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. Learners will get hands-on practice using Vertex AI Feature Store's streaming ingestion at the SDK layer.
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What you'll learn
- Containerize ML workflows for reproducibility, reuse, and scalable training and inference on Google Cloud
- Efficiently share, discover, and re-use ML features at scale while conducting reproducible ML experiments with Vertex AI Feature Store
Syllabus
Welcome to the Machine Learning Operations (MLOps) with Vertex AI: Manage Features
Module 1
Introduction to the course.
Introduction to Vertex AI Feature Store
Module 2
Vertex AI and its MLOps capabilities. Main challenges related to data and potential solutions to mitigate them.
Machine Learning Operations (MLOps) with Vertex AI: Manage Features An in depth look
Module 3
Key capabilities of Vertex AI Feature Store
Summary
Module 4
Summary of the course
