Machine Learning Operations (MLOps) with Vertex AI: Manage Features (Coursera)

Machine Learning Operations (MLOps) with Vertex AI: Manage Features (Coursera)
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Machine Learning Operations (MLOps) with Vertex AI: Manage Features (Coursera)
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



MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Course Auditing
45.00 EUR
No previous experience necessary.

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.