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 Operations (MLOps) with Vertex AI: Manage Features

Instructor: Google Cloud Training
Access provided by Google
1,576 already enrolled
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

Add to your LinkedIn profile
See how employees at top companies are mastering in-demand skills


Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review

There are 4 modules in this course
Introduction to the course.
What's included
1 video
Vertex AI and its MLOps capabilities. Main challenges related to data and potential solutions to mitigate them.
What's included
3 videos
Key capabilities of Vertex AI Feature Store
What's included
4 videos1 app item
Summary of the course
What's included
1 video
Instructor

Offered by
Why people choose Coursera for their career




Recommended if you're interested in Information Technology


Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree
Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy