learning systems in production systems on Google Cloud.
Designed for professionals working with operational ML workflows, this course introduces core MLOps concepts related to deployment, testing, monitoring, automation, and feature management. You’ll gain hands-on experience working with Vertex AI Feature Store and examine how production ML systems are managed at scale.
This course explores the role of feature management within MLOps workflows, including:
- Managing and reusing machine learning features across workflows and environments
- Working with Vertex AI Feature Store for feature ingestion and organization
- Supporting reproducibility and consistency across ML development workflows
- Using feature management practices to improve operational efficiency in ML environments
You’ll use Vertex AI Feature Store streaming ingestion at the SDK Layer while exploring how feature management supports consistency and efficiency across machine learning workflows, and how to organize machine learning assets to support repeatable experimentation practices.
By the end of this course, you’ll be able to work with Vertex AI Feature Store and apply foundational MLOps practices to support machine learning systems on Google Cloud.
