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URL: https://www.coursera.org/learn/machine-learning-operations-with-vertex-ai-manage-features

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

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

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

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Gain insight into a topic and learn the fundamentals.
4.1

16 reviews

Intermediate level
Some related experience required
2 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.1

16 reviews

Intermediate level
Some related experience required
2 hours to complete
Flexible schedule
Learn at your own pace

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

Details to know

Shareable certificate

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Taught in English

Build your subject-matter expertise

This course is part of the Machine Learning Operations (MLOps) on Google Cloud Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 4 modules in this course

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.

Introduction to the course.

What's included

1 video

1 video•Total 3 minutes
  • Course Introduction•3 minutes

Vertex AI and its MLOps capabilities. Main challenges related to data and potential solutions to mitigate them.

What's included

3 videos

3 videos•Total 9 minutes
  • Recap: How does Vertex AI help with the MLOps workflow?•2 minutes
  • Introduction to Vertex AI Feature Store•0 minutes
  • Introduction to Vertex AI Feature Store - Demo •7 minutes

Key capabilities of Vertex AI Feature Store

What's included

4 videos1 app item1 plugin

4 videos•Total 21 minutes
  • Main capabilities of Vertex AI Feature Store•4 minutes
  • Data Model in Vertex AI Feature Store•11 minutes
  • Introduction to Vertex AI Feature Store•6 minutes
  • Lab Intro: Feature Store: Streaming Ingestion SDK•0 minutes
1 app item•Total 90 minutes
  • Lab: Feature Store: Streaming Ingestion SDK•90 minutes
1 plugin•Total 15 minutes
  • Accessing and completing labs•15 minutes

Summary of the course

What's included

1 video

1 video•Total 2 minutes
  • Summary•2 minutes

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Instructor

Google Cloud
2,244 Courses•4,416,115 learners

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Frequently asked questions

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